diff --git "a/wandb/wandb/run-20260415_125137-5wrix5f2/files/output.log" "b/wandb/wandb/run-20260415_125137-5wrix5f2/files/output.log" new file mode 100644--- /dev/null +++ "b/wandb/wandb/run-20260415_125137-5wrix5f2/files/output.log" @@ -0,0 +1,2068 @@ +04/15 [12:51:39] INFO  | >> ***** Training Configuration ***** ]8;id=935518;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=571858;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#346\346]8;;\ +  INFO  | >> Total optimization steps = 800000 ]8;id=98246;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=229258;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#347\347]8;;\ +  INFO  | >> Per device batch size = 8 ]8;id=208496;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=750800;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#348\348]8;;\ +  INFO  | >> Gradient accumulation steps = 1 ]8;id=471029;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=617889;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#349\349]8;;\ +  INFO  | >> Total batch size = 64 ]8;id=844962;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=167414;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#350\350]8;;\ +  INFO  | >> 📊 Accessed config snapshot saved to results/Checkpoints/0415_libero4in1_WanOFT/config.yaml ]8;id=225772;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=800581;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#279\279]8;;\ + 0%| | 1100/800000 [45:37<430:45:58, 1.94s/it, data_times=0.000, model_times=1.761] +04/15 [12:55:45] INFO  | >> Step 100, Loss: {'action_dit_loss': 0.2311452329158783, 'mse_score': 0.015102453529834747, ]8;id=376417;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=888662;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008701774291694164, 'model_time': 1.8750573685392737, 'learning_rate':   +  2.0000000000000003e-06, 'epoch': 0.02})   +04/15 [12:59:53] INFO  | >> Step 200, Loss: {'action_dit_loss': 0.2322949469089508, 'mse_score': 0.018796831369400024, ]8;id=45561;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=765179;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007661851122975349, 'model_time': 1.7167812883853912, 'learning_rate':   +  4.000000000000001e-06, 'epoch': 0.03})   +04/15 [13:04:09] INFO  | >> Step 300, Loss: {'action_dit_loss': 0.28165072202682495, 'mse_score': 0.015275124992643083, ]8;id=396922;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=82627;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0004352470859885216, 'model_time': 1.3603750672191381, 'learning_rate': 6e-06,   +  'epoch': 0.05})   +04/15 [13:08:16] INFO  | >> Step 400, Loss: {'action_dit_loss': 0.27280279994010925, 'mse_score': 0.02003167356763567, ]8;id=648564;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=928463;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0004037804901599884, 'model_time': 1.9987561302259564, 'learning_rate':   +  8.000000000000001e-06, 'epoch': 0.06})   +04/15 [13:12:22] INFO  | >> Step 500, Loss: {'action_dit_loss': 0.25735825300216675, 'mse_score': 0.01958099220480238, ]8;id=738797;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=72933;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007863136008381844, 'model_time': 1.6904770769178867, 'learning_rate': 1e-05, 'epoch':   +  0.08})   +04/15 [13:16:39] INFO  | >> Step 600, Loss: {'action_dit_loss': 0.27335649728775024, 'mse_score': 0.01705597766808101, ]8;id=303445;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=83667;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009744423441588879, 'model_time': 1.3451588787138462, 'learning_rate': 1.2e-05,   +  'epoch': 0.09})   +04/15 [13:20:46] INFO  | >> Step 700, Loss: {'action_dit_loss': 0.277921587228775, 'mse_score': 0.020645248038428172, ]8;id=398591;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=291476;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00030484143644571304, 'model_time': 1.936359442770481, 'learning_rate':   +  1.4000000000000001e-05, 'epoch': 0.11})   +04/15 [13:24:53] INFO  | >> Step 800, Loss: {'action_dit_loss': 0.23638026416301727, 'mse_score': 0.017349228262901306, ]8;id=170555;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=388162;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0004036668688058853, 'model_time': 1.6759228156879544, 'learning_rate':   +  1.6000000000000003e-05, 'epoch': 0.13})   +04/15 [13:29:09] INFO  | >> Step 900, Loss: {'action_dit_loss': 0.2795989513397217, 'mse_score': 0.017364336975983212, ]8;id=735911;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=982153;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.005450090393424034, 'model_time': 1.3527773460373282, 'learning_rate': 1.8e-05,   +  'epoch': 0.14})   +04/15 [13:33:16] INFO  | >> Step 1000, Loss: {'action_dit_loss': 0.235279843211174, 'mse_score': 0.015045914266790663, ]8;id=665822;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=179451;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.012604234740138054, 'model_time': 1.9269948787987232, 'learning_rate': 2e-05, 'epoch':   +  0.16})   +04/15 [13:37:18] INFO  | >> Step 1100, Loss: {'action_dit_loss': 0.2167305201292038, 'mse_score': 0.014566598193986076, ]8;id=484714;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=397887;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00034712813794612885, 'model_time': 1.7606455637142062, 'learning_rate':   +  2.2000000000000003e-05, 'epoch': 0.17})   +04/15 [13:41:24] INFO  | >> Step 1200, Loss: {'action_dit_loss': 0.18982774019241333, 'mse_score': 0.014324705515589033, ]8;id=584004;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=230283;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003778589889407158, 'model_time': 1.3236372712999582, 'learning_rate': 2.4e-05,   +  'epoch': 0.19})   +04/15 [13:45:42] INFO  | >> Step 1300, Loss: {'action_dit_loss': 0.18688255548477173, 'mse_score': 0.011654668620654516, ]8;id=813694;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=58655;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.005260930396616459, 'model_time': 1.8628632985055447, 'learning_rate':   +  2.6000000000000002e-05, 'epoch': 0.2})   +04/15 [13:49:48] INFO  | >> Step 1400, Loss: {'action_dit_loss': 0.14111502468585968, 'mse_score': 0.013042900179113661, ]8;id=330776;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=420651;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.010928962379693985, 'model_time': 1.7207593759521842, 'learning_rate':   +  2.8000000000000003e-05, 'epoch': 0.22})   +04/15 [13:53:55] INFO  | >> Step 1500, Loss: {'action_dit_loss': 0.1435604840517044, 'mse_score': 0.011086489473070418, ]8;id=988712;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=594731;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002516321837902069, 'model_time': 1.4125766474753618, 'learning_rate': 3e-05,   +  'epoch': 0.24})   +04/15 [13:58:11] INFO  | >> Step 1600, Loss: {'action_dit_loss': 0.16783052682876587, 'mse_score': 0.009059252483504159, ]8;id=687277;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=523481;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003334116190671921, 'model_time': 1.8800068814307451, 'learning_rate':   +  3.2000000000000005e-05, 'epoch': 0.25})   +04/15 [14:02:18] INFO  | >> Step 1700, Loss: {'action_dit_loss': 0.1654355525970459, 'mse_score': 0.012715935707092285, ]8;id=481141;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=149811;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0047749727964401245, 'model_time': 1.7236609887331724, 'learning_rate':   +  3.4000000000000007e-05, 'epoch': 0.27})   +04/15 [14:06:24] INFO  | >> Step 1800, Loss: {'action_dit_loss': 0.16736425459384918, 'mse_score': 0.011780972991670881, ]8;id=588637;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=565158;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.012787561863660812, 'model_time': 1.3428379036486149, 'learning_rate': 3.6e-05,   +  'epoch': 0.28})   +04/15 [14:10:41] INFO  | >> Step 1900, Loss: {'action_dit_loss': 0.17432111501693726, 'mse_score': 0.007578103137867791, ]8;id=941435;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=611878;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002584196627140045, 'model_time': 1.9083254309371114, 'learning_rate': 3.8e-05,   +  'epoch': 0.3})   +04/15 [14:14:48] INFO  | >> Step 2000, Loss: {'action_dit_loss': 0.11931513249874115, 'mse_score': 0.012382612696715764, ]8;id=534277;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=517488;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00047847162932157516, 'model_time': 1.7328761955723166, 'learning_rate': 4e-05,   +  'epoch': 0.32})   +04/15 [14:18:55] INFO  | >> Step 2100, Loss: {'action_dit_loss': 0.10377104580402374, 'mse_score': 0.009141774049827031, ]8;id=114975;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=160265;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004405133426189423, 'model_time': 1.367800067178905, 'learning_rate': 4.2e-05,   +  'epoch': 0.33})   +04/15 [14:23:10] INFO  | >> Step 2200, Loss: {'action_dit_loss': 0.13536213338375092, 'mse_score': 0.010576019329684121, ]8;id=442666;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=625380;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0084876399487257, 'model_time': 1.9927370054647326, 'learning_rate':   +  4.4000000000000006e-05, 'epoch': 0.35})   +04/15 [14:27:18] INFO  | >> Step 2300, Loss: {'action_dit_loss': 0.11961809545755386, 'mse_score': 0.010605585362230028, ]8;id=490785;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=554816;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004810190759599209, 'model_time': 1.6962281446903944, 'learning_rate':   +  4.600000000000001e-05, 'epoch': 0.36})   +04/15 [14:31:24] INFO  | >> Step 2400, Loss: {'action_dit_loss': 0.11251465231180191, 'mse_score': 0.009916705744607108, ]8;id=12038;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=713328;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00024387426674365997, 'model_time': 1.336913438513875, 'learning_rate': 4.8e-05,   +  'epoch': 0.38})   +04/15 [14:35:41] INFO  | >> Step 2500, Loss: {'action_dit_loss': 0.09264562278985977, 'mse_score': 0.008596763546977724, ]8;id=563054;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=787352;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0047557419165968895, 'model_time': 1.944807132706046, 'learning_rate': 5e-05, 'epoch':   +  0.39})   +04/15 [14:39:48] INFO  | >> Step 2600, Loss: {'action_dit_loss': 0.16344282031059265, 'mse_score': 0.010671222848551614, ]8;id=116970;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=307757;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008800327777862549, 'model_time': 1.7191461874172091, 'learning_rate':   +  5.2000000000000004e-05, 'epoch': 0.41})   +04/15 [14:43:54] INFO  | >> Step 2700, Loss: {'action_dit_loss': 0.19925013184547424, 'mse_score': 0.00866386347583362, ]8;id=757168;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=918398;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004862348549067974, 'model_time': 1.317508365958929, 'learning_rate':   +  5.4000000000000005e-05, 'epoch': 0.43})   +04/15 [14:48:11] INFO  | >> Step 2800, Loss: {'action_dit_loss': 0.13141438364982605, 'mse_score': 0.006932773760386876, ]8;id=187330;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=532342;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003072349354624748, 'model_time': 1.9665582329034805, 'learning_rate':   +  5.6000000000000006e-05, 'epoch': 0.44})   +04/15 [14:52:17] INFO  | >> Step 2900, Loss: {'action_dit_loss': 0.14999228715896606, 'mse_score': 0.010462501219340734, ]8;id=312942;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=882554;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.003940843045711517, 'model_time': 1.6965030366554856, 'learning_rate': 5.8e-05,   +  'epoch': 0.46})   +04/15 [14:56:20] INFO  | >> Step 3000, Loss: {'action_dit_loss': 0.09718113392591476, 'mse_score': 0.011717751622200012, ]8;id=160263;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=392077;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0074804071336984634, 'model_time': 1.2893523294478655, 'learning_rate': 6e-05,   +  'epoch': 0.47})   +04/15 [15:00:34] INFO  | >> Step 3100, Loss: {'action_dit_loss': 0.17661555111408234, 'mse_score': 0.006169574069125312, ]8;id=816449;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=967242;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0048571620136499405, 'model_time': 8.528589708730578, 'learning_rate': 6.2e-05,   +  'epoch': 0.49})   +04/15 [15:04:43] INFO  | >> Step 3200, Loss: {'action_dit_loss': 0.11879130452871323, 'mse_score': 0.006040634853499276, ]8;id=339902;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=512340;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.000268339179456234, 'model_time': 1.6824241615831852, 'learning_rate':   +  6.400000000000001e-05, 'epoch': 0.5})   +04/15 [15:08:49] INFO  | >> Step 3300, Loss: {'action_dit_loss': 0.10991456359624863, 'mse_score': 0.007344892514603478, ]8;id=921406;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=872064;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.005770275369286537, 'model_time': 1.3461255263537169, 'learning_rate': 6.6e-05,   +  'epoch': 0.52})   +04/15 [15:13:02] INFO  | >> Step 3400, Loss: {'action_dit_loss': 0.09789715707302094, 'mse_score': 0.010720948023455483, ]8;id=252572;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=920659;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0077662235125899315, 'model_time': 8.196263023652136, 'learning_rate':   +  6.800000000000001e-05, 'epoch': 0.54})   +04/15 [15:17:13] INFO  | >> Step 3500, Loss: {'action_dit_loss': 0.1503371298313141, 'mse_score': 0.008503796266657966, ]8;id=767460;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=509597;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004449355415999889, 'model_time': 1.7807504562661052, 'learning_rate': 7e-05, 'epoch':   +  0.55})   +04/15 [15:21:19] INFO  | >> Step 3600, Loss: {'action_dit_loss': 0.10609789192676544, 'mse_score': 0.00972526946238109, ]8;id=803035;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=131869;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003843773156404495, 'model_time': 1.3169615445658565, 'learning_rate': 7.2e-05,   +  'epoch': 0.57})   +04/15 [15:25:33] INFO  | >> Step 3700, Loss: {'action_dit_loss': 0.10769832879304886, 'mse_score': 0.007045517542532512, ]8;id=576510;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=173148;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004711818881332874, 'model_time': 8.555423486977816, 'learning_rate': 7.4e-05,   +  'epoch': 0.58})   +04/15 [15:29:39] INFO  | >> Step 3800, Loss: {'action_dit_loss': 0.09230568259954453, 'mse_score': 0.011578487498419625, ]8;id=443692;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=222086;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009124496951699257, 'model_time': 2.2186738215386868, 'learning_rate': 7.6e-05,   +  'epoch': 0.6})   +04/15 [15:33:44] INFO  | >> Step 3900, Loss: {'action_dit_loss': 0.12966124713420868, 'mse_score': 0.00959487578698567, ]8;id=723378;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=210922;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004708347842097282, 'model_time': 1.3908668272197247, 'learning_rate':   +  7.800000000000001e-05, 'epoch': 0.61})   +04/15 [15:37:50] INFO  | >> Step 4000, Loss: {'action_dit_loss': 0.07835473865270615, 'mse_score': 0.009336237396512712, ]8;id=681446;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=391559;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.000618654303252697, 'model_time': 1.9867321345955133, 'learning_rate': 8e-05, 'epoch':   +  0.63})   +04/15 [15:42:07] INFO  | >> Step 4100, Loss: {'action_dit_loss': 0.08853168785572052, 'mse_score': 0.007075905267681394, ]8;id=126882;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=259947;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004528310149908066, 'model_time': 5.229576771147549, 'learning_rate': 8.2e-05,   +  'epoch': 0.65})   +04/15 [15:46:15] INFO  | >> Step 4200, Loss: {'action_dit_loss': 0.09516461193561554, 'mse_score': 0.006063458110604968, ]8;id=616886;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=580828;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00827904511243105, 'model_time': 1.2970036221668124, 'learning_rate': 8.4e-05,   +  'epoch': 0.66})   +04/15 [15:50:21] INFO  | >> Step 4300, Loss: {'action_dit_loss': 0.10856106877326965, 'mse_score': 0.00668996519276074, ]8;id=74441;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=742225;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004367891699075699, 'model_time': 1.963155336678028, 'learning_rate': 8.6e-05,   +  'epoch': 0.68})   +04/15 [15:54:38] INFO  | >> Step 4400, Loss: {'action_dit_loss': 0.10262586921453476, 'mse_score': 0.008907089275973184, ]8;id=949401;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=32938;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0008380105718970299, 'model_time': 5.283092305064201, 'learning_rate':   +  8.800000000000001e-05, 'epoch': 0.69})   +04/15 [15:58:45] INFO  | >> Step 4500, Loss: {'action_dit_loss': 0.11811632663011551, 'mse_score': 0.009387584669249398, ]8;id=249565;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=292004;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004263412207365036, 'model_time': 1.433085777796805, 'learning_rate': 9e-05, 'epoch':   +  0.71})   +04/15 [16:02:51] INFO  | >> Step 4600, Loss: {'action_dit_loss': 0.13604062795639038, 'mse_score': 0.010227464139461517, ]8;id=138739;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=758490;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00775928795337677, 'model_time': 1.9786125300452113, 'learning_rate':   +  9.200000000000001e-05, 'epoch': 0.73})   +04/15 [16:07:07] INFO  | >> Step 4700, Loss: {'action_dit_loss': 0.13488611578941345, 'mse_score': 0.007393198353903634, ]8;id=495631;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=254801;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00487905740737915, 'model_time': 4.878601481206715, 'learning_rate': 9.4e-05, 'epoch':   +  0.74})   +04/15 [16:11:14] INFO  | >> Step 4800, Loss: {'action_dit_loss': 0.1059974655508995, 'mse_score': 0.0052279989634241375, ]8;id=199659;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=98907;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0007694205269217491, 'model_time': 1.3380100578069687, 'learning_rate': 9.6e-05,   +  'epoch': 0.76})   +04/15 [16:15:22] INFO  | >> Step 4900, Loss: {'action_dit_loss': 0.18266096711158752, 'mse_score': 0.0069617410855633876, ]8;id=444154;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=431071;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004393353126943111, 'model_time': 1.9269312052056193, 'learning_rate': 9.8e-05,   +  'epoch': 0.77})   +04/15 [16:19:38] INFO  | >> Step 5000, Loss: {'action_dit_loss': 0.09196247905492783, 'mse_score': 0.007804098406008312, ]8;id=706073;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=685197;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009222113527357578, 'model_time': 6.1959704188629985, 'learning_rate': 0.0001,   +  'epoch': 0.79})   +04/15 [16:23:44] INFO  | >> Step 5100, Loss: {'action_dit_loss': 0.0921001136302948, 'mse_score': 0.011524632573127747, ]8;id=763587;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=355784;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004738820716738701, 'model_time': 1.3264180002734065, 'learning_rate':   +  9.999999625219726e-05, 'epoch': 0.8})   +04/15 [16:27:51] INFO  | >> Step 5200, Loss: {'action_dit_loss': 0.1473020315170288, 'mse_score': 0.009478921336787087, ]8;id=200896;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=199448;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00035053305327892303, 'model_time': 2.0007482739165425, 'learning_rate':   +  9.999998500878964e-05, 'epoch': 0.82})   +04/15 [16:32:08] INFO  | >> Step 5300, Loss: {'action_dit_loss': 0.09220493584871292, 'mse_score': 0.006147764090980802, ]8;id=192401;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=292075;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004343067295849323, 'model_time': 5.243287725374103, 'learning_rate':   +  9.999996626977886e-05, 'epoch': 0.84})   +04/15 [16:36:14] INFO  | >> Step 5400, Loss: {'action_dit_loss': 0.1126035749912262, 'mse_score': 0.011077352932521276, ]8;id=79046;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=464656;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.006994801573455334, 'model_time': 1.3299116278067231, 'learning_rate':   +  9.99999400351679e-05, 'epoch': 0.85})   +04/15 [16:40:21] INFO  | >> Step 5500, Loss: {'action_dit_loss': 0.11401397734880447, 'mse_score': 0.011004563953195299, ]8;id=102664;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=53045;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.006014087237417698, 'model_time': 1.8836404038593173, 'learning_rate':   +  9.999990630496082e-05, 'epoch': 0.87})   +04/15 [16:44:38] INFO  | >> Step 5600, Loss: {'action_dit_loss': 0.09679253399372101, 'mse_score': 0.009043859583990914, ]8;id=97793;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=971366;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003438536077737808, 'model_time': 4.538538129068911, 'learning_rate':   +  9.999986507916289e-05, 'epoch': 0.88})   +04/15 [16:48:44] INFO  | >> Step 5700, Loss: {'action_dit_loss': 0.09824160486459732, 'mse_score': 0.006738983626876559, ]8;id=426156;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=509231;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0049042049795389175, 'model_time': 1.3381031230092049, 'learning_rate':   +  9.999981635778056e-05, 'epoch': 0.9})   +04/15 [16:52:51] INFO  | >> Step 5800, Loss: {'action_dit_loss': 0.1331956684589386, 'mse_score': 0.008428627891199929, ]8;id=946279;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=61483;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00818316638469696, 'model_time': 1.9763716366142035, 'learning_rate':   +  9.999976014082142e-05, 'epoch': 0.91})   +04/15 [16:57:08] INFO  | >> Step 5900, Loss: {'action_dit_loss': 0.11063128709793091, 'mse_score': 0.00904554980141776, ]8;id=278085;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=971524;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004138507880270481, 'model_time': 5.668315075337887, 'learning_rate':   +  9.999969642829427e-05, 'epoch': 0.93})   +04/15 [17:01:14] INFO  | >> Step 6000, Loss: {'action_dit_loss': 0.08508355170488358, 'mse_score': 0.008404456079006195, ]8;id=443555;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=730429;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002446882426738739, 'model_time': 1.3801049776375294, 'learning_rate':   +  9.999962522020904e-05, 'epoch': 0.95})   +04/15 [17:05:21] INFO  | >> Step 6100, Loss: {'action_dit_loss': 0.08704421669244766, 'mse_score': 0.005854006324495588, ]8;id=753305;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=510311;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.005026441067457199, 'model_time': 1.9537249226123095, 'learning_rate':   +  9.999954651657686e-05, 'epoch': 0.96})   +04/15 [17:09:38] INFO  | >> Step 6200, Loss: {'action_dit_loss': 0.08010870218276978, 'mse_score': 0.008503721228667669, ]8;id=61324;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=607314;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008612032979726791, 'model_time': 4.311529686674476, 'learning_rate':   +  9.999946031741005e-05, 'epoch': 0.98})   +04/15 [17:13:46] INFO  | >> Step 6300, Loss: {'action_dit_loss': 0.1025165542960167, 'mse_score': 0.01069117124591555, ]8;id=328838;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=59942;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.016715417616069317, 'model_time': 1.3045243388041854, 'learning_rate':   +  9.9999366622722e-05, 'epoch': 0.99})   +04/15 [17:17:51] INFO  | >> Step 6400, Loss: {'action_dit_loss': 0.08935461193323135, 'mse_score': 0.0061520300805568695, ]8;id=964047;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=894141;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00031847506761550903, 'model_time': 1.9712728392332792, 'learning_rate':   +  9.99992654325274e-05, 'epoch': 1.01})   +04/15 [17:22:08] INFO  | >> Step 6500, Loss: {'action_dit_loss': 0.10234634578227997, 'mse_score': 0.006150334009102413, ]8;id=84002;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=892697;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0006170142441987991, 'model_time': 4.978736076503992, 'learning_rate':   +  9.999915674684202e-05, 'epoch': 1.02})   +04/15 [17:26:15] INFO  | >> Step 6600, Loss: {'action_dit_loss': 0.08305777609348297, 'mse_score': 0.007512680121830532, ]8;id=708011;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=903682;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003865491598844528, 'model_time': 1.3437553001567721, 'learning_rate':   +  9.999904056568285e-05, 'epoch': 1.04})   +04/15 [17:30:22] INFO  | >> Step 6700, Loss: {'action_dit_loss': 0.08248062431812286, 'mse_score': 0.0075581978474344525, ]8;id=933533;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=597347;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.017522244714200497, 'model_time': 2.040482295677066, 'learning_rate':   +  9.999891688906803e-05, 'epoch': 1.06})   +04/15 [17:34:38] INFO  | >> Step 6800, Loss: {'action_dit_loss': 0.09541381150484085, 'mse_score': 0.005859695374965668, ]8;id=649468;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=85965;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0004765251651406288, 'model_time': 5.037772970274091, 'learning_rate':   +  9.999878571701688e-05, 'epoch': 1.07})   +04/15 [17:38:41] INFO  | >> Step 6900, Loss: {'action_dit_loss': 0.07799283415079117, 'mse_score': 0.005258857671703611, ]8;id=548177;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=331737;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0006142985075712204, 'model_time': 1.3059754790738225, 'learning_rate':   +  9.999864704954987e-05, 'epoch': 1.09})   +04/15 [17:42:46] INFO  | >> Step 7000, Loss: {'action_dit_loss': 0.07990868389606476, 'mse_score': 0.005439733288117817, ]8;id=750981;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=329445;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0004932833835482597, 'model_time': 1.9718434605747461, 'learning_rate':   +  9.999850088668865e-05, 'epoch': 1.1})   +04/15 [17:46:53] INFO  | >> Step 7100, Loss: {'action_dit_loss': 0.0950927585363388, 'mse_score': 0.006484907120466232, ]8;id=704318;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=676856;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.015216344967484474, 'model_time': 1.7269531190395355, 'learning_rate':   +  9.999834722845607e-05, 'epoch': 1.12})   +04/15 [17:51:09] INFO  | >> Step 7200, Loss: {'action_dit_loss': 0.08100375533103943, 'mse_score': 0.004918300147567477, ]8;id=788387;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=981188;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0005209017544984818, 'model_time': 1.4293371802195907, 'learning_rate':   +  9.99981860748761e-05, 'epoch': 1.14})   +04/15 [17:55:16] INFO  | >> Step 7300, Loss: {'action_dit_loss': 0.09690417349338531, 'mse_score': 0.007964119847331728, ]8;id=590341;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=104837;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00027349870651960373, 'model_time': 1.8602231331169605, 'learning_rate':   +  9.99980174259739e-05, 'epoch': 1.15})   +04/15 [17:59:22] INFO  | >> Step 7400, Loss: {'action_dit_loss': 0.08208435028791428, 'mse_score': 0.005609021655150822, ]8;id=278082;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=138890;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003862529993057251, 'model_time': 1.711327730678022, 'learning_rate':   +  9.999784128177584e-05, 'epoch': 1.17})   +04/15 [18:03:39] INFO  | >> Step 7500, Loss: {'action_dit_loss': 0.0803559198975563, 'mse_score': 0.006009623408317566, ]8;id=921981;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=256150;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.01605005096644163, 'model_time': 1.2980770180001855, 'learning_rate':   +  9.99976576423094e-05, 'epoch': 1.18})   +04/15 [18:07:46] INFO  | >> Step 7600, Loss: {'action_dit_loss': 0.09983451664447784, 'mse_score': 0.00787055492401123, ]8;id=874244;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=569605;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00031965505331754684, 'model_time': 1.9410744281485677, 'learning_rate':   +  9.999746650760327e-05, 'epoch': 1.2})   +04/15 [18:11:53] INFO  | >> Step 7700, Loss: {'action_dit_loss': 0.09290974587202072, 'mse_score': 0.00476926618388721, ]8;id=685743;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=554634;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00036683306097984314, 'model_time': 1.6888857707381248, 'learning_rate':   +  9.999726787768727e-05, 'epoch': 1.21})   +04/15 [18:16:09] INFO  | >> Step 7800, Loss: {'action_dit_loss': 0.09137774258852005, 'mse_score': 0.008471116423606873, ]8;id=313921;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=977017;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0006492789834737778, 'model_time': 1.3326879516243935, 'learning_rate':   +  9.999706175259244e-05, 'epoch': 1.23})   +04/15 [18:20:16] INFO  | >> Step 7900, Loss: {'action_dit_loss': 0.08261715620756149, 'mse_score': 0.005062166601419449, ]8;id=140814;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=277312;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.01562977023422718, 'model_time': 1.961297495290637, 'learning_rate':   +  9.9996848132351e-05, 'epoch': 1.25})   +04/15 [18:24:23] INFO  | >> Step 8000, Loss: {'action_dit_loss': 0.06910717487335205, 'mse_score': 0.010499572115285056, ]8;id=580097;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=162998;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00065621268004179, 'model_time': 1.7946613654494286, 'learning_rate':   +  9.999662701699624e-05, 'epoch': 1.26})   +04/15 [18:28:39] INFO  | >> Step 8100, Loss: {'action_dit_loss': 0.07357179373502731, 'mse_score': 0.005322820906128202, ]8;id=752470;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=359536;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00032788142561912537, 'model_time': 1.381612878292799, 'learning_rate':   +  9.999639840656274e-05, 'epoch': 1.28})   +04/15 [18:32:46] INFO  | >> Step 8200, Loss: {'action_dit_loss': 0.09231642633676529, 'mse_score': 0.0054421573877334595, ]8;id=276807;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=529959;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00037435349076986313, 'model_time': 1.8717349283397198, 'learning_rate':   +  9.999616230108617e-05, 'epoch': 1.29})   +04/15 [18:36:53] INFO  | >> Step 8300, Loss: {'action_dit_loss': 0.09431097656488419, 'mse_score': 0.007234001266104835, ]8;id=887204;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=53266;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.017284924164414406, 'model_time': 1.6858759438619018, 'learning_rate':   +  9.999591870060343e-05, 'epoch': 1.31})   +04/15 [18:41:09] INFO  | >> Step 8400, Loss: {'action_dit_loss': 0.08749154955148697, 'mse_score': 0.005730758820261274, ]8;id=290120;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=46228;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003723828122019768, 'model_time': 1.3211838938295841, 'learning_rate':   +  9.999566760515252e-05, 'epoch': 1.32})   +04/15 [18:45:17] INFO  | >> Step 8500, Loss: {'action_dit_loss': 0.07278335094451904, 'mse_score': 0.006794147725616183, ]8;id=668061;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=274680;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00023322366178035736, 'model_time': 1.9060166031122208, 'learning_rate':   +  9.999540901477269e-05, 'epoch': 1.34})   +04/15 [18:49:23] INFO  | >> Step 8600, Loss: {'action_dit_loss': 0.07760816812515259, 'mse_score': 0.005391439156872886, ]8;id=739945;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=448462;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00030838698148727417, 'model_time': 1.6994356866925955, 'learning_rate':   +  9.999514292950431e-05, 'epoch': 1.36})   +04/15 [18:53:39] INFO  | >> Step 8700, Loss: {'action_dit_loss': 0.09328819066286087, 'mse_score': 0.00810794425862176, ]8;id=990957;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=926004;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.015429748222231865, 'model_time': 1.3031497150659561, 'learning_rate':   +  9.999486934938894e-05, 'epoch': 1.37})   +04/15 [18:57:46] INFO  | >> Step 8800, Loss: {'action_dit_loss': 0.06666361540555954, 'mse_score': 0.004621370562485286, ]8;id=37778;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=875136;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00029501691460609436, 'model_time': 1.9252212299034, 'learning_rate':   +  9.999458827446926e-05, 'epoch': 1.39})   +04/15 [19:01:53] INFO  | >> Step 8900, Loss: {'action_dit_loss': 0.06663500517606735, 'mse_score': 0.0052527279726096564, ]8;id=450664;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=133636;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0005739331245422363, 'model_time': 1.6922539416700602, 'learning_rate':   +  9.999429970478919e-05, 'epoch': 1.4})   +04/15 [19:06:09] INFO  | >> Step 9000, Loss: {'action_dit_loss': 0.06630684435367584, 'mse_score': 0.006124632166964667, ]8;id=978413;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=834794;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0005093822255730629, 'model_time': 1.382619851268828, 'learning_rate':   +  9.999400364039382e-05, 'epoch': 1.42})   +04/15 [19:10:16] INFO  | >> Step 9100, Loss: {'action_dit_loss': 0.0621187686920166, 'mse_score': 0.0062348560563155585, ]8;id=220281;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=715198;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.02004116214811802, 'model_time': 1.9284409182146192, 'learning_rate':   +  9.999370008132935e-05, 'epoch': 1.43})   +04/15 [19:14:23] INFO  | >> Step 9200, Loss: {'action_dit_loss': 0.06066310405731201, 'mse_score': 0.007073200174740383, ]8;id=818011;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=587080;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003839777782559395, 'model_time': 1.6763262143358588, 'learning_rate':   +  9.999338902764316e-05, 'epoch': 1.45})   +04/15 [19:18:39] INFO  | >> Step 9300, Loss: {'action_dit_loss': 0.09490495175123215, 'mse_score': 0.005069972681147712, ]8;id=785884;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=162060;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002297181636095047, 'model_time': 1.3444302277639508, 'learning_rate':   +  9.999307047938387e-05, 'epoch': 1.47})   +04/15 [19:22:46] INFO  | >> Step 9400, Loss: {'action_dit_loss': 0.05221797153353691, 'mse_score': 0.005218295114380973, ]8;id=170395;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=838742;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003495737910270691, 'model_time': 1.9054341036826372, 'learning_rate':   +  9.999274443660123e-05, 'epoch': 1.48})   +04/15 [19:26:52] INFO  | >> Step 9500, Loss: {'action_dit_loss': 0.06420296430587769, 'mse_score': 0.006522330322435924, ]8;id=25990;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=188073;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.015320513397455215, 'model_time': 1.6453262194991112, 'learning_rate':   +  9.99924108993461e-05, 'epoch': 1.5})   +04/15 [19:31:09] INFO  | >> Step 9600, Loss: {'action_dit_loss': 0.06583824008703232, 'mse_score': 0.00440847288284983, ]8;id=976031;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=431712;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002537313848733902, 'model_time': 1.3183366786688566, 'learning_rate':   +  9.999206986767061e-05, 'epoch': 1.51})   +04/15 [19:35:16] INFO  | >> Step 9700, Loss: {'action_dit_loss': 0.06113598868250847, 'mse_score': 0.00498503286923681, ]8;id=850132;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=260222;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00033017899841070175, 'model_time': 1.9125207429751754, 'learning_rate':   +  9.9991721341628e-05, 'epoch': 1.53})   +04/15 [19:39:23] INFO  | >> Step 9800, Loss: {'action_dit_loss': 0.07397589087486267, 'mse_score': 0.004445936264736312, ]8;id=113346;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=401124;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004079524427652359, 'model_time': 1.6914480598643422, 'learning_rate':   +  9.999136532127269e-05, 'epoch': 1.55})   +04/15 [19:43:38] INFO  | >> Step 9900, Loss: {'action_dit_loss': 0.0747055858373642, 'mse_score': 0.004101833860789027, ]8;id=233238;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=209267;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.011447666212916374, 'model_time': 1.5578847611323, 'learning_rate':   +  9.99910018066603e-05, 'epoch': 1.56})   +04/15 [19:47:46] INFO  | >> Step 10000, Loss: {'action_dit_loss': 0.08454509824514389, 'mse_score': 0.005404854991606304, ]8;id=320015;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=860394;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00036359112709760666, 'model_time': 1.9686749521642923, 'learning_rate':   +  9.999063079784757e-05, 'epoch': 1.58})   +✅ Checkpoint saved at ./results/Checkpoints/0415_libero4in1_WanOFT/checkpoints/steps_10000 +04/15 [19:48:37] INFO  | >> 📊 Saving accessed configuration... ]8;id=692094;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=202511;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#238\238]8;;\ +  INFO  | >> 📦 Saving full merged configuration to ]8;id=810891;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=292683;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#242\242]8;;\ +  `results/Checkpoints/0415_libero4in1_WanOFT/config.full.yaml`...   +  INFO  | >> ✅ Configuration files saved ]8;id=884642;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=562262;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#244\244]8;;\ +04/15 [19:52:43] INFO  | >> Step 10100, Loss: {'action_dit_loss': 0.07676355540752411, 'mse_score': 0.0056398000035967144, ]8;id=919641;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=273903;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.000429278239607811, 'model_time': 1.705812611617148, 'learning_rate':   +  9.999025229489244e-05, 'epoch': 1.59})   +04/15 [19:56:49] INFO  | >> Step 10200, Loss: {'action_dit_loss': 0.09789557754993439, 'mse_score': 0.006802210850375039, ]8;id=113668;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=625550;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004968144930899143, 'model_time': 1.3189940610900521, 'learning_rate':   +  9.998986629785402e-05, 'epoch': 1.61})   +04/15 [20:01:02] INFO  | >> Step 10300, Loss: {'action_dit_loss': 0.08671974390745163, 'mse_score': 0.005576224731547492, ]8;id=328914;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=457592;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.011842509731650352, 'model_time': 8.305435050278902, 'learning_rate':   +  9.998947280679259e-05, 'epoch': 1.62})   +04/15 [20:05:13] INFO  | >> Step 10400, Loss: {'action_dit_loss': 0.06667780876159668, 'mse_score': 0.0042914216007505146, ]8;id=943199;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=604596;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003679320216178894, 'model_time': 1.696342476643622, 'learning_rate':   +  9.998907182176958e-05, 'epoch': 1.64})   +04/15 [20:09:19] INFO  | >> Step 10500, Loss: {'action_dit_loss': 0.0725770890712738, 'mse_score': 0.004663400884185519, ]8;id=457239;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=1773;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003699641674757004, 'model_time': 1.354057589545846, 'learning_rate':   +  9.998866334284764e-05, 'epoch': 1.66})   +04/15 [20:13:32] INFO  | >> Step 10600, Loss: {'action_dit_loss': 0.07621489465236664, 'mse_score': 0.006798816046544484, ]8;id=720221;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=754377;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004722967743873596, 'model_time': 7.927269810810685, 'learning_rate':   +  9.998824737009055e-05, 'epoch': 1.67})   +04/15 [20:17:43] INFO  | >> Step 10700, Loss: {'action_dit_loss': 0.07415547966957092, 'mse_score': 0.003311541197555406, ]8;id=206606;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=381913;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.012401266023516655, 'model_time': 1.7089720834046602, 'learning_rate':   +  9.998782390356323e-05, 'epoch': 1.69})   +04/15 [20:21:49] INFO  | >> Step 10800, Loss: {'action_dit_loss': 0.11737347394227982, 'mse_score': 0.006385414195912225, ]8;id=965498;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=346239;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.000249616801738739, 'model_time': 1.3212471222504973, 'learning_rate':   +  9.998739294333185e-05, 'epoch': 1.7})   +04/15 [20:26:02] INFO  | >> Step 10900, Loss: {'action_dit_loss': 0.09390749782323837, 'mse_score': 0.005470897470201764, ]8;id=130679;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=754717;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00037820544093847275, 'model_time': 8.006148817017674, 'learning_rate':   +  9.998695448946369e-05, 'epoch': 1.72})   +04/15 [20:30:14] INFO  | >> Step 11000, Loss: {'action_dit_loss': 0.059364307671785355, 'mse_score': 0.006638024002313614, ]8;id=699287;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=428231;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004753401502966881, 'model_time': 1.7821536036208272, 'learning_rate':   +  9.99865085420272e-05, 'epoch': 1.73})   +04/15 [20:34:19] INFO  | >> Step 11100, Loss: {'action_dit_loss': 0.07584189623594284, 'mse_score': 0.00516481271811894, ]8;id=581343;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=133470;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.011335819959640503, 'model_time': 1.3718450162559748, 'learning_rate':   +  9.998605510109207e-05, 'epoch': 1.75})   +04/15 [20:38:33] INFO  | >> Step 11200, Loss: {'action_dit_loss': 0.07813660055398941, 'mse_score': 0.006747626300368991, ]8;id=397562;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=710219;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.000362275168299675, 'model_time': 8.474420826882124, 'learning_rate':   +  9.998559416672905e-05, 'epoch': 1.77})   +04/15 [20:42:43] INFO  | >> Step 11300, Loss: {'action_dit_loss': 0.0674796923995018, 'mse_score': 0.0074154532381466454, ]8;id=596750;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=315568;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003361208364367485, 'model_time': 1.6778131444007158, 'learning_rate':   +  9.998512573901017e-05, 'epoch': 1.78})   +04/15 [20:46:49] INFO  | >> Step 11400, Loss: {'action_dit_loss': 0.08102681487798691, 'mse_score': 0.004706193826028279, ]8;id=318635;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=300850;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004211314022541046, 'model_time': 1.3269299333915114, 'learning_rate':   +  9.998464981800856e-05, 'epoch': 1.8})   +04/15 [20:50:52] INFO  | >> Step 11500, Loss: {'action_dit_loss': 0.06337418407201767, 'mse_score': 0.004279272098626409, ]8;id=636130;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=686508;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.012542740441858768, 'model_time': 1.925981804728508, 'learning_rate':   +  9.998416640379852e-05, 'epoch': 1.81})   +04/15 [20:55:08] INFO  | >> Step 11600, Loss: {'action_dit_loss': 0.06959909200668335, 'mse_score': 0.006645524076053074, ]8;id=708446;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=224082;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00027566030621528625, 'model_time': 5.727528732270002, 'learning_rate':   +  9.998367549645556e-05, 'epoch': 1.83})   +04/15 [20:59:14] INFO  | >> Step 11700, Loss: {'action_dit_loss': 0.0670405775308609, 'mse_score': 0.006218068833862033, ]8;id=834692;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=771711;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003162939101457596, 'model_time': 1.4493608307093382, 'learning_rate':   +  9.998317709605632e-05, 'epoch': 1.84})   +04/15 [21:03:21] INFO  | >> Step 11800, Loss: {'action_dit_loss': 0.06337639689445496, 'mse_score': 0.005392426358801978, ]8;id=540490;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=696101;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004141135141253471, 'model_time': 1.8359276866540313, 'learning_rate':   +  9.998267120267866e-05, 'epoch': 1.86})   +04/15 [21:07:38] INFO  | >> Step 11900, Loss: {'action_dit_loss': 0.06407879292964935, 'mse_score': 0.005739559552499226, ]8;id=858179;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=998243;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.013293064199388027, 'model_time': 5.288545316085219, 'learning_rate':   +  9.998215781640155e-05, 'epoch': 1.88})   +04/15 [21:11:44] INFO  | >> Step 12000, Loss: {'action_dit_loss': 0.06525123119354248, 'mse_score': 0.005650676254715238, ]8;id=235552;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=845742;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00023296009749174118, 'model_time': 1.314887197688222, 'learning_rate':   +  9.998163693730518e-05, 'epoch': 1.89})   +04/15 [21:15:52] INFO  | >> Step 12100, Loss: {'action_dit_loss': 0.06260380148887634, 'mse_score': 0.004949788962091718, ]8;id=256736;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=498216;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0004799189046025276, 'model_time': 2.0563902305439115, 'learning_rate':   +  9.998110856547088e-05, 'epoch': 1.91})   +04/15 [21:20:08] INFO  | >> Step 12200, Loss: {'action_dit_loss': 0.07947920262813568, 'mse_score': 0.006236370652914047, ]8;id=477538;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=434572;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004295645281672478, 'model_time': 5.000896113924682, 'learning_rate':   +  9.998057270098116e-05, 'epoch': 1.92})   +04/15 [21:24:14] INFO  | >> Step 12300, Loss: {'action_dit_loss': 0.061275728046894073, 'mse_score': 0.005786046917949404, ]8;id=753240;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=730180;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.01229132991284132, 'model_time': 1.388608817011118, 'learning_rate':   +  9.99800293439197e-05, 'epoch': 1.94})   +04/15 [21:28:21] INFO  | >> Step 12400, Loss: {'action_dit_loss': 0.07636027038097382, 'mse_score': 0.005006017429488046, ]8;id=154739;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=687926;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003755660727620125, 'model_time': 1.8998893070966005, 'learning_rate':   +  9.997947849437135e-05, 'epoch': 1.96})   +04/15 [21:32:38] INFO  | >> Step 12500, Loss: {'action_dit_loss': 0.059518128633499146, 'mse_score': 0.004638671875, ]8;id=902237;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=807451;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.000506632961332798, 'model_time': 5.794092409312725, 'learning_rate':   +  9.997892015242214e-05, 'epoch': 1.97})   +04/15 [21:36:42] INFO  | >> Step 12600, Loss: {'action_dit_loss': 0.05025096982717514, 'mse_score': 0.003654498340828078, ]8;id=229471;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=184430;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004758678376674652, 'model_time': 1.3927090521901846, 'learning_rate':   +  9.997835431815924e-05, 'epoch': 1.99})   +04/15 [21:40:46] INFO  | >> Step 12700, Loss: {'action_dit_loss': 0.054840438067913055, 'mse_score': 0.008289284471954619, ]8;id=52657;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=584482;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00970013253390789, 'model_time': 1.9582413146272302, 'learning_rate':   +  9.997778099167103e-05, 'epoch': 2.0})   +04/15 [21:44:53] INFO  | >> Step 12800, Loss: {'action_dit_loss': 0.07423623651266098, 'mse_score': 0.004767086889062609, ]8;id=478634;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=139816;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00042971502989530563, 'model_time': 1.6903696116060019, 'learning_rate':   +  9.997720017304701e-05, 'epoch': 2.02})   +04/15 [21:49:09] INFO  | >> Step 12900, Loss: {'action_dit_loss': 0.07461877167224884, 'mse_score': 0.004176345520785877, ]8;id=586075;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=624377;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004845727235078812, 'model_time': 1.3514511371031404, 'learning_rate':   +  9.997661186237791e-05, 'epoch': 2.03})   +04/15 [21:53:17] INFO  | >> Step 13000, Loss: {'action_dit_loss': 0.04483398422598839, 'mse_score': 0.005082636539425168, ]8;id=464071;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=642412;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004869410768151283, 'model_time': 2.1378771793097258, 'learning_rate':   +  9.99760160597556e-05, 'epoch': 2.05})   +04/15 [21:57:23] INFO  | >> Step 13100, Loss: {'action_dit_loss': 0.058828338980674744, 'mse_score': 0.0050265054617609295, ]8;id=447470;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=870914;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008348374627530575, 'model_time': 1.6970106279477477, 'learning_rate':   +  9.99754127652731e-05, 'epoch': 2.07})   +04/15 [22:01:39] INFO  | >> Step 13200, Loss: {'action_dit_loss': 0.07252763211727142, 'mse_score': 0.004393791779875755, ]8;id=166889;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=779779;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002475352957844734, 'model_time': 1.4384837374091148, 'learning_rate':   +  9.997480197902463e-05, 'epoch': 2.08})   +04/15 [22:05:46] INFO  | >> Step 13300, Loss: {'action_dit_loss': 0.0558428019285202, 'mse_score': 0.00573515093752316, ]8;id=788295;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=259249;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0049688005819916725, 'model_time': 1.9169507250189781, 'learning_rate':   +  9.997418370110556e-05, 'epoch': 2.1})   +04/15 [22:09:53] INFO  | >> Step 13400, Loss: {'action_dit_loss': 0.06972460448741913, 'mse_score': 0.004819198910679136, ]8;id=815451;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=546622;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004383263178169727, 'model_time': 1.6839090744033456, 'learning_rate':   +  9.997355793161246e-05, 'epoch': 2.11})   +04/15 [22:14:09] INFO  | >> Step 13500, Loss: {'action_dit_loss': 0.04615577310323715, 'mse_score': 0.004356799381119865, ]8;id=461239;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=81247;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008154353126883507, 'model_time': 1.3130203448235989, 'learning_rate':   +  9.997292467064302e-05, 'epoch': 2.13})   +04/15 [22:18:16] INFO  | >> Step 13600, Loss: {'action_dit_loss': 0.04789931699633598, 'mse_score': 0.003184491502387183, ]8;id=352161;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=335239;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003986665979027748, 'model_time': 1.946722156368196, 'learning_rate':   +  9.997228391829617e-05, 'epoch': 2.14})   +04/15 [22:22:23] INFO  | >> Step 13700, Loss: {'action_dit_loss': 0.04521803557872772, 'mse_score': 0.002816063751067434, ]8;id=158157;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=242495;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004852652549743652, 'model_time': 1.69733567815274, 'learning_rate':   +  9.997163567467191e-05, 'epoch': 2.16})   +04/15 [22:26:39] INFO  | >> Step 13800, Loss: {'action_dit_loss': 0.05628303438425064, 'mse_score': 0.00641202021922384, ]8;id=224345;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=67348;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004834366030991077, 'model_time': 1.3196182185783982, 'learning_rate':   +  9.997097993987155e-05, 'epoch': 2.18})   +04/15 [22:30:46] INFO  | >> Step 13900, Loss: {'action_dit_loss': 0.05918266251683235, 'mse_score': 0.005764872900077275, ]8;id=488557;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=435970;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008079959079623222, 'model_time': 1.9737825179472566, 'learning_rate':   +  9.99703167139974e-05, 'epoch': 2.19})   +04/15 [22:34:53] INFO  | >> Step 14000, Loss: {'action_dit_loss': 0.07173842191696167, 'mse_score': 0.003936319212828364, ]8;id=408396;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=948791;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003793509677052498, 'model_time': 1.7206432679668069, 'learning_rate':   +  9.99696459971531e-05, 'epoch': 2.21})   +04/15 [22:39:09] INFO  | >> Step 14100, Loss: {'action_dit_loss': 0.06871532648801804, 'mse_score': 0.005772215447255543, ]8;id=20480;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=898348;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.005108257755637169, 'model_time': 1.3100137570872903, 'learning_rate':   +  9.996896778944334e-05, 'epoch': 2.22})   +04/15 [22:43:16] INFO  | >> Step 14200, Loss: {'action_dit_loss': 0.05388255417346954, 'mse_score': 0.0039493005190576825, ]8;id=500149;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=6182;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00484220776706934, 'model_time': 1.8931796252727509, 'learning_rate':   +  9.996828209097404e-05, 'epoch': 2.24})   +04/15 [22:47:23] INFO  | >> Step 14300, Loss: {'action_dit_loss': 0.058146193623542786, 'mse_score': 0.006015940436295101, ]8;id=408930;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=894905;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00877903588116169, 'model_time': 1.7264217976480722, 'learning_rate':   +  9.996758890185229e-05, 'epoch': 2.25})   +04/15 [22:51:39] INFO  | >> Step 14400, Loss: {'action_dit_loss': 0.06503891199827194, 'mse_score': 0.005386993821178164, ]8;id=564365;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=783826;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002534538507461548, 'model_time': 1.3255519941449165, 'learning_rate':   +  9.996688822218635e-05, 'epoch': 2.27})   +04/15 [22:55:46] INFO  | >> Step 14500, Loss: {'action_dit_loss': 0.051888782531023026, 'mse_score': 0.0049726249916212896, ]8;id=941423;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=231251;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0046281274408102036, 'model_time': 1.9514033133164048, 'learning_rate':   +  9.99661800520856e-05, 'epoch': 2.29})   +04/15 [22:59:53] INFO  | >> Step 14600, Loss: {'action_dit_loss': 0.06472184509038925, 'mse_score': 0.006659964897802898, ]8;id=509232;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=30434;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004383879713714123, 'model_time': 1.6954451566562057, 'learning_rate':   +  9.996546439166065e-05, 'epoch': 2.3})   +04/15 [23:04:09] INFO  | >> Step 14700, Loss: {'action_dit_loss': 0.037710659205913544, 'mse_score': 0.004483513534069061, ]8;id=836912;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=423956;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008216267451643944, 'model_time': 1.3437912482768297, 'learning_rate':   +  9.996474124102324e-05, 'epoch': 2.32})   +04/15 [23:08:16] INFO  | >> Step 14800, Loss: {'action_dit_loss': 0.08659067749977112, 'mse_score': 0.004775955208710262, ]8;id=964209;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=133827;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.000481409952044487, 'model_time': 1.9590901108458638, 'learning_rate':   +  9.996401060028632e-05, 'epoch': 2.33})   +04/15 [23:12:23] INFO  | >> Step 14900, Loss: {'action_dit_loss': 0.08526217192411423, 'mse_score': 0.0034421120903321673, ]8;id=413160;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=620644;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004898552782833576, 'model_time': 1.6977477902546525, 'learning_rate':   +  9.996327246956398e-05, 'epoch': 2.35})   +04/15 [23:16:39] INFO  | >> Step 15000, Loss: {'action_dit_loss': 0.07754583656787872, 'mse_score': 0.0037329409803662983, ]8;id=673971;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=449433;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0045633576810359955, 'model_time': 1.3212313940748572, 'learning_rate':   +  9.996252684897145e-05, 'epoch': 2.37})   +04/15 [23:20:46] INFO  | >> Step 15100, Loss: {'action_dit_loss': 0.04319339618086815, 'mse_score': 0.0061090146856648585, ]8;id=52727;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=272793;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008307365700602531, 'model_time': 1.9285904113203287, 'learning_rate':   +  9.996177373862521e-05, 'epoch': 2.38})   +04/15 [23:24:54] INFO  | >> Step 15200, Loss: {'action_dit_loss': 0.06252913177013397, 'mse_score': 0.0038328631115811212, ]8;id=342722;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=353894;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003171134740114212, 'model_time': 1.704757697880268, 'learning_rate':   +  9.996101313864284e-05, 'epoch': 2.4})   +04/15 [23:29:09] INFO  | >> Step 15300, Loss: {'action_dit_loss': 0.06316270679235458, 'mse_score': 0.003603254844035421, ]8;id=788539;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=997409;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.005401666276156902, 'model_time': 1.3366986801847816, 'learning_rate':   +  9.996024504914314e-05, 'epoch': 2.41})   +04/15 [23:33:16] INFO  | >> Step 15400, Loss: {'action_dit_loss': 0.03697217255830765, 'mse_score': 0.004274801484176091, ]8;id=85884;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=493152;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004223095253109932, 'model_time': 1.901682185009122, 'learning_rate':   +  9.995946947024603e-05, 'epoch': 2.43})   +04/15 [23:37:21] INFO  | >> Step 15500, Loss: {'action_dit_loss': 0.05888036638498306, 'mse_score': 0.002975240083677428, ]8;id=998160;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=366960;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007781406864523888, 'model_time': 1.6481765322387218, 'learning_rate':   +  9.995868640207263e-05, 'epoch': 2.44})   +04/15 [23:41:24] INFO  | >> Step 15600, Loss: {'action_dit_loss': 0.045386213809251785, 'mse_score': 0.0032680870166846682, ]8;id=683414;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=42213;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003222767263650894, 'model_time': 1.3744217464700341, 'learning_rate':   +  9.99578958447452e-05, 'epoch': 2.46})   +04/15 [23:45:42] INFO  | >> Step 15700, Loss: {'action_dit_loss': 0.045474037528038025, 'mse_score': 0.004049454150455338, ]8;id=209044;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=879995;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004705221392214298, 'model_time': 1.8974235020577908, 'learning_rate':   +  9.995709779838723e-05, 'epoch': 2.48})   +04/15 [23:49:48] INFO  | >> Step 15800, Loss: {'action_dit_loss': 0.04473111778497696, 'mse_score': 0.004909388188804899, ]8;id=132352;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=496564;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00501092616468668, 'model_time': 1.7476293295621872, 'learning_rate':   +  9.995629226312333e-05, 'epoch': 2.49})   +04/15 [23:53:54] INFO  | >> Step 15900, Loss: {'action_dit_loss': 0.06221310794353485, 'mse_score': 0.0036787079381091253, ]8;id=228552;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=487623;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008965898305177689, 'model_time': 1.3392474511638284, 'learning_rate':   +  9.995547923907929e-05, 'epoch': 2.51})   +04/15 [23:58:11] INFO  | >> Step 16000, Loss: {'action_dit_loss': 0.063383549451828, 'mse_score': 0.0024557049785341534, ]8;id=175939;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=635324;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0006399825215339661, 'model_time': 1.9373237658292055, 'learning_rate':   +  9.995465872638205e-05, 'epoch': 2.52})   +04/16 [00:02:18] INFO  | >> Step 16100, Loss: {'action_dit_loss': 0.05727531015872955, 'mse_score': 0.004762009850570134, ]8;id=815573;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=859099;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004820048809051514, 'model_time': 1.716595159843564, 'learning_rate':   +  9.995383072515977e-05, 'epoch': 2.54})   +04/16 [00:06:24] INFO  | >> Step 16200, Loss: {'action_dit_loss': 0.06600234657526016, 'mse_score': 0.005315515611852918, ]8;id=26925;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=974008;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00445061270147562, 'model_time': 1.3858104087412357, 'learning_rate':   +  9.995299523554172e-05, 'epoch': 2.55})   +04/16 [00:10:41] INFO  | >> Step 16300, Loss: {'action_dit_loss': 0.052712228149175644, 'mse_score': 0.005356444844177791, ]8;id=393537;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=415922;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007328111678361893, 'model_time': 1.895527085289359, 'learning_rate':   +  9.99521522576584e-05, 'epoch': 2.57})   +04/16 [00:14:48] INFO  | >> Step 16400, Loss: {'action_dit_loss': 0.0488034151494503, 'mse_score': 0.0035437201814992087, ]8;id=620859;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=724161;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00030050985515117645, 'model_time': 1.73447195161134, 'learning_rate':   +  9.995130179164143e-05, 'epoch': 2.59})   +04/16 [00:18:54] INFO  | >> Step 16500, Loss: {'action_dit_loss': 0.0611678808927536, 'mse_score': 0.004612031259707042, ]8;id=731059;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=810004;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004275010898709297, 'model_time': 1.3436520993709564, 'learning_rate':   +  9.995044383762363e-05, 'epoch': 2.6})   +04/16 [00:23:12] INFO  | >> Step 16600, Loss: {'action_dit_loss': 0.0559319332242012, 'mse_score': 0.006792052515915462, ]8;id=844657;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=126935;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.005130033940076828, 'model_time': 1.9378908164799213, 'learning_rate':   +  9.994957839573895e-05, 'epoch': 2.62})   +04/16 [00:27:18] INFO  | >> Step 16700, Loss: {'action_dit_loss': 0.045790139585733414, 'mse_score': 0.003378897107073239, ]8;id=364069;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=558623;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008388076908886433, 'model_time': 1.7148792268708348, 'learning_rate':   +  9.994870546612256e-05, 'epoch': 2.63})   +04/16 [00:31:24] INFO  | >> Step 16800, Loss: {'action_dit_loss': 0.044171370565891266, 'mse_score': 0.003930819087794849, ]8;id=530538;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=678998;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00037507619708776474, 'model_time': 1.3214895334094763, 'learning_rate':   +  9.994782504891077e-05, 'epoch': 2.65})   +04/16 [00:35:41] INFO  | >> Step 16900, Loss: {'action_dit_loss': 0.04164954274892807, 'mse_score': 0.0027536912156002863, ]8;id=862276;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=514013;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.005517623387277126, 'model_time': 1.9366605896502733, 'learning_rate':   +  9.994693714424106e-05, 'epoch': 2.66})   +04/16 [00:39:48] INFO  | >> Step 17000, Loss: {'action_dit_loss': 0.06372895836830139, 'mse_score': 0.004783535110098975, ]8;id=934884;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=868962;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0038340305909514427, 'model_time': 1.7967745764181018, 'learning_rate':   +  9.99460417522521e-05, 'epoch': 2.68})   +04/16 [00:43:54] INFO  | >> Step 17100, Loss: {'action_dit_loss': 0.04503713548183441, 'mse_score': 0.003974520468286106, ]8;id=184692;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=769440;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008356448262929916, 'model_time': 1.3253671135753393, 'learning_rate':   +  9.994513887308369e-05, 'epoch': 2.7})   +04/16 [00:48:11] INFO  | >> Step 17200, Loss: {'action_dit_loss': 0.046719592064619064, 'mse_score': 0.003759071496980531, ]8;id=847458;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=964289;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003868592903017998, 'model_time': 1.9136728420853615, 'learning_rate':   +  9.994422850687684e-05, 'epoch': 2.71})   +04/16 [00:52:18] INFO  | >> Step 17300, Loss: {'action_dit_loss': 0.04115738347172737, 'mse_score': 0.003454438809837614, ]8;id=456732;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=865845;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004825231619179249, 'model_time': 1.7464014748111367, 'learning_rate':   +  9.994331065377369e-05, 'epoch': 2.73})   +04/16 [00:56:24] INFO  | >> Step 17400, Loss: {'action_dit_loss': 0.04108991101384163, 'mse_score': 0.004220887752515929, ]8;id=893085;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=257420;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0048848288133740425, 'model_time': 1.36506331525743, 'learning_rate':   +  9.99423853139176e-05, 'epoch': 2.74})   +04/16 [01:00:41] INFO  | >> Step 17500, Loss: {'action_dit_loss': 0.06407269090414047, 'mse_score': 0.005023332046610969, ]8;id=924457;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=472700;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008497512899339199, 'model_time': 1.9910330884158611, 'learning_rate':   +  9.994145248745304e-05, 'epoch': 2.76})   +04/16 [01:04:48] INFO  | >> Step 17600, Loss: {'action_dit_loss': 0.037597641348838806, 'mse_score': 0.004034727279629026, ]8;id=639979;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=700646;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002666981890797615, 'model_time': 1.7662430861964822, 'learning_rate':   +  9.99405121745257e-05, 'epoch': 2.78})   +04/16 [01:08:54] INFO  | >> Step 17700, Loss: {'action_dit_loss': 0.05247821286320686, 'mse_score': 0.0045434827251093724, ]8;id=892288;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=340802;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0045943185687065125, 'model_time': 1.3077790504321456, 'learning_rate':   +  9.99395643752824e-05, 'epoch': 2.79})   +04/16 [01:13:11] INFO  | >> Step 17800, Loss: {'action_dit_loss': 0.06323648989200592, 'mse_score': 0.00395279989710876, ]8;id=836587;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=270902;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004739766009151936, 'model_time': 1.8987618014216423, 'learning_rate':   +  9.993860908987118e-05, 'epoch': 2.81})   +04/16 [01:17:18] INFO  | >> Step 17900, Loss: {'action_dit_loss': 0.03614657372236252, 'mse_score': 0.005572475492954254, ]8;id=735244;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=922859;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007719793356955051, 'model_time': 1.769849923439324, 'learning_rate':   +  9.993764631844118e-05, 'epoch': 2.82})   +04/16 [01:21:25] INFO  | >> Step 18000, Loss: {'action_dit_loss': 0.048484012484550476, 'mse_score': 0.005478855222463608, ]8;id=994115;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=200337;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.000352274626493454, 'model_time': 1.3458272609859705, 'learning_rate':   +  9.993667606114276e-05, 'epoch': 2.84})   +04/16 [01:25:41] INFO  | >> Step 18100, Loss: {'action_dit_loss': 0.049083925783634186, 'mse_score': 0.0036744988922561917, ]8;id=512311;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=582144;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004575465805828571, 'model_time': 1.9018379729241133, 'learning_rate':   +  9.993569831812743e-05, 'epoch': 2.85})   +04/16 [01:29:48] INFO  | >> Step 18200, Loss: {'action_dit_loss': 0.03906777501106262, 'mse_score': 0.0038353425583669116, ]8;id=677278;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=746420;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0053370557725429535, 'model_time': 1.7684133751317859, 'learning_rate':   +  9.993471308954788e-05, 'epoch': 2.87})   +04/16 [01:33:54] INFO  | >> Step 18300, Loss: {'action_dit_loss': 0.04371453449130058, 'mse_score': 0.004964047776801246, ]8;id=97573;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=308528;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.010079087689518929, 'model_time': 1.2979246657341719, 'learning_rate':   +  9.993372037555795e-05, 'epoch': 2.89})   +04/16 [01:38:11] INFO  | >> Step 18400, Loss: {'action_dit_loss': 0.07025653123855591, 'mse_score': 0.004447179447327342, ]8;id=321080;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=696212;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00028075091540813446, 'model_time': 1.8782381024211645, 'learning_rate':   +  9.993272017631267e-05, 'epoch': 2.9})   +04/16 [01:42:17] INFO  | >> Step 18500, Loss: {'action_dit_loss': 0.03920922800898552, 'mse_score': 0.004513242415019444, ]8;id=556711;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=360455;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.005765927955508232, 'model_time': 1.7064228290691972, 'learning_rate':   +  9.993171249196822e-05, 'epoch': 2.92})   +04/16 [01:46:24] INFO  | >> Step 18600, Loss: {'action_dit_loss': 0.06027091294527054, 'mse_score': 0.0029834391815321787, ]8;id=368900;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=736996;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004494006745517254, 'model_time': 1.3402710193768144, 'learning_rate':   +  9.993069732268199e-05, 'epoch': 2.93})   +04/16 [01:50:41] INFO  | >> Step 18700, Loss: {'action_dit_loss': 0.041284751147031784, 'mse_score': 0.005163524299860001, ]8;id=241736;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=126516;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.010483468882739544, 'model_time': 1.9007743345573545, 'learning_rate':   +  9.992967466861247e-05, 'epoch': 2.95})   +04/16 [01:54:47] INFO  | >> Step 18800, Loss: {'action_dit_loss': 0.057114604860544205, 'mse_score': 0.004145634493657521, ]8;id=778967;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=561894;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002606930211186409, 'model_time': 1.763287221081555, 'learning_rate':   +  9.992864452991935e-05, 'epoch': 2.96})   +04/16 [01:58:55] INFO  | >> Step 18900, Loss: {'action_dit_loss': 0.06119575351476669, 'mse_score': 0.0026195996573993136, ]8;id=200845;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=226895;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.010421764105558395, 'model_time': 1.3865653229877353, 'learning_rate':   +  9.992760690676354e-05, 'epoch': 2.98})   +04/16 [02:03:11] INFO  | >> Step 19000, Loss: {'action_dit_loss': 0.03303610160946846, 'mse_score': 0.0031691789627075195, ]8;id=618226;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=797135;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0005910852923989296, 'model_time': 1.8985252119600773, 'learning_rate':   +  9.992656179930702e-05, 'epoch': 3.0})   +04/16 [02:07:18] INFO  | >> Step 19100, Loss: {'action_dit_loss': 0.042304448783397675, 'mse_score': 0.005052897014788219, ]8;id=873074;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=203547;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008623799309134483, 'model_time': 1.703690703958273, 'learning_rate':   +  9.992550920771304e-05, 'epoch': 3.01})   +04/16 [02:11:25] INFO  | >> Step 19200, Loss: {'action_dit_loss': 0.058706872165203094, 'mse_score': 0.0037520541144268854, ]8;id=316950;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=14835;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003669150173664093, 'model_time': 1.3923189910128713, 'learning_rate':   +  9.992444913214594e-05, 'epoch': 3.03})   +04/16 [02:15:41] INFO  | >> Step 19300, Loss: {'action_dit_loss': 0.03814714774489403, 'mse_score': 0.002936754109604018, ]8;id=47726;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=57174;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00843597762286663, 'model_time': 2.0743141677230597, 'learning_rate':   +  9.992338157277128e-05, 'epoch': 3.04})   +04/16 [02:19:48] INFO  | >> Step 19400, Loss: {'action_dit_loss': 0.052568890154361725, 'mse_score': 0.0020333327619092806, ]8;id=132413;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=668854;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00037591904401779175, 'model_time': 1.7232964616268873, 'learning_rate':   +  9.992230652975574e-05, 'epoch': 3.06})   +04/16 [02:23:54] INFO  | >> Step 19500, Loss: {'action_dit_loss': 0.0377204604446888, 'mse_score': 0.0036220702209642957, ]8;id=915112;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=12861;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008880184032022953, 'model_time': 1.3273570984601974, 'learning_rate':   +  9.992122400326725e-05, 'epoch': 3.07})   +04/16 [02:28:08] INFO  | >> Step 19600, Loss: {'action_dit_loss': 0.038346193730831146, 'mse_score': 0.007629143340247018, ]8;id=461865;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=357256;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002974672242999077, 'model_time': 8.238163375295699, 'learning_rate':   +  9.992013399347481e-05, 'epoch': 3.09})   +04/16 [02:32:13] INFO  | >> Step 19700, Loss: {'action_dit_loss': 0.05187291279435158, 'mse_score': 0.004250970269952502, ]8;id=903582;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=500935;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008588152006268501, 'model_time': 1.653177854605019, 'learning_rate':   +  9.991903650054864e-05, 'epoch': 3.11})   +04/16 [02:36:19] INFO  | >> Step 19800, Loss: {'action_dit_loss': 0.05248711258172989, 'mse_score': 0.0028860409344945636, ]8;id=515633;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=77680;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00034150388091802597, 'model_time': 1.3308545984327793, 'learning_rate':   +  9.991793152466011e-05, 'epoch': 3.12})   +04/16 [02:40:33] INFO  | >> Step 19900, Loss: {'action_dit_loss': 0.04645099863409996, 'mse_score': 0.006918802325214658, ]8;id=159097;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=156445;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.011350861750543118, 'model_time': 8.789555218070745, 'learning_rate':   +  9.991681906598181e-05, 'epoch': 3.14})   +04/16 [02:44:43] INFO  | >> Step 20000, Loss: {'action_dit_loss': 0.032745521515607834, 'mse_score': 0.005644813179969788, ]8;id=89318;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=260247;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0005529094487428665, 'model_time': 1.7133816806599498, 'learning_rate':   +  9.991569912468744e-05, 'epoch': 3.15})   +✅ Checkpoint saved at ./results/Checkpoints/0415_libero4in1_WanOFT/checkpoints/steps_20000 +04/16 [02:45:22] INFO  | >> 📊 Saving accessed configuration... ]8;id=635770;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=625084;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#238\238]8;;\ +  INFO  | >> 📦 Saving full merged configuration to ]8;id=547957;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=398855;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#242\242]8;;\ +  `results/Checkpoints/0415_libero4in1_WanOFT/config.full.yaml`...   +  INFO  | >> ✅ Configuration files saved ]8;id=901950;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=617113;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#244\244]8;;\ +04/16 [02:49:39] INFO  | >> Step 20100, Loss: {'action_dit_loss': 0.04751437529921532, 'mse_score': 0.00418051119361605, ]8;id=63156;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=639244;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008535660803318024, 'model_time': 1.2915872633457184, 'learning_rate':   +  9.991457170095187e-05, 'epoch': 3.17})   +04/16 [02:53:46] INFO  | >> Step 20200, Loss: {'action_dit_loss': 0.053202975541353226, 'mse_score': 0.004216525969760758, ]8;id=217881;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=655900;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002814019098877907, 'model_time': 1.9137523006647825, 'learning_rate':   +  9.99134367949512e-05, 'epoch': 3.19})   +04/16 [02:57:53] INFO  | >> Step 20300, Loss: {'action_dit_loss': 0.049719832837581635, 'mse_score': 0.003309055364557675, ]8;id=164686;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=251516;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00822385959327221, 'model_time': 1.6544316597282887, 'learning_rate':   +  9.99122944068626e-05, 'epoch': 3.2})   +04/16 [03:02:09] INFO  | >> Step 20400, Loss: {'action_dit_loss': 0.0440654531121254, 'mse_score': 0.004140514348234449, ]8;id=2805;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=428361;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00032398663461208344, 'model_time': 1.3370811380445957, 'learning_rate':   +  9.991114453686452e-05, 'epoch': 3.22})   +04/16 [03:06:16] INFO  | >> Step 20500, Loss: {'action_dit_loss': 0.05860191956162453, 'mse_score': 0.0039863695523568565, ]8;id=305407;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=34225;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007982831448316574, 'model_time': 1.929307585582137, 'learning_rate':   +  9.990998718513649e-05, 'epoch': 3.23})   +04/16 [03:10:23] INFO  | >> Step 20600, Loss: {'action_dit_loss': 0.04386081174015999, 'mse_score': 0.0031728047345365796, ]8;id=737135;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=901362;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0005273083224892616, 'model_time': 1.7183681325986981, 'learning_rate':   +  9.990882235185925e-05, 'epoch': 3.25})   +04/16 [03:14:39] INFO  | >> Step 20700, Loss: {'action_dit_loss': 0.06028345972299576, 'mse_score': 0.0027891466660158975, ]8;id=968790;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=277405;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008908483199775219, 'model_time': 1.3093164088204503, 'learning_rate':   +  9.990765003721468e-05, 'epoch': 3.26})   +04/16 [03:18:46] INFO  | >> Step 20800, Loss: {'action_dit_loss': 0.05321889370679855, 'mse_score': 0.0033309480973652433, ]8;id=693300;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=842956;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003382749855518341, 'model_time': 1.872930260375142, 'learning_rate':   +  9.990647024138586e-05, 'epoch': 3.28})   +04/16 [03:22:53] INFO  | >> Step 20900, Loss: {'action_dit_loss': 0.03300672024488449, 'mse_score': 0.005280716078622001, ]8;id=571015;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=235729;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009768129326403141, 'model_time': 1.693877698853612, 'learning_rate':   +  9.990528296455703e-05, 'epoch': 3.3})   +04/16 [03:27:09] INFO  | >> Step 21000, Loss: {'action_dit_loss': 0.02666315995156765, 'mse_score': 0.004136976652911731, ]8;id=866785;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=149145;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0006001442670822144, 'model_time': 1.3325972482562065, 'learning_rate':   +  9.99040882069136e-05, 'epoch': 3.31})   +04/16 [03:31:16] INFO  | >> Step 21100, Loss: {'action_dit_loss': 0.03304048255085945, 'mse_score': 0.0027273246752364294, ]8;id=322554;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=623948;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00931419339030981, 'model_time': 1.9278451334685087, 'learning_rate':   +  9.990288596864213e-05, 'epoch': 3.33})   +04/16 [03:35:23] INFO  | >> Step 21200, Loss: {'action_dit_loss': 0.0446833111345768, 'mse_score': 0.006853770464658737, ]8;id=302630;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=460485;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0005111889913678169, 'model_time': 1.6716285049915314, 'learning_rate':   +  9.990167624993034e-05, 'epoch': 3.34})   +04/16 [03:39:39] INFO  | >> Step 21300, Loss: {'action_dit_loss': 0.04689595848321915, 'mse_score': 0.0025526519332613263, ]8;id=733723;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=422060;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007976634427905083, 'model_time': 1.438157545402646, 'learning_rate':   +  9.990045905096719e-05, 'epoch': 3.36})   +04/16 [03:43:46] INFO  | >> Step 21400, Loss: {'action_dit_loss': 0.03533320128917694, 'mse_score': 0.003476290830544063, ]8;id=517781;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=459023;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0006820661947131157, 'model_time': 1.9842581022530794, 'learning_rate':   +  9.98992343719427e-05, 'epoch': 3.37})   +04/16 [03:47:53] INFO  | >> Step 21500, Loss: {'action_dit_loss': 0.04355282709002495, 'mse_score': 0.00258232732968671, ]8;id=453014;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=770214;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00880582444369793, 'model_time': 1.6885591251775622, 'learning_rate':   +  9.989800221304814e-05, 'epoch': 3.39})   +04/16 [03:52:09] INFO  | >> Step 21600, Loss: {'action_dit_loss': 0.03380218893289566, 'mse_score': 0.004048439541033336, ]8;id=95763;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=240044;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0005807364359498024, 'model_time': 1.3326361626386642, 'learning_rate':   +  9.989676257447593e-05, 'epoch': 3.41})   +04/16 [03:56:16] INFO  | >> Step 21700, Loss: {'action_dit_loss': 0.0304435882717371, 'mse_score': 0.0019067625648209027, ]8;id=615643;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=996971;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008309613913297653, 'model_time': 1.9666520645841956, 'learning_rate':   +  9.989551545641963e-05, 'epoch': 3.42})   +04/16 [04:00:24] INFO  | >> Step 21800, Loss: {'action_dit_loss': 0.025216972455382347, 'mse_score': 0.00414333598954337, ]8;id=282602;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=604238;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002984916791319847, 'model_time': 1.811157344840467, 'learning_rate':   +  9.989426085907402e-05, 'epoch': 3.44})   +04/16 [04:04:38] INFO  | >> Step 21900, Loss: {'action_dit_loss': 0.04723336920142174, 'mse_score': 0.0033409816345998217, ]8;id=493355;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=544173;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009166370145976543, 'model_time': 1.3488905280828476, 'learning_rate':   +  9.989299878263497e-05, 'epoch': 3.45})   +04/16 [04:08:46] INFO  | >> Step 22000, Loss: {'action_dit_loss': 0.03516102209687233, 'mse_score': 0.003267445202384676, ]8;id=190305;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=613762;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003967089578509331, 'model_time': 1.9295150702819228, 'learning_rate':   +  9.98917292272996e-05, 'epoch': 3.47})   +04/16 [04:12:53] INFO  | >> Step 22100, Loss: {'action_dit_loss': 0.04133693128824234, 'mse_score': 0.0025240877377135412, ]8;id=95674;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=492841;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007995836436748505, 'model_time': 1.6771124806255102, 'learning_rate':   +  9.989045219326614e-05, 'epoch': 3.48})   +04/16 [04:17:09] INFO  | >> Step 22200, Loss: {'action_dit_loss': 0.035147830843925476, 'mse_score': 0.0029674936085939407, ]8;id=702685;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=109680;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00035627372562885284, 'model_time': 1.313239449635148, 'learning_rate':   +  9.988916768073402e-05, 'epoch': 3.5})   +04/16 [04:21:16] INFO  | >> Step 22300, Loss: {'action_dit_loss': 0.03378019854426384, 'mse_score': 0.003030675064240183, ]8;id=727369;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=519536;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008282636292278767, 'model_time': 1.9179779756814241, 'learning_rate':   +  9.988787568990384e-05, 'epoch': 3.52})   +04/16 [04:25:23] INFO  | >> Step 22400, Loss: {'action_dit_loss': 0.04112013801932335, 'mse_score': 0.005419061652251652, ]8;id=853085;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=797441;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0004936093464493752, 'model_time': 1.7108996417373419, 'learning_rate':   +  9.988657622097733e-05, 'epoch': 3.53})   +04/16 [04:29:39] INFO  | >> Step 22500, Loss: {'action_dit_loss': 0.05832589790225029, 'mse_score': 0.0031250856284584317, ]8;id=329795;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=264659;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00816766545176506, 'model_time': 1.310750431381166, 'learning_rate':   +  9.988526927415743e-05, 'epoch': 3.55})   +04/16 [04:33:46] INFO  | >> Step 22600, Loss: {'action_dit_loss': 0.04980752244591713, 'mse_score': 0.004055817744561604, ]8;id=906924;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=539593;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00032706744968891144, 'model_time': 1.904097093269229, 'learning_rate':   +  9.988395484964822e-05, 'epoch': 3.56})   +04/16 [04:37:53] INFO  | >> Step 22700, Loss: {'action_dit_loss': 0.05014527961611748, 'mse_score': 0.003899572417140007, ]8;id=568950;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=484417;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009483824484050274, 'model_time': 1.6781616797670722, 'learning_rate':   +  9.988263294765499e-05, 'epoch': 3.58})   +04/16 [04:42:09] INFO  | >> Step 22800, Loss: {'action_dit_loss': 0.033831216394901276, 'mse_score': 0.002640607367668833, ]8;id=379353;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=652878;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0006513511762022972, 'model_time': 1.2966191321611404, 'learning_rate':   +  9.98813035683841e-05, 'epoch': 3.6})   +04/16 [04:46:16] INFO  | >> Step 22900, Loss: {'action_dit_loss': 0.04424036666750908, 'mse_score': 0.0027063938656023572, ]8;id=796907;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=54118;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009490796364843845, 'model_time': 1.903798932209611, 'learning_rate':   +  9.987996671204322e-05, 'epoch': 3.61})   +04/16 [04:50:23] INFO  | >> Step 23000, Loss: {'action_dit_loss': 0.0420965813100338, 'mse_score': 0.0030295997858047485, ]8;id=972735;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=302020;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.000328725203871727, 'model_time': 1.6816410971805453, 'learning_rate':   +  9.987862237884106e-05, 'epoch': 3.63})   +04/16 [04:54:39] INFO  | >> Step 23100, Loss: {'action_dit_loss': 0.04404076561331749, 'mse_score': 0.0019548600539565086, ]8;id=127324;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=30271;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008724945597350597, 'model_time': 1.4345559664070606, 'learning_rate':   +  9.987727056898756e-05, 'epoch': 3.64})   +04/16 [04:58:47] INFO  | >> Step 23200, Loss: {'action_dit_loss': 0.02815992571413517, 'mse_score': 0.004128429240414074, ]8;id=744261;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=166071;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00034702662378549576, 'model_time': 1.971874663606286, 'learning_rate':   +  9.987591128269384e-05, 'epoch': 3.66})   +04/16 [05:02:53] INFO  | >> Step 23300, Loss: {'action_dit_loss': 0.03649543598294258, 'mse_score': 0.002898011090500014, ]8;id=427809;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=97736;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007448006421327591, 'model_time': 1.6918668458238244, 'learning_rate':   +  9.987454452017212e-05, 'epoch': 3.67})   +04/16 [05:07:09] INFO  | >> Step 23400, Loss: {'action_dit_loss': 0.05018904432654381, 'mse_score': 0.004238483096872058, ]8;id=483863;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=993065;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0008389679715037346, 'model_time': 1.3699088282883167, 'learning_rate':   +  9.987317028163589e-05, 'epoch': 3.69})   +04/16 [05:11:16] INFO  | >> Step 23500, Loss: {'action_dit_loss': 0.05119992420077324, 'mse_score': 0.005048085004091263, ]8;id=522584;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=977957;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009201048873364925, 'model_time': 1.873431995511055, 'learning_rate':   +  9.987178856729968e-05, 'epoch': 3.71})   +04/16 [05:15:23] INFO  | >> Step 23600, Loss: {'action_dit_loss': 0.039845965802669525, 'mse_score': 0.004886233380862645, ]8;id=286706;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=435673;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0006457353010773659, 'model_time': 1.7362645901739597, 'learning_rate':   +  9.98703993773793e-05, 'epoch': 3.72})   +04/16 [05:19:39] INFO  | >> Step 23700, Loss: {'action_dit_loss': 0.04359668865799904, 'mse_score': 0.003349381632038525, ]8;id=478975;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=578043;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007761194370687008, 'model_time': 1.3115211930125952, 'learning_rate':   +  9.98690027120917e-05, 'epoch': 3.74})   +04/16 [05:23:46] INFO  | >> Step 23800, Loss: {'action_dit_loss': 0.027623003348708153, 'mse_score': 0.006009039069925036, ]8;id=628492;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=532929;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00032482296228408813, 'model_time': 1.925629054196179, 'learning_rate':   +  9.986759857165494e-05, 'epoch': 3.75})   +04/16 [05:27:53] INFO  | >> Step 23900, Loss: {'action_dit_loss': 0.0342198982834816, 'mse_score': 0.005638788853372846, ]8;id=73201;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=289666;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008681450970470905, 'model_time': 1.6995546212419868, 'learning_rate':   +  9.986618695628832e-05, 'epoch': 3.77})   +04/16 [05:32:09] INFO  | >> Step 24000, Loss: {'action_dit_loss': 0.04966442659497261, 'mse_score': 0.0037259946444204877, ]8;id=356385;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=979630;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003519020974636078, 'model_time': 1.3405396714806557, 'learning_rate':   +  9.986476786621226e-05, 'epoch': 3.78})   +04/16 [05:36:16] INFO  | >> Step 24100, Loss: {'action_dit_loss': 0.037875931710004807, 'mse_score': 0.002190937687243734, ]8;id=2689;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=296578;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008281754329800606, 'model_time': 1.9228490460664034, 'learning_rate':   +  9.986334130164834e-05, 'epoch': 3.8})   +04/16 [05:40:23] INFO  | >> Step 24200, Loss: {'action_dit_loss': 0.03623028099536896, 'mse_score': 0.00659641410623278, ]8;id=608093;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=691998;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0004635350778698921, 'model_time': 1.6978817582130432, 'learning_rate':   +  9.986190726281938e-05, 'epoch': 3.82})   +04/16 [05:44:39] INFO  | >> Step 24300, Loss: {'action_dit_loss': 0.02790299616754055, 'mse_score': 0.0027024136590106146, ]8;id=564742;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=507868;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009462029673159122, 'model_time': 1.4850822258740664, 'learning_rate':   +  9.986046574994928e-05, 'epoch': 3.83})   +04/16 [05:48:46] INFO  | >> Step 24400, Loss: {'action_dit_loss': 0.04177885875105858, 'mse_score': 0.00518881157040596, ]8;id=569827;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=395533;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00033970270305871964, 'model_time': 1.863233296200633, 'learning_rate':   +  9.985901676326316e-05, 'epoch': 3.85})   +04/16 [05:52:53] INFO  | >> Step 24500, Loss: {'action_dit_loss': 0.03927002102136612, 'mse_score': 0.0023426746151276995, ]8;id=197816;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=731380;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0077303387224674225, 'model_time': 1.688625312410295, 'learning_rate':   +  9.985756030298728e-05, 'epoch': 3.86})   +04/16 [05:57:09] INFO  | >> Step 24600, Loss: {'action_dit_loss': 0.039621591567993164, 'mse_score': 0.003999405141387667, ]8;id=897594;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=813217;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0007501291111111641, 'model_time': 1.3144311113283038, 'learning_rate':   +  9.985609636934908e-05, 'epoch': 3.88})   +04/16 [06:01:17] INFO  | >> Step 24700, Loss: {'action_dit_loss': 0.039023030549287796, 'mse_score': 0.002623289025255612, ]8;id=495951;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=739485;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.010324430651962757, 'model_time': 1.89706199336797, 'learning_rate':   +  9.985462496257718e-05, 'epoch': 3.89})   +04/16 [06:05:23] INFO  | >> Step 24800, Loss: {'action_dit_loss': 0.040374673902988434, 'mse_score': 0.0025430156716278623, ]8;id=695928;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=830884;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0006059417501091957, 'model_time': 1.750355121679604, 'learning_rate':   +  9.985314608290134e-05, 'epoch': 3.91})   +04/16 [06:09:39] INFO  | >> Step 24900, Loss: {'action_dit_loss': 0.03890594467520714, 'mse_score': 0.002404778131416866, ]8;id=38817;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=132378;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.010004070587456226, 'model_time': 1.410514472052455, 'learning_rate':   +  9.985165973055251e-05, 'epoch': 3.93})   +04/16 [06:13:46] INFO  | >> Step 25000, Loss: {'action_dit_loss': 0.03622298315167427, 'mse_score': 0.005944680954728808, ]8;id=105239;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=916655;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0004929453134536743, 'model_time': 2.01555678807199, 'learning_rate':   +  9.98501659057628e-05, 'epoch': 3.94})   +04/16 [06:17:53] INFO  | >> Step 25100, Loss: {'action_dit_loss': 0.04497670754790306, 'mse_score': 0.0037909397589308874, ]8;id=954667;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=479123;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00807934906333685, 'model_time': 1.6876722173765302, 'learning_rate':   +  9.984866460876547e-05, 'epoch': 3.96})   +04/16 [06:22:09] INFO  | >> Step 25200, Loss: {'action_dit_loss': 0.043735820800065994, 'mse_score': 0.004949206752436501, ]8;id=913239;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=686587;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004437933675944805, 'model_time': 1.3155374489724636, 'learning_rate':   +  9.984715583979496e-05, 'epoch': 3.97})   +04/16 [06:26:16] INFO  | >> Step 25300, Loss: {'action_dit_loss': 0.037314463406801224, 'mse_score': 0.002427533535020692, ]8;id=277896;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=355007;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008646884001791477, 'model_time': 1.9415143076330423, 'learning_rate':   +  9.984563959908686e-05, 'epoch': 3.99})   +04/16 [06:30:24] INFO  | >> Step 25400, Loss: {'action_dit_loss': 0.045926909893751144, 'mse_score': 0.004666271486452648, ]8;id=84216;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=893140;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0005854172632098198, 'model_time': 1.7619877206161618, 'learning_rate':   +  9.9844115886878e-05, 'epoch': 4.01})   +04/16 [06:34:39] INFO  | >> Step 25500, Loss: {'action_dit_loss': 0.028692202642560005, 'mse_score': 0.0033811607531138827, ]8;id=559543;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=398468;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004870777949690819, 'model_time': 1.319100994616747, 'learning_rate':   +  9.984258470340627e-05, 'epoch': 4.02})   +04/16 [06:38:46] INFO  | >> Step 25600, Loss: {'action_dit_loss': 0.052643533796072006, 'mse_score': 0.003536633348890713, ]8;id=796290;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=511650;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00455472432076931, 'model_time': 1.9638150176033378, 'learning_rate':   +  9.984104604891079e-05, 'epoch': 4.04})   +04/16 [06:42:53] INFO  | >> Step 25700, Loss: {'action_dit_loss': 0.04495704919099808, 'mse_score': 0.0020042462274432182, ]8;id=71744;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=246174;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008100944571197033, 'model_time': 1.722605088725686, 'learning_rate':   +  9.983949992363183e-05, 'epoch': 4.05})   +04/16 [06:47:09] INFO  | >> Step 25800, Loss: {'action_dit_loss': 0.03799564763903618, 'mse_score': 0.0042601751961878365, ]8;id=238536;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=783041;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002558855339884758, 'model_time': 1.346195180900395, 'learning_rate':   +  9.983794632781085e-05, 'epoch': 4.07})   +04/16 [06:51:16] INFO  | >> Step 25900, Loss: {'action_dit_loss': 0.03825302794575691, 'mse_score': 0.0024826696940830778, ]8;id=664532;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=738083;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004876105114817619, 'model_time': 1.9309679055586457, 'learning_rate':   +  9.983638526169043e-05, 'epoch': 4.08})   +04/16 [06:55:23] INFO  | >> Step 26000, Loss: {'action_dit_loss': 0.03255271539092064, 'mse_score': 0.003169467406613486, ]8;id=727712;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=314012;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0041014282032847404, 'model_time': 1.686699234880507, 'learning_rate':   +  9.983481672551437e-05, 'epoch': 4.1})   +04/16 [06:59:40] INFO  | >> Step 26100, Loss: {'action_dit_loss': 0.029344329610466957, 'mse_score': 0.0038340254021542414, ]8;id=834816;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=58845;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.010857504792511463, 'model_time': 1.2934002438560128, 'learning_rate':   +  9.98332407195276e-05, 'epoch': 4.12})   +04/16 [07:03:46] INFO  | >> Step 26200, Loss: {'action_dit_loss': 0.03035055473446846, 'mse_score': 0.002912011795810291, ]8;id=152640;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=256059;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003061508759856224, 'model_time': 1.9192858897149563, 'learning_rate':   +  9.983165724397622e-05, 'epoch': 4.13})   +04/16 [07:07:52] INFO  | >> Step 26300, Loss: {'action_dit_loss': 0.02636495791375637, 'mse_score': 0.0024358872324228287, ]8;id=831016;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=188803;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004032580181956291, 'model_time': 1.6878028633072972, 'learning_rate':   +  9.98300662991075e-05, 'epoch': 4.15})   +04/16 [07:12:09] INFO  | >> Step 26400, Loss: {'action_dit_loss': 0.029680650681257248, 'mse_score': 0.0022738794130938394, ]8;id=913141;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=401126;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004868471994996071, 'model_time': 1.3436185512691736, 'learning_rate':   +  9.982846788516988e-05, 'epoch': 4.16})   +04/16 [07:16:16] INFO  | >> Step 26500, Loss: {'action_dit_loss': 0.03839615732431412, 'mse_score': 0.006688780018261501, ]8;id=957170;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=611484;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004461130127310753, 'model_time': 1.8956895805895329, 'learning_rate':   +  9.982686200241299e-05, 'epoch': 4.18})   +04/16 [07:20:23] INFO  | >> Step 26600, Loss: {'action_dit_loss': 0.03831014782190323, 'mse_score': 0.003097240147846086, ]8;id=266314;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=481894;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.000632651150226593, 'model_time': 1.6725432835519314, 'learning_rate':   +  9.98252486510876e-05, 'epoch': 4.19})   +04/16 [07:24:39] INFO  | >> Step 26700, Loss: {'action_dit_loss': 0.04039006680250168, 'mse_score': 0.0028637067547866274, ]8;id=843718;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=487853;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008714824914932251, 'model_time': 1.3409932386130095, 'learning_rate':   +  9.98236278314456e-05, 'epoch': 4.21})   +04/16 [07:28:46] INFO  | >> Step 26800, Loss: {'action_dit_loss': 0.0429236963391304, 'mse_score': 0.002965056470462254, ]8;id=165649;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=77449;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00040597375482320786, 'model_time': 1.9440606189891696, 'learning_rate':   +  9.982199954374014e-05, 'epoch': 4.23})   +04/16 [07:32:53] INFO  | >> Step 26900, Loss: {'action_dit_loss': 0.032513655722141266, 'mse_score': 0.003485502675175667, ]8;id=313685;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=669975;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008048969320952892, 'model_time': 1.6891960343346, 'learning_rate':   +  9.982036378822549e-05, 'epoch': 4.24})   +04/16 [07:37:09] INFO  | >> Step 27000, Loss: {'action_dit_loss': 0.04435854032635689, 'mse_score': 0.002572054841688701, ]8;id=886365;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=316797;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.000607895664870739, 'model_time': 1.3138438165187836, 'learning_rate':   +  9.981872056515706e-05, 'epoch': 4.26})   +04/16 [07:41:16] INFO  | >> Step 27100, Loss: {'action_dit_loss': 0.04283846169710159, 'mse_score': 0.002978772723249027, ]8;id=111834;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=248728;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009378297254443169, 'model_time': 1.9571060379967093, 'learning_rate':   +  9.981706987479148e-05, 'epoch': 4.27})   +04/16 [07:45:24] INFO  | >> Step 27200, Loss: {'action_dit_loss': 0.03873727470636368, 'mse_score': 0.002992316016129085, ]8;id=310244;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=733247;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00037100445479154587, 'model_time': 1.679186474531889, 'learning_rate':   +  9.98154117173865e-05, 'epoch': 4.29})   +04/16 [07:49:39] INFO  | >> Step 27300, Loss: {'action_dit_loss': 0.04185653105378151, 'mse_score': 0.002319873443671635, ]8;id=415032;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=287813;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009645604528486729, 'model_time': 1.4009109325706959, 'learning_rate':   +  9.981374609320108e-05, 'epoch': 4.3})   +04/16 [07:53:46] INFO  | >> Step 27400, Loss: {'action_dit_loss': 0.03220824897289276, 'mse_score': 0.001985777568604265, ]8;id=816118;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=780841;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0006512347608804703, 'model_time': 1.8945459080860019, 'learning_rate':   +  9.981207300249528e-05, 'epoch': 4.32})   +04/16 [07:57:53] INFO  | >> Step 27500, Loss: {'action_dit_loss': 0.03076063096523285, 'mse_score': 0.003516356327704021, ]8;id=520856;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=873294;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00855198409408331, 'model_time': 1.7382980650290847, 'learning_rate':   +  9.981039244553043e-05, 'epoch': 4.34})   +04/16 [08:02:09] INFO  | >> Step 27600, Loss: {'action_dit_loss': 0.037635959684848785, 'mse_score': 0.003832493775657245, ]8;id=837665;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=241296;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003653746098279953, 'model_time': 1.3460895586758852, 'learning_rate':   +  9.980870442256889e-05, 'epoch': 4.35})   +04/16 [08:06:17] INFO  | >> Step 27700, Loss: {'action_dit_loss': 0.03313980996608734, 'mse_score': 0.004036557993718556, ]8;id=667542;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=199367;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008914497680962086, 'model_time': 1.954316089861095, 'learning_rate':   +  9.98070089338743e-05, 'epoch': 4.37})   +04/16 [08:10:23] INFO  | >> Step 27800, Loss: {'action_dit_loss': 0.04917539283633232, 'mse_score': 0.004268338637692588, ]8;id=755948;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=804751;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00030051078647375107, 'model_time': 1.7211540536955, 'learning_rate':   +  9.980530597971143e-05, 'epoch': 4.38})   +04/16 [08:14:39] INFO  | >> Step 27900, Loss: {'action_dit_loss': 0.03171752020716667, 'mse_score': 0.0032142241086278644, ]8;id=658765;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=101883;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009272271767258644, 'model_time': 1.3493193425238132, 'learning_rate':   +  9.98035955603462e-05, 'epoch': 4.4})   +04/16 [08:18:46] INFO  | >> Step 28000, Loss: {'action_dit_loss': 0.027641598135232925, 'mse_score': 0.003108181857636997, ]8;id=323939;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=826918;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00029328279197216034, 'model_time': 1.9868007842451334, 'learning_rate':   +  9.980187767604571e-05, 'epoch': 4.42})   +04/16 [08:22:55] INFO  | >> Step 28100, Loss: {'action_dit_loss': 0.032988958060741425, 'mse_score': 0.0023472503359828678, ]8;id=767934;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=137795;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008852142840623856, 'model_time': 1.7130991742014885, 'learning_rate':   +  9.98001523270782e-05, 'epoch': 4.43})   +04/16 [08:27:09] INFO  | >> Step 28200, Loss: {'action_dit_loss': 0.027124281972646713, 'mse_score': 0.004890189639159611, ]8;id=783790;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=435686;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003429800271987915, 'model_time': 1.318054142408073, 'learning_rate':   +  9.979841951371312e-05, 'epoch': 4.45})   +04/16 [08:31:16] INFO  | >> Step 28300, Loss: {'action_dit_loss': 0.03764447197318077, 'mse_score': 0.002441103703209332, ]8;id=565610;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=919035;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008320722728967667, 'model_time': 1.9166651600971818, 'learning_rate':   +  9.979667923622107e-05, 'epoch': 4.46})   +04/16 [08:35:23] INFO  | >> Step 28400, Loss: {'action_dit_loss': 0.043946437537670135, 'mse_score': 0.00527389081461089, ]8;id=285765;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=870813;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00039834436029195786, 'model_time': 1.691256889142096, 'learning_rate':   +  9.97949314948738e-05, 'epoch': 4.48})   +04/16 [08:39:39] INFO  | >> Step 28500, Loss: {'action_dit_loss': 0.030022183433175087, 'mse_score': 0.0032244008034467697, ]8;id=990052;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=505254;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007778055965900421, 'model_time': 1.4305764436721802, 'learning_rate':   +  9.979317628994423e-05, 'epoch': 4.49})   +04/16 [08:43:47] INFO  | >> Step 28600, Loss: {'action_dit_loss': 0.0313371866941452, 'mse_score': 0.0020146934049470083, ]8;id=355168;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=843298;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0006941072642803192, 'model_time': 1.919343501329422, 'learning_rate':   +  9.979141362170646e-05, 'epoch': 4.51})   +04/16 [08:47:52] INFO  | >> Step 28700, Loss: {'action_dit_loss': 0.035275690257549286, 'mse_score': 0.0032644447471414295, ]8;id=790785;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=236574;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007781140506267548, 'model_time': 1.707798896357417, 'learning_rate':   +  9.978964349043573e-05, 'epoch': 4.53})   +04/16 [08:52:09] INFO  | >> Step 28800, Loss: {'action_dit_loss': 0.03463602438569069, 'mse_score': 0.007598029715674264, ]8;id=416716;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=886827;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00032580457627773285, 'model_time': 1.3427170971408486, 'learning_rate':   +  9.978786589640847e-05, 'epoch': 4.54})   +04/16 [08:56:16] INFO  | >> Step 28900, Loss: {'action_dit_loss': 0.03626903146505356, 'mse_score': 0.0021582034283450673, ]8;id=829090;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=413741;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009968549944460392, 'model_time': 1.9142691930755973, 'learning_rate':   +  9.978608083990227e-05, 'epoch': 4.56})   +04/16 [09:00:23] INFO  | >> Step 29000, Loss: {'action_dit_loss': 0.024268189445137978, 'mse_score': 0.0022506615413086756, ]8;id=476877;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=386490;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.000456295907497406, 'model_time': 1.7319568172097206, 'learning_rate':   +  9.978428832119589e-05, 'epoch': 4.57})   +04/16 [09:04:39] INFO  | >> Step 29100, Loss: {'action_dit_loss': 0.028309719637036324, 'mse_score': 0.00337555179638522, ]8;id=612955;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=399534;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00764089822769165, 'model_time': 1.316219275817275, 'learning_rate':   +  9.978248834056921e-05, 'epoch': 4.59})   +04/16 [09:08:46] INFO  | >> Step 29200, Loss: {'action_dit_loss': 0.027847731485962868, 'mse_score': 0.005522604499544416, ]8;id=113609;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=707617;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003122882917523384, 'model_time': 2.0254655182361603, 'learning_rate':   +  9.978068089830335e-05, 'epoch': 4.6})   +04/16 [09:12:53] INFO  | >> Step 29300, Loss: {'action_dit_loss': 0.05433187633752823, 'mse_score': 0.0033522439854485647, ]8;id=927187;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=988984;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008537141606211662, 'model_time': 1.7297621984034777, 'learning_rate':   +  9.977886599468054e-05, 'epoch': 4.62})   +04/16 [09:17:09] INFO  | >> Step 29400, Loss: {'action_dit_loss': 0.027630295604467392, 'mse_score': 0.0023240715797458377, ]8;id=232120;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=679112;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0006237290799617767, 'model_time': 1.413974093273282, 'learning_rate':   +  9.977704362998422e-05, 'epoch': 4.64})   +04/16 [09:21:16] INFO  | >> Step 29500, Loss: {'action_dit_loss': 0.03985195606946945, 'mse_score': 0.0020632363323654446, ]8;id=953562;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=735132;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008835656568408012, 'model_time': 1.9042351180687547, 'learning_rate':   +  9.977521380449891e-05, 'epoch': 4.65})   +04/16 [09:25:23] INFO  | >> Step 29600, Loss: {'action_dit_loss': 0.034556105732917786, 'mse_score': 0.0033589335424559458, ]8;id=146566;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=47549;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00046146102249622345, 'model_time': 1.6708670426160097, 'learning_rate':   +  9.97733765185104e-05, 'epoch': 4.67})   +04/16 [09:29:39] INFO  | >> Step 29700, Loss: {'action_dit_loss': 0.03475858271121979, 'mse_score': 0.0025166813284158707, ]8;id=121761;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=101913;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00881093367934227, 'model_time': 1.3079970637336373, 'learning_rate':   +  9.97715317723056e-05, 'epoch': 4.68})   +04/16 [09:33:46] INFO  | >> Step 29800, Loss: {'action_dit_loss': 0.024849621579051018, 'mse_score': 0.0024204105138778687, ]8;id=407524;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=475679;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003469809889793396, 'model_time': 1.9150398997589946, 'learning_rate':   +  9.976967956617255e-05, 'epoch': 4.7})   +04/16 [09:37:53] INFO  | >> Step 29900, Loss: {'action_dit_loss': 0.029550353065133095, 'mse_score': 0.0020213365288717406, ]8;id=730316;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=991925;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008151871152222157, 'model_time': 1.7150076227262616, 'learning_rate':   +  9.976781990040051e-05, 'epoch': 4.71})   +04/16 [09:42:09] INFO  | >> Step 30000, Loss: {'action_dit_loss': 0.026540812104940414, 'mse_score': 0.003544576732175691, ]8;id=761894;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=162029;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003676731139421463, 'model_time': 1.3424927704036236, 'learning_rate':   +  9.976595277527989e-05, 'epoch': 4.73})   +✅ Checkpoint saved at ./results/Checkpoints/0415_libero4in1_WanOFT/checkpoints/steps_30000 +04/16 [09:42:49] INFO  | >> 📊 Saving accessed configuration... ]8;id=874190;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=513117;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#238\238]8;;\ +  INFO  | >> 📦 Saving full merged configuration to ]8;id=293328;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=34305;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#242\242]8;;\ +  `results/Checkpoints/0415_libero4in1_WanOFT/config.full.yaml`...   +  INFO  | >> ✅ Configuration files saved ]8;id=466297;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=996729;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#244\244]8;;\ +04/16 [09:47:03] INFO  | >> Step 30100, Loss: {'action_dit_loss': 0.02592356689274311, 'mse_score': 0.002809460141829082, ]8;id=718987;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=385178;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009825016371905804, 'model_time': 8.367541881278157, 'learning_rate':   +  9.976407819110222e-05, 'epoch': 4.75})   +04/16 [09:51:13] INFO  | >> Step 30200, Loss: {'action_dit_loss': 0.025145793333649635, 'mse_score': 0.00156038227890219, ]8;id=63491;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=417479;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004471036605536938, 'model_time': 1.733682249672711, 'learning_rate':   +  9.976219614816028e-05, 'epoch': 4.76})   +04/16 [09:55:20] INFO  | >> Step 30300, Loss: {'action_dit_loss': 0.02345646731555462, 'mse_score': 0.0035619443016392843, ]8;id=889227;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=864226;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004797285422682762, 'model_time': 1.309452936053276, 'learning_rate':   +  9.976030664674793e-05, 'epoch': 4.78})   +04/16 [09:59:33] INFO  | >> Step 30400, Loss: {'action_dit_loss': 0.028402332216501236, 'mse_score': 0.004586532711982727, ]8;id=672875;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=670556;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0005796235054731369, 'model_time': 8.783661772496998, 'learning_rate':   +  9.975840968716026e-05, 'epoch': 4.79})   +04/16 [10:03:43] INFO  | >> Step 30500, Loss: {'action_dit_loss': 0.02733195386826992, 'mse_score': 0.001809298326926572, ]8;id=349709;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=255400;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004630830138921738, 'model_time': 1.8221319299191236, 'learning_rate':   +  9.975650526969347e-05, 'epoch': 4.81})   +04/16 [10:07:49] INFO  | >> Step 30600, Loss: {'action_dit_loss': 0.03179799020290375, 'mse_score': 0.0041085902069296154, ]8;id=71942;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=870127;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007514797151088715, 'model_time': 1.2926789550110698, 'learning_rate':   +  9.975459339464498e-05, 'epoch': 4.82})   +04/16 [10:12:03] INFO  | >> Step 30700, Loss: {'action_dit_loss': 0.03229941800236702, 'mse_score': 0.0036133365439517157, ]8;id=226441;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=852547;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004474207758903503, 'model_time': 8.68863323237747, 'learning_rate':   +  9.975267406231331e-05, 'epoch': 4.84})   +04/16 [10:16:13] INFO  | >> Step 30800, Loss: {'action_dit_loss': 0.029559262096881866, 'mse_score': 0.0033030187977211817, ]8;id=154721;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=826952;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0004020305350422859, 'model_time': 1.682567079551518, 'learning_rate':   +  9.975074727299821e-05, 'epoch': 4.86})   +04/16 [10:20:15] INFO  | >> Step 30900, Loss: {'action_dit_loss': 0.025709394365549088, 'mse_score': 0.002327981005821909, ]8;id=900104;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=151716;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004439575597643852, 'model_time': 1.3339705262333155, 'learning_rate':   +  9.974881302700055e-05, 'epoch': 4.87})   +04/16 [10:24:21] INFO  | >> Step 31000, Loss: {'action_dit_loss': 0.029678747057914734, 'mse_score': 0.0017367260796683176, ]8;id=182973;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=115266;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007507571019232273, 'model_time': 1.9251759955659509, 'learning_rate':   +  9.974687132462239e-05, 'epoch': 4.89})   +04/16 [10:28:38] INFO  | >> Step 31100, Loss: {'action_dit_loss': 0.02905164659023285, 'mse_score': 0.002410160643713815, ]8;id=15582;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=375644;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004510729573667049, 'model_time': 5.26014188863337, 'learning_rate':   +  9.974492216616693e-05, 'epoch': 4.9})   +04/16 [10:32:44] INFO  | >> Step 31200, Loss: {'action_dit_loss': 0.029278090223670006, 'mse_score': 0.0037123611462967737, ]8;id=339498;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=16547;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00028285663574934006, 'model_time': 1.3361176243051887, 'learning_rate':   +  9.974296555193853e-05, 'epoch': 4.92})   +04/16 [10:36:51] INFO  | >> Step 31300, Loss: {'action_dit_loss': 0.03684382140636444, 'mse_score': 0.002497063683612006, ]8;id=777747;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=441409;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.005356660112738609, 'model_time': 1.9543886724859476, 'learning_rate':   +  9.974100148224277e-05, 'epoch': 4.94})   +04/16 [10:41:09] INFO  | >> Step 31400, Loss: {'action_dit_loss': 0.032408662140369415, 'mse_score': 0.005462257457630975, ]8;id=499380;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=470050;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00028385408222675323, 'model_time': 3.3477955469861627, 'learning_rate':   +  9.973902995738635e-05, 'epoch': 4.95})   +04/16 [10:45:15] INFO  | >> Step 31500, Loss: {'action_dit_loss': 0.025016821920871735, 'mse_score': 0.0031516014465263914, ]8;id=114351;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=473962;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.010742071084678173, 'model_time': 1.3980187391862273, 'learning_rate':   +  9.973705097767713e-05, 'epoch': 4.97})   +04/16 [10:49:21] INFO  | >> Step 31600, Loss: {'action_dit_loss': 0.02638351172208786, 'mse_score': 0.004575362695114953, ]8;id=45471;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=762569;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004522665403783321, 'model_time': 1.9714694982394576, 'learning_rate':   +  9.973506454342413e-05, 'epoch': 4.98})   +04/16 [10:53:38] INFO  | >> Step 31700, Loss: {'action_dit_loss': 0.029509803280234337, 'mse_score': 0.0019660802291972296, ]8;id=546781;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=316282;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0044961851090192795, 'model_time': 5.399376432411373, 'learning_rate':   +  9.973307065493758e-05, 'epoch': 5.0})   +04/16 [10:57:44] INFO  | >> Step 31800, Loss: {'action_dit_loss': 0.02833879180252552, 'mse_score': 0.0018184656011206763, ]8;id=502248;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=888456;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002782503142952919, 'model_time': 1.3037606598809361, 'learning_rate':   +  9.973106931252882e-05, 'epoch': 5.01})   +04/16 [11:01:52] INFO  | >> Step 31900, Loss: {'action_dit_loss': 0.030483687296509743, 'mse_score': 0.0023209817175354275, ]8;id=514084;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=747006;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00912410207092762, 'model_time': 1.9551737131550908, 'learning_rate':   +  9.972906051651038e-05, 'epoch': 5.03})   +04/16 [11:06:07] INFO  | >> Step 32000, Loss: {'action_dit_loss': 0.03483956679701805, 'mse_score': 0.005405926810843604, ]8;id=84714;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=337758;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004241785034537315, 'model_time': 5.359069990925491, 'learning_rate':   +  9.972704426719596e-05, 'epoch': 5.05})   +04/16 [11:10:14] INFO  | >> Step 32100, Loss: {'action_dit_loss': 0.02985434979200363, 'mse_score': 0.0047219448855945045, ]8;id=288375;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=654644;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0052089327946305275, 'model_time': 1.40301594696939, 'learning_rate':   +  9.97250205649004e-05, 'epoch': 5.06})   +04/16 [11:14:21] INFO  | >> Step 32200, Loss: {'action_dit_loss': 0.02617664262652397, 'mse_score': 0.001492711715400219, ]8;id=340981;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=399407;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0008207820355892181, 'model_time': 2.0214875983074307, 'learning_rate':   +  9.972298940993974e-05, 'epoch': 5.08})   +04/16 [11:18:38] INFO  | >> Step 32300, Loss: {'action_dit_loss': 0.031442176550626755, 'mse_score': 0.0017689277551003865, ]8;id=530108;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=634836;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007494019344449043, 'model_time': 6.012752899900079, 'learning_rate':   +  9.972095080263113e-05, 'epoch': 5.09})   +04/16 [11:22:44] INFO  | >> Step 32400, Loss: {'action_dit_loss': 0.034892451018095016, 'mse_score': 0.0030315880264554706, ]8;id=119971;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=894217;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0045413486659526825, 'model_time': 1.3306436846032739, 'learning_rate':   +  9.971890474329294e-05, 'epoch': 5.11})   +04/16 [11:26:51] INFO  | >> Step 32500, Loss: {'action_dit_loss': 0.03018176555633545, 'mse_score': 0.0019183138917599405, ]8;id=578116;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=755855;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00481463223695755, 'model_time': 1.9186196215450764, 'learning_rate':   +  9.971685123224466e-05, 'epoch': 5.12})   +04/16 [11:31:08] INFO  | >> Step 32600, Loss: {'action_dit_loss': 0.024236317723989487, 'mse_score': 0.0018920778696026122, ]8;id=931230;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=239592;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00040231645107269287, 'model_time': 5.639059340581298, 'learning_rate':   +  9.9714790269807e-05, 'epoch': 5.14})   +04/16 [11:35:15] INFO  | >> Step 32700, Loss: {'action_dit_loss': 0.022226577624678612, 'mse_score': 0.0023146215826272964, ]8;id=418098;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=436196;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008645222522318363, 'model_time': 1.3816613433882594, 'learning_rate':   +  9.971272185630177e-05, 'epoch': 5.16})   +04/16 [11:39:21] INFO  | >> Step 32800, Loss: {'action_dit_loss': 0.036259159445762634, 'mse_score': 0.001784210093319416, ]8;id=327704;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=697416;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004299294203519821, 'model_time': 1.9088377878069878, 'learning_rate':   +  9.971064599205196e-05, 'epoch': 5.17})   +04/16 [11:43:38] INFO  | >> Step 32900, Loss: {'action_dit_loss': 0.03637946769595146, 'mse_score': 0.0024323511336530957, ]8;id=720184;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=967819;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00447181798517704, 'model_time': 5.24257926363498, 'learning_rate':   +  9.970856267738175e-05, 'epoch': 5.19})   +04/16 [11:47:44] INFO  | >> Step 33000, Loss: {'action_dit_loss': 0.02548978291451931, 'mse_score': 0.0019076369436723845, ]8;id=89511;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=97758;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00036743469536304474, 'model_time': 1.434355859644711, 'learning_rate':   +  9.970647191261647e-05, 'epoch': 5.2})   +04/16 [11:51:51] INFO  | >> Step 33100, Loss: {'action_dit_loss': 0.021516209468245506, 'mse_score': 0.002060514342572008, ]8;id=390748;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=851201;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009225520305335522, 'model_time': 1.853983823210001, 'learning_rate':   +  9.97043736980826e-05, 'epoch': 5.22})   +04/16 [11:56:08] INFO  | >> Step 33200, Loss: {'action_dit_loss': 0.029477985575795174, 'mse_score': 0.001803342519061906, ]8;id=588866;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=588967;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0041323937475681305, 'model_time': 4.831734496168792, 'learning_rate':   +  9.97022680341078e-05, 'epoch': 5.23})   +04/16 [12:00:15] INFO  | >> Step 33300, Loss: {'action_dit_loss': 0.02989327162504196, 'mse_score': 0.0016552208523665155, ]8;id=370774;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=916043;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.005009031854569912, 'model_time': 1.391877201385796, 'learning_rate':   +  9.970015492102089e-05, 'epoch': 5.25})   +04/16 [12:04:21] INFO  | >> Step 33400, Loss: {'action_dit_loss': 0.0398675911128521, 'mse_score': 0.002742646262049675, ]8;id=910260;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=960331;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00038593728095293045, 'model_time': 1.882246327586472, 'learning_rate':   +  9.969803435915183e-05, 'epoch': 5.27})   +04/16 [12:08:38] INFO  | >> Step 33500, Loss: {'action_dit_loss': 0.026370326057076454, 'mse_score': 0.0021411944180727005, ]8;id=327626;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=368727;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009401540271937847, 'model_time': 5.814040084369481, 'learning_rate':   +  9.969590634883179e-05, 'epoch': 5.28})   +04/16 [12:12:44] INFO  | >> Step 33600, Loss: {'action_dit_loss': 0.031319860368967056, 'mse_score': 0.0017980603235108511, ]8;id=162246;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=688637;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00484574306756258, 'model_time': 1.3619365422055125, 'learning_rate':   +  9.969377089039307e-05, 'epoch': 5.3})   +04/16 [12:16:51] INFO  | >> Step 33700, Loss: {'action_dit_loss': 0.028492260724306107, 'mse_score': 0.0017996845500809805, ]8;id=367121;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=886438;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004644487053155899, 'model_time': 1.9685021415352821, 'learning_rate':   +  9.969162798416913e-05, 'epoch': 5.31})   +04/16 [12:21:08] INFO  | >> Step 33800, Loss: {'action_dit_loss': 0.019412627443671227, 'mse_score': 0.002012893690594605, ]8;id=292099;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=601987;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0008745994418859482, 'model_time': 5.563406568020582, 'learning_rate':   +  9.968947763049462e-05, 'epoch': 5.33})   +04/16 [12:25:15] INFO  | >> Step 33900, Loss: {'action_dit_loss': 0.017468536272644997, 'mse_score': 0.0031375419348478317, ]8;id=588215;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=804711;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009333784691989422, 'model_time': 1.35551549308002, 'learning_rate':   +  9.968731982970532e-05, 'epoch': 5.35})   +04/16 [12:29:22] INFO  | >> Step 34000, Loss: {'action_dit_loss': 0.02374103106558323, 'mse_score': 0.002963272322501455, ]8;id=673918;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=583783;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.005098480731248856, 'model_time': 1.96736341714859, 'learning_rate':   +  9.968515458213818e-05, 'epoch': 5.36})   +04/16 [12:33:38] INFO  | >> Step 34100, Loss: {'action_dit_loss': 0.027278713881969452, 'mse_score': 0.002889127071414675, ]8;id=869752;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=727157;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004241044633090496, 'model_time': 5.328283827751875, 'learning_rate':   +  9.968298188813136e-05, 'epoch': 5.38})   +04/16 [12:37:44] INFO  | >> Step 34200, Loss: {'action_dit_loss': 0.02839723788201809, 'mse_score': 0.003673590985792024, ]8;id=736833;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=799444;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0004583848640322685, 'model_time': 1.3008407093584538, 'learning_rate':   +  9.968080174802411e-05, 'epoch': 5.39})   +04/16 [12:41:51] INFO  | >> Step 34300, Loss: {'action_dit_loss': 0.02778276987373829, 'mse_score': 0.002516410978777068, ]8;id=6402;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=190217;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004747427999973297, 'model_time': 1.8853830769658089, 'learning_rate':   +  9.967861416215688e-05, 'epoch': 5.41})   +04/16 [12:46:08] INFO  | >> Step 34400, Loss: {'action_dit_loss': 0.031163029372692108, 'mse_score': 0.003538820892572403, ]8;id=420252;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=72965;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009714365005493164, 'model_time': 4.64530139323324, 'learning_rate':   +  9.967641913087128e-05, 'epoch': 5.42})   +04/16 [12:50:14] INFO  | >> Step 34500, Loss: {'action_dit_loss': 0.029320811852812767, 'mse_score': 0.002491659883941923, ]8;id=96214;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=782354;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0045743584632873535, 'model_time': 1.3048594361171126, 'learning_rate':   +  9.967421665451012e-05, 'epoch': 5.44})   +04/16 [12:54:21] INFO  | >> Step 34600, Loss: {'action_dit_loss': 0.027974549680948257, 'mse_score': 0.0023694533322538647, ]8;id=475682;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=357455;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00040444452315568924, 'model_time': 1.9944722102954984, 'learning_rate':   +  9.96720067334173e-05, 'epoch': 5.46})   +04/16 [12:58:38] INFO  | >> Step 34700, Loss: {'action_dit_loss': 0.034160442650318146, 'mse_score': 0.0018736537812011583, ]8;id=340140;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=814571;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.005008047446608543, 'model_time': 5.527555393986404, 'learning_rate':   +  9.96697893679379e-05, 'epoch': 5.47})   +04/16 [13:02:44] INFO  | >> Step 34800, Loss: {'action_dit_loss': 0.026829605922102928, 'mse_score': 0.003955080839140075, ]8;id=926251;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=55164;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008221447467803955, 'model_time': 1.3325910121202469, 'learning_rate':   +  9.966756455841822e-05, 'epoch': 5.49})   +04/16 [13:06:51] INFO  | >> Step 34900, Loss: {'action_dit_loss': 0.024012809619307518, 'mse_score': 0.0023144754980291638, ]8;id=52179;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=706707;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.005115320906043053, 'model_time': 1.991835051216185, 'learning_rate':   +  9.966533230520567e-05, 'epoch': 5.5})   +04/16 [13:11:08] INFO  | >> Step 35000, Loss: {'action_dit_loss': 0.01706952042877674, 'mse_score': 0.0023886518818991525, ]8;id=444611;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=509253;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00038764625787734985, 'model_time': 5.123599154874682, 'learning_rate':   +  9.966309260864883e-05, 'epoch': 5.52})   +04/16 [13:15:15] INFO  | >> Step 35100, Loss: {'action_dit_loss': 0.022177578881382942, 'mse_score': 0.0019109853144202913, ]8;id=226040;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=791615;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.005946577526628971, 'model_time': 1.3174610622227192, 'learning_rate':   +  9.966084546909745e-05, 'epoch': 5.53})   +04/16 [13:19:21] INFO  | >> Step 35200, Loss: {'action_dit_loss': 0.034575264900922775, 'mse_score': 0.002432046724217279, ]8;id=116276;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=297005;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.011284048669040203, 'model_time': 1.9943425804376602, 'learning_rate':   +  9.965859088690241e-05, 'epoch': 5.55})   +04/16 [13:23:37] INFO  | >> Step 35300, Loss: {'action_dit_loss': 0.02888851799070835, 'mse_score': 0.002165434882044792, ]8;id=552530;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=699539;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004292946308851242, 'model_time': 6.34740140568465, 'learning_rate':   +  9.965632886241584e-05, 'epoch': 5.57})   +04/16 [13:27:44] INFO  | >> Step 35400, Loss: {'action_dit_loss': 0.02916593849658966, 'mse_score': 0.0018358487369758742, ]8;id=628437;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=57443;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00023758411407470703, 'model_time': 1.3606359232217073, 'learning_rate':   +  9.965405939599094e-05, 'epoch': 5.58})   +04/16 [13:31:51] INFO  | >> Step 35500, Loss: {'action_dit_loss': 0.02671016938984394, 'mse_score': 0.002076731063425541, ]8;id=221494;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=804624;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004751142114400864, 'model_time': 1.973873883485794, 'learning_rate':   +  9.965178248798211e-05, 'epoch': 5.6})   +04/16 [13:35:54] INFO  | >> Step 35600, Loss: {'action_dit_loss': 0.0317118838429451, 'mse_score': 0.003901745857936995, ]8;id=344061;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=125812;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007609705440700054, 'model_time': 1.669997532851994, 'learning_rate':   +  9.964949813874493e-05, 'epoch': 5.61})   +04/16 [13:40:09] INFO  | >> Step 35700, Loss: {'action_dit_loss': 0.03793569654226303, 'mse_score': 0.0013977511386786187, ]8;id=184229;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=135461;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004956716671586037, 'model_time': 1.3178749131038785, 'learning_rate':   +  9.964720634863607e-05, 'epoch': 5.63})   +04/16 [13:44:16] INFO  | >> Step 35800, Loss: {'action_dit_loss': 0.028004243969917297, 'mse_score': 0.002238479309848377, ]8;id=524563;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=585864;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00024437345564365387, 'model_time': 1.9835716346278787, 'learning_rate':   +  9.964490711801346e-05, 'epoch': 5.64})   +04/16 [13:48:22] INFO  | >> Step 35900, Loss: {'action_dit_loss': 0.027810217812657356, 'mse_score': 0.003668171486684254, ]8;id=75576;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=416359;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004732160829007626, 'model_time': 1.7293990030884743, 'learning_rate':   +  9.964260044723613e-05, 'epoch': 5.66})   +04/16 [13:52:28] INFO  | >> Step 36000, Loss: {'action_dit_loss': 0.026447666808962822, 'mse_score': 0.001812403223344258, ]8;id=19651;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=482087;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009597983211278915, 'model_time': 1.935148511081934, 'learning_rate':   +  9.964028633666426e-05, 'epoch': 5.68})   +04/16 [13:56:41] INFO  | >> Step 36100, Loss: {'action_dit_loss': 0.0238747987896204, 'mse_score': 0.0015838917876992906, ]8;id=603727;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=450137;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0050397710874676704, 'model_time': 2.0116335302591324, 'learning_rate':   +  9.963796478665926e-05, 'epoch': 5.69})   +04/16 [14:00:49] INFO  | >> Step 36200, Loss: {'action_dit_loss': 0.02755768783390522, 'mse_score': 0.0033422751086098807, ]8;id=437983;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=303578;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003590807318687439, 'model_time': 1.691292641684413, 'learning_rate':   +  9.963563579758365e-05, 'epoch': 5.71})   +04/16 [14:04:54] INFO  | >> Step 36300, Loss: {'action_dit_loss': 0.033075399696826935, 'mse_score': 0.0017234282568097115, ]8;id=180222;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=840247;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004550796002149582, 'model_time': 1.3564714109525084, 'learning_rate':   +  9.96332993698011e-05, 'epoch': 5.72})   +04/16 [14:09:11] INFO  | >> Step 36400, Loss: {'action_dit_loss': 0.02441031113266945, 'mse_score': 0.0029517955013683866, ]8;id=723108;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=964448;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00833766907453537, 'model_time': 1.9232127144932747, 'learning_rate':   +  9.963095550367647e-05, 'epoch': 5.74})   +04/16 [14:13:18] INFO  | >> Step 36500, Loss: {'action_dit_loss': 0.0348820835351944, 'mse_score': 0.004353422405464309, ]8;id=111005;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=255135;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004671329632401466, 'model_time': 1.7688340479508042, 'learning_rate':   +  9.962860419957579e-05, 'epoch': 5.76})   +04/16 [14:17:24] INFO  | >> Step 36600, Loss: {'action_dit_loss': 0.048444878309965134, 'mse_score': 0.0026956554502248764, ]8;id=82467;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=414991;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002727136015892029, 'model_time': 1.3008888214826584, 'learning_rate':   +  9.962624545786622e-05, 'epoch': 5.77})   +04/16 [14:21:41] INFO  | >> Step 36700, Loss: {'action_dit_loss': 0.02660570852458477, 'mse_score': 0.003602140982236181, ]8;id=232335;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=349247;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.005314864218235016, 'model_time': 1.9552627746015787, 'learning_rate':   +  9.962387927891611e-05, 'epoch': 5.79})   +04/16 [14:25:48] INFO  | >> Step 36800, Loss: {'action_dit_loss': 0.02335592731833458, 'mse_score': 0.0035373603126832415, ]8;id=663984;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=119565;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008249740116298199, 'model_time': 1.7453615926206112, 'learning_rate':   +  9.962150566309495e-05, 'epoch': 5.8})   +04/16 [14:29:54] INFO  | >> Step 36900, Loss: {'action_dit_loss': 0.026754047721624374, 'mse_score': 0.0016711102798581123, ]8;id=813934;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=366346;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.006386548280715942, 'model_time': 1.3022682052105665, 'learning_rate':   +  9.961912461077338e-05, 'epoch': 5.82})   +04/16 [14:34:11] INFO  | >> Step 37000, Loss: {'action_dit_loss': 0.03923659771680832, 'mse_score': 0.002213618851133755, ]8;id=854628;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=154864;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00040603429079055786, 'model_time': 1.9266981231048703, 'learning_rate':   +  9.961673612232327e-05, 'epoch': 5.83})   +04/16 [14:38:18] INFO  | >> Step 37100, Loss: {'action_dit_loss': 0.03052433207631111, 'mse_score': 0.0032648774130003794, ]8;id=206854;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=181926;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.005342615768313408, 'model_time': 1.7454957412555814, 'learning_rate':   +  9.961434019811757e-05, 'epoch': 5.85})   +04/16 [14:42:24] INFO  | >> Step 37200, Loss: {'action_dit_loss': 0.02576817013323307, 'mse_score': 0.004386962790574346, ]8;id=687351;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=79013;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009483958594501019, 'model_time': 1.3036723220720887, 'learning_rate':   +  9.961193683853042e-05, 'epoch': 5.87})   +04/16 [14:46:41] INFO  | >> Step 37300, Loss: {'action_dit_loss': 0.024286892265081406, 'mse_score': 0.0020670805658612934, ]8;id=518119;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=486490;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004483823664486408, 'model_time': 1.9311578925698996, 'learning_rate':   +  9.960952604393716e-05, 'epoch': 5.88})   +04/16 [14:50:48] INFO  | >> Step 37400, Loss: {'action_dit_loss': 0.026055406779050827, 'mse_score': 0.003863480208175523, ]8;id=470711;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=714220;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002959035336971283, 'model_time': 1.710305318236351, 'learning_rate':   +  9.960710781471421e-05, 'epoch': 5.9})   +04/16 [14:54:54] INFO  | >> Step 37500, Loss: {'action_dit_loss': 0.026391079649329185, 'mse_score': 0.0018442589789628983, ]8;id=666158;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=654858;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004890876822173595, 'model_time': 1.2951816003769636, 'learning_rate':   +  9.960468215123923e-05, 'epoch': 5.91})   +04/16 [14:59:11] INFO  | >> Step 37600, Loss: {'action_dit_loss': 0.037702858448028564, 'mse_score': 0.0017180788729872023, ]8;id=158290;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=461124;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007656407542526722, 'model_time': 1.9573306273669004, 'learning_rate':   +  9.960224905389098e-05, 'epoch': 5.93})   +04/16 [15:03:18] INFO  | >> Step 37700, Loss: {'action_dit_loss': 0.036649107933044434, 'mse_score': 0.0015274453908205032, ]8;id=317530;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=835012;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.013189862482249737, 'model_time': 1.7079864842817187, 'learning_rate':   +  9.959980852304943e-05, 'epoch': 5.94})   +04/16 [15:07:24] INFO  | >> Step 37800, Loss: {'action_dit_loss': 0.03558912128210068, 'mse_score': 0.0029498349343027386, ]8;id=531981;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=77794;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00456556212157011, 'model_time': 1.3366823708638549, 'learning_rate':   +  9.959736055909568e-05, 'epoch': 5.96})   +04/16 [15:11:41] INFO  | >> Step 37900, Loss: {'action_dit_loss': 0.03348883241415024, 'mse_score': 0.003029670300228255, ]8;id=59653;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=386649;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00023518595844507217, 'model_time': 1.9504740256816149, 'learning_rate':   +  9.959490516241202e-05, 'epoch': 5.98})   +04/16 [15:15:48] INFO  | >> Step 38000, Loss: {'action_dit_loss': 0.036969296634197235, 'mse_score': 0.0016783346821154868, ]8;id=906231;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=896840;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00036698393523693085, 'model_time': 1.752291776239872, 'learning_rate':   +  9.959244233338185e-05, 'epoch': 5.99})   +04/16 [15:19:55] INFO  | >> Step 38100, Loss: {'action_dit_loss': 0.024955222383141518, 'mse_score': 0.0020758508305464473, ]8;id=403159;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=485188;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.011398234404623508, 'model_time': 1.3456628043204546, 'learning_rate':   +  9.95899720723898e-05, 'epoch': 6.01})   +04/16 [15:24:11] INFO  | >> Step 38200, Loss: {'action_dit_loss': 0.022790301591157913, 'mse_score': 0.003349211865237781, ]8;id=939394;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=43015;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.003986787982285023, 'model_time': 1.9339072667062283, 'learning_rate':   +  9.958749437982158e-05, 'epoch': 6.02})   +04/16 [15:28:18] INFO  | >> Step 38300, Loss: {'action_dit_loss': 0.02317340485751629, 'mse_score': 0.002374658893261637, ]8;id=683501;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=197383;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0006035231053829193, 'model_time': 1.7501250505447388, 'learning_rate':   +  9.958500925606413e-05, 'epoch': 6.04})   +04/16 [15:32:24] INFO  | >> Step 38400, Loss: {'action_dit_loss': 0.02810177393257618, 'mse_score': 0.00190447670008455, ]8;id=158189;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=64879;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003050388768315315, 'model_time': 1.370384112931788, 'learning_rate':   +  9.958251670150548e-05, 'epoch': 6.05})   +04/16 [15:36:41] INFO  | >> Step 38500, Loss: {'action_dit_loss': 0.02053699642419815, 'mse_score': 0.0029462275228330065, ]8;id=878053;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=360120;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.010012561455368996, 'model_time': 1.9237746391445398, 'learning_rate':   +  9.958001671653493e-05, 'epoch': 6.07})   +04/16 [15:40:48] INFO  | >> Step 38600, Loss: {'action_dit_loss': 0.03796815499663353, 'mse_score': 0.002821850191269602, ]8;id=180941;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=41043;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009118666872382164, 'model_time': 1.673696069046855, 'learning_rate':   +  9.957750930154283e-05, 'epoch': 6.09})   +04/16 [15:44:54] INFO  | >> Step 38700, Loss: {'action_dit_loss': 0.026836838573217392, 'mse_score': 0.0030893257686070035, ]8;id=549525;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=548141;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0007304186001420021, 'model_time': 1.3354653920978308, 'learning_rate':   +  9.957499445692076e-05, 'epoch': 6.1})   +04/16 [15:49:11] INFO  | >> Step 38800, Loss: {'action_dit_loss': 0.02242477610707283, 'mse_score': 0.0015079758263060025, ]8;id=962526;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=296635;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0005912547931075096, 'model_time': 1.8966849874705076, 'learning_rate':   +  9.957247218306141e-05, 'epoch': 6.12})   +04/16 [15:53:18] INFO  | >> Step 38900, Loss: {'action_dit_loss': 0.03136994317173958, 'mse_score': 0.002260579062359674, ]8;id=711875;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=626928;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007975894957780838, 'model_time': 1.7349254116415977, 'learning_rate':   +  9.956994248035867e-05, 'epoch': 6.13})   +04/16 [15:57:24] INFO  | >> Step 39000, Loss: {'action_dit_loss': 0.02377835102379322, 'mse_score': 0.0016664526026163781, ]8;id=350905;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=69113;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00716389250010252, 'model_time': 1.368507587350905, 'learning_rate':   +  9.956740534920756e-05, 'epoch': 6.15})   +04/16 [16:01:41] INFO  | >> Step 39100, Loss: {'action_dit_loss': 0.024650953710079193, 'mse_score': 0.0016733268275856972, ]8;id=405341;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=297949;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0005319751799106598, 'model_time': 1.9142957953736186, 'learning_rate':   +  9.956486079000428e-05, 'epoch': 6.17})   +04/16 [16:05:48] INFO  | >> Step 39200, Loss: {'action_dit_loss': 0.02496824972331524, 'mse_score': 0.002011624297925404, ]8;id=950369;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=631977;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0004092920571565628, 'model_time': 1.7233779458329082, 'learning_rate':   +  9.956230880314621e-05, 'epoch': 6.18})   +04/16 [16:09:54] INFO  | >> Step 39300, Loss: {'action_dit_loss': 0.025336945429444313, 'mse_score': 0.001983221487275192, ]8;id=611046;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=695847;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008722047321498394, 'model_time': 1.3324011247605085, 'learning_rate':   +  9.955974938903183e-05, 'epoch': 6.2})   +04/16 [16:14:09] INFO  | >> Step 39400, Loss: {'action_dit_loss': 0.025860778987407684, 'mse_score': 0.0013317577540874481, ]8;id=687923;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=732409;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007612714543938637, 'model_time': 7.761091153137386, 'learning_rate':   +  9.955718254806081e-05, 'epoch': 6.21})   +04/16 [16:18:13] INFO  | >> Step 39500, Loss: {'action_dit_loss': 0.03187153860926628, 'mse_score': 0.002358481554048402, ]8;id=743266;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=983566;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00040471646934747696, 'model_time': 1.6957830032333732, 'learning_rate':   +  9.955460828063402e-05, 'epoch': 6.23})   +04/16 [16:22:19] INFO  | >> Step 39600, Loss: {'action_dit_loss': 0.02273574098944664, 'mse_score': 0.0034765255238328662, ]8;id=674751;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=830117;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0005010645836591721, 'model_time': 1.2986660674214363, 'learning_rate':   +  9.955202658715343e-05, 'epoch': 6.24})   +04/16 [16:26:32] INFO  | >> Step 39700, Loss: {'action_dit_loss': 0.026460327208042145, 'mse_score': 0.005274188837834767, ]8;id=736971;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=869226;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008892509154975414, 'model_time': 8.045780370943248, 'learning_rate':   +  9.95494374680222e-05, 'epoch': 6.26})   +04/16 [16:30:43] INFO  | >> Step 39800, Loss: {'action_dit_loss': 0.02347690425813198, 'mse_score': 0.0017874242205704962, ]8;id=551963;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=97992;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008725027553737164, 'model_time': 1.6989450566470623, 'learning_rate':   +  9.954684092364463e-05, 'epoch': 6.28})   +04/16 [16:34:49] INFO  | >> Step 39900, Loss: {'action_dit_loss': 0.02398304082453251, 'mse_score': 0.0016107744138155664, ]8;id=379404;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=19116;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00033896975219249725, 'model_time': 1.314455864019692, 'learning_rate':   +  9.954423695442621e-05, 'epoch': 6.29})   +04/16 [16:39:02] INFO  | >> Step 40000, Loss: {'action_dit_loss': 0.026840705424547195, 'mse_score': 0.0018010554569108145, ]8;id=224597;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=358332;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003537023440003395, 'model_time': 7.755962163209915, 'learning_rate':   +  9.954162556077355e-05, 'epoch': 6.31})   +✅ Checkpoint saved at ./results/Checkpoints/0415_libero4in1_WanOFT/checkpoints/steps_40000 +04/16 [16:39:45] INFO  | >> 📊 Saving accessed configuration... ]8;id=237547;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=144247;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#238\238]8;;\ +  INFO  | >> 📦 Saving full merged configuration to ]8;id=826403;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=106053;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#242\242]8;;\ +  `results/Checkpoints/0415_libero4in1_WanOFT/config.full.yaml`...   +  INFO  | >> ✅ Configuration files saved ]8;id=774524;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=926607;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#244\244]8;;\ +04/16 [16:43:53] INFO  | >> Step 40100, Loss: {'action_dit_loss': 0.025438526645302773, 'mse_score': 0.0017348994900073325, ]8;id=918964;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=803531;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008546417579054832, 'model_time': 1.7374789351597428, 'learning_rate':   +  9.953900674309447e-05, 'epoch': 6.32})   +04/16 [16:48:09] INFO  | >> Step 40200, Loss: {'action_dit_loss': 0.025930874049663544, 'mse_score': 0.0018371979572943278, ]8;id=161745;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=170128;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008501100353896618, 'model_time': 1.7534564528614283, 'learning_rate':   +  9.953638050179789e-05, 'epoch': 6.34})   +04/16 [16:52:16] INFO  | >> Step 40300, Loss: {'action_dit_loss': 0.021547067910432816, 'mse_score': 0.0014577317716819899, ]8;id=655087;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=848343;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0007485430687665939, 'model_time': 1.8982851328328252, 'learning_rate':   +  9.953374683729395e-05, 'epoch': 6.35})   +04/16 [16:56:23] INFO  | >> Step 40400, Loss: {'action_dit_loss': 0.0257412176579237, 'mse_score': 0.0036912430077791214, ]8;id=45814;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=430816;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00046181678771972656, 'model_time': 1.6572872009128332, 'learning_rate':   +  9.95311057499939e-05, 'epoch': 6.37})   +04/16 [17:00:40] INFO  | >> Step 40500, Loss: {'action_dit_loss': 0.029790883883833885, 'mse_score': 0.0030636476086718695, ]8;id=465776;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=640255;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009479105472564697, 'model_time': 1.3115162597969174, 'learning_rate':   +  9.952845724031016e-05, 'epoch': 6.39})   +04/16 [17:04:46] INFO  | >> Step 40600, Loss: {'action_dit_loss': 0.020762061700224876, 'mse_score': 0.0012732862627932004, ]8;id=470735;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=245369;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008934363722801208, 'model_time': 1.89331722445786, 'learning_rate':   +  9.952580130865634e-05, 'epoch': 6.4})   +04/16 [17:08:53] INFO  | >> Step 40700, Loss: {'action_dit_loss': 0.0232879389077425, 'mse_score': 0.004928872521434512, ]8;id=822471;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=491798;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00028349459171295166, 'model_time': 1.6788474190980196, 'learning_rate':   +  9.952313795544717e-05, 'epoch': 6.42})   +04/16 [17:13:09] INFO  | >> Step 40800, Loss: {'action_dit_loss': 0.026588665321469307, 'mse_score': 0.0012675905600190163, ]8;id=711256;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=993137;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00030228588730096817, 'model_time': 1.3699608528986573, 'learning_rate':   +  9.952046718109857e-05, 'epoch': 6.43})   +04/16 [17:17:17] INFO  | >> Step 40900, Loss: {'action_dit_loss': 0.025738688185811043, 'mse_score': 0.0018879833764263562, ]8;id=295459;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=815922;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007740777917206287, 'model_time': 1.9871227601543069, 'learning_rate':   +  9.951778898602761e-05, 'epoch': 6.45})   +04/16 [17:21:23] INFO  | >> Step 41000, Loss: {'action_dit_loss': 0.02393398992717266, 'mse_score': 0.0057286109243120465, ]8;id=169930;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=856572;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007730050012469292, 'model_time': 1.704408691264689, 'learning_rate':   +  9.951510337065248e-05, 'epoch': 6.46})   +04/16 [17:25:40] INFO  | >> Step 41100, Loss: {'action_dit_loss': 0.02636648528277874, 'mse_score': 0.0018494782437171256, ]8;id=915408;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=262147;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00028910208493471146, 'model_time': 1.3243808224797249, 'learning_rate':   +  9.951241033539257e-05, 'epoch': 6.48})   +04/16 [17:29:46] INFO  | >> Step 41200, Loss: {'action_dit_loss': 0.021145587787032127, 'mse_score': 0.002825336530804634, ]8;id=389244;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=581478;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00030810199677944183, 'model_time': 1.8948506088927388, 'learning_rate':   +  9.950970988066843e-05, 'epoch': 6.5})   +04/16 [17:33:53] INFO  | >> Step 41300, Loss: {'action_dit_loss': 0.022764751687645912, 'mse_score': 0.001809372566640377, ]8;id=540970;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=892512;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007901682518422604, 'model_time': 1.6796541530638933, 'learning_rate':   +  9.950700200690177e-05, 'epoch': 6.51})   +04/16 [17:38:09] INFO  | >> Step 41400, Loss: {'action_dit_loss': 0.017987273633480072, 'mse_score': 0.001395030612392085, ]8;id=168099;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=286042;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009126032702624798, 'model_time': 1.3037998490035534, 'learning_rate':   +  9.950428671451543e-05, 'epoch': 6.53})   +04/16 [17:42:16] INFO  | >> Step 41500, Loss: {'action_dit_loss': 0.022954516112804413, 'mse_score': 0.0015046347730926105, ]8;id=871415;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=458723;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002869861200451851, 'model_time': 1.9349899804219604, 'learning_rate':   +  9.950156400393344e-05, 'epoch': 6.54})   +04/16 [17:46:23] INFO  | >> Step 41600, Loss: {'action_dit_loss': 0.0336894616484642, 'mse_score': 0.0018690722063183784, ]8;id=856375;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=473041;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0006522629410028458, 'model_time': 1.7174059702083468, 'learning_rate':   +  9.949883387558095e-05, 'epoch': 6.56})   +04/16 [17:50:39] INFO  | >> Step 41700, Loss: {'action_dit_loss': 0.03147010877728462, 'mse_score': 0.0018519059355769838, ]8;id=435050;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=55843;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008099136874079704, 'model_time': 1.326752527616918, 'learning_rate':   +  9.949609632988432e-05, 'epoch': 6.58})   +04/16 [17:54:46] INFO  | >> Step 41800, Loss: {'action_dit_loss': 0.02858530730009079, 'mse_score': 0.0025929132742541178, ]8;id=404924;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=85569;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007858267053961754, 'model_time': 1.900864620693028, 'learning_rate':   +  9.949335136727102e-05, 'epoch': 6.59})   +04/16 [17:58:53] INFO  | >> Step 41900, Loss: {'action_dit_loss': 0.026191676035523415, 'mse_score': 0.002373926873717989, ]8;id=976041;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=103896;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002339417114853859, 'model_time': 1.7051033051684499, 'learning_rate':   +  9.949059898816972e-05, 'epoch': 6.61})   +04/16 [18:03:09] INFO  | >> Step 42000, Loss: {'action_dit_loss': 0.023105107247829437, 'mse_score': 0.005933857922043119, ]8;id=829822;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=153143;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.000290493480861187, 'model_time': 1.2896202579140663, 'learning_rate':   +  9.948783919301019e-05, 'epoch': 6.62})   +04/16 [18:07:16] INFO  | >> Step 42100, Loss: {'action_dit_loss': 0.023233244195580482, 'mse_score': 0.0018683550879359245, ]8;id=870068;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=495404;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008146824315190315, 'model_time': 1.9041378693655133, 'learning_rate':   +  9.948507198222346e-05, 'epoch': 6.64})   +04/16 [18:11:23] INFO  | >> Step 42200, Loss: {'action_dit_loss': 0.018863141536712646, 'mse_score': 0.0017130345638309205, ]8;id=739808;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=491897;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007912136614322662, 'model_time': 1.6873606406152248, 'learning_rate':   +  9.948229735624157e-05, 'epoch': 6.65})   +04/16 [18:15:40] INFO  | >> Step 42300, Loss: {'action_dit_loss': 0.027352428063750267, 'mse_score': 0.0015504871095929826, ]8;id=83074;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=19927;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00026987213641405106, 'model_time': 1.3758035255596042, 'learning_rate':   +  9.947951531549787e-05, 'epoch': 6.67})   +04/16 [18:19:46] INFO  | >> Step 42400, Loss: {'action_dit_loss': 0.02795264683663845, 'mse_score': 0.0030862768845898764, ]8;id=575462;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=985898;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0004605976864695549, 'model_time': 1.9274342330172658, 'learning_rate':   +  9.947672586042677e-05, 'epoch': 6.69})   +04/16 [18:23:52] INFO  | >> Step 42500, Loss: {'action_dit_loss': 0.02172793261706829, 'mse_score': 0.0017733613827398845, ]8;id=116587;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=813875;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007810680195689201, 'model_time': 1.7422652272507548, 'learning_rate':   +  9.947392899146388e-05, 'epoch': 6.7})   +04/16 [18:28:09] INFO  | >> Step 42600, Loss: {'action_dit_loss': 0.024845343083143234, 'mse_score': 0.001686843511249338, ]8;id=50068;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=250021;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008184364065527916, 'model_time': 1.370557420887053, 'learning_rate':   +  9.947112470904594e-05, 'epoch': 6.72})   +04/16 [18:32:16] INFO  | >> Step 42700, Loss: {'action_dit_loss': 0.031597889959812164, 'mse_score': 0.0021654400708419935, ]8;id=479318;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=65858;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00033508986234664917, 'model_time': 1.907491398975253, 'learning_rate':   +  9.946831301361087e-05, 'epoch': 6.73})   +04/16 [18:36:22] INFO  | >> Step 42800, Loss: {'action_dit_loss': 0.025931308045983315, 'mse_score': 0.0019027157021420343, ]8;id=625726;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=562093;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00029391422867774963, 'model_time': 1.667609455063939, 'learning_rate':   +  9.946549390559772e-05, 'epoch': 6.75})   +04/16 [18:40:39] INFO  | >> Step 42900, Loss: {'action_dit_loss': 0.024018101394176483, 'mse_score': 0.0029483897877590997, ]8;id=253690;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=753448;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008840888738632202, 'model_time': 1.3236286537721753, 'learning_rate':   +  9.946266738544676e-05, 'epoch': 6.76})   +04/16 [18:44:46] INFO  | >> Step 43000, Loss: {'action_dit_loss': 0.021133681759238243, 'mse_score': 0.0019749420295868602, ]8;id=644674;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=369954;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009281239472329617, 'model_time': 1.9862631289288402, 'learning_rate':   +  9.945983345359933e-05, 'epoch': 6.78})   +04/16 [18:48:53] INFO  | >> Step 43100, Loss: {'action_dit_loss': 0.02360488660633564, 'mse_score': 0.0015792267929230417, ]8;id=696643;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=700674;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00036452338099479675, 'model_time': 1.6705216085538268, 'learning_rate':   +  9.945699211049802e-05, 'epoch': 6.8})   +04/16 [18:53:09] INFO  | >> Step 43200, Loss: {'action_dit_loss': 0.02219628356397152, 'mse_score': 0.0017312067959989821, ]8;id=999716;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=551613;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00044839829206466675, 'model_time': 1.3774739494547248, 'learning_rate':   +  9.945414335658648e-05, 'epoch': 6.81})   +04/16 [18:57:16] INFO  | >> Step 43300, Loss: {'action_dit_loss': 0.0291876383125782, 'mse_score': 0.002133748760180814, ]8;id=581070;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=21322;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008451317436993122, 'model_time': 1.9048265172168612, 'learning_rate':   +  9.94512871923096e-05, 'epoch': 6.83})   +04/16 [19:01:23] INFO  | >> Step 43400, Loss: {'action_dit_loss': 0.018467195332050323, 'mse_score': 0.003589923360518047, ]8;id=666549;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=405674;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009211307391524315, 'model_time': 1.6939183697104454, 'learning_rate':   +  9.944842361811338e-05, 'epoch': 6.84})   +04/16 [19:05:39] INFO  | >> Step 43500, Loss: {'action_dit_loss': 0.01996035687625408, 'mse_score': 0.001568282422210489, ]8;id=374440;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=826823;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.000228038989007473, 'model_time': 1.3125826604664326, 'learning_rate':   +  9.9445552634445e-05, 'epoch': 6.86})   +04/16 [19:09:46] INFO  | >> Step 43600, Loss: {'action_dit_loss': 0.02058793231844902, 'mse_score': 0.0022552513650485446, ]8;id=689023;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=658775;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.000279122032225132, 'model_time': 1.9601366156712174, 'learning_rate':   +  9.944267424175278e-05, 'epoch': 6.87})   +04/16 [19:13:53] INFO  | >> Step 43700, Loss: {'action_dit_loss': 0.028574833646416664, 'mse_score': 0.001623640236045633, ]8;id=793435;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=348671;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009388837963342667, 'model_time': 1.6754854544997215, 'learning_rate':   +  9.943978844048622e-05, 'epoch': 6.89})   +04/16 [19:18:08] INFO  | >> Step 43800, Loss: {'action_dit_loss': 0.024858679622411728, 'mse_score': 0.0027778263070753644, ]8;id=354992;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=853025;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008368261158466339, 'model_time': 1.314518103376031, 'learning_rate':   +  9.943689523109595e-05, 'epoch': 6.91})   +04/16 [19:22:16] INFO  | >> Step 43900, Loss: {'action_dit_loss': 0.028720742091536522, 'mse_score': 0.0016078344945396697, ]8;id=717941;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=487192;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003547975793480873, 'model_time': 1.9857730837538838, 'learning_rate':   +  9.943399461403376e-05, 'epoch': 6.92})   +04/16 [19:26:23] INFO  | >> Step 44000, Loss: {'action_dit_loss': 0.025766560807824135, 'mse_score': 0.001423643103667668, ]8;id=850916;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=141403;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003957943990826607, 'model_time': 1.7024874240159988, 'learning_rate':   +  9.943108658975262e-05, 'epoch': 6.94})   +04/16 [19:30:39] INFO  | >> Step 44100, Loss: {'action_dit_loss': 0.03305020555853844, 'mse_score': 0.002902305285845484, ]8;id=479911;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=38780;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002723252400755882, 'model_time': 1.339734892360866, 'learning_rate':   +  9.942817115870663e-05, 'epoch': 6.95})   +04/16 [19:34:46] INFO  | >> Step 44200, Loss: {'action_dit_loss': 0.022241635248064995, 'mse_score': 0.0016965435019561223, ]8;id=209159;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=928818;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0006148936226963997, 'model_time': 1.9438770869746804, 'learning_rate':   +  9.942524832135109e-05, 'epoch': 6.97})   +04/16 [19:38:53] INFO  | >> Step 44300, Loss: {'action_dit_loss': 0.030376698821783066, 'mse_score': 0.0016156759645257676, ]8;id=540418;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=417568;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.016861709766089916, 'model_time': 1.6797962579876184, 'learning_rate':   +  9.942231807814238e-05, 'epoch': 6.99})   +04/16 [19:43:09] INFO  | >> Step 44400, Loss: {'action_dit_loss': 0.022100381553173065, 'mse_score': 0.002292015456727573, ]8;id=38399;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=789882;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002964017912745476, 'model_time': 1.3462945399805903, 'learning_rate':   +  9.941938042953812e-05, 'epoch': 7.0})   +04/16 [19:47:16] INFO  | >> Step 44500, Loss: {'action_dit_loss': 0.028478598222136497, 'mse_score': 0.0022011451157076018, ]8;id=904017;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=818771;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003351578488945961, 'model_time': 1.853257899172604, 'learning_rate':   +  9.941643537599703e-05, 'epoch': 7.02})   +04/16 [19:51:23] INFO  | >> Step 44600, Loss: {'action_dit_loss': 0.028543269261717796, 'mse_score': 0.0030330454132386614, ]8;id=286488;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=130521;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0005118539556860924, 'model_time': 1.7029410023242235, 'learning_rate':   +  9.941348291797902e-05, 'epoch': 7.03})   +04/16 [19:55:28] INFO  | >> Step 44700, Loss: {'action_dit_loss': 0.023876361548900604, 'mse_score': 0.0012913734785148076, ]8;id=419453;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=779414;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0157224228605628, 'model_time': 2.0673809414729476, 'learning_rate':   +  9.941052305594513e-05, 'epoch': 7.05})   +04/16 [19:59:41] INFO  | >> Step 44800, Loss: {'action_dit_loss': 0.026937613263726234, 'mse_score': 0.00276312418282032, ]8;id=195892;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=520306;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003447774797677994, 'model_time': 1.9454844305291772, 'learning_rate':   +  9.940755579035756e-05, 'epoch': 7.06})   +04/16 [20:03:48] INFO  | >> Step 44900, Loss: {'action_dit_loss': 0.021919967606663704, 'mse_score': 0.002174921067697661, ]8;id=836020;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=544500;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0008061006665229797, 'model_time': 1.738562274724245, 'learning_rate':   +  9.940458112167968e-05, 'epoch': 7.08})   +04/16 [20:07:54] INFO  | >> Step 45000, Loss: {'action_dit_loss': 0.018257183954119682, 'mse_score': 0.0014770146725433214, ]8;id=445120;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=82760;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0005991030484437943, 'model_time': 1.3739636084064841, 'learning_rate':   +  9.940159905037602e-05, 'epoch': 7.1})   +04/16 [20:12:11] INFO  | >> Step 45100, Loss: {'action_dit_loss': 0.029089128598570824, 'mse_score': 0.001557228554572378, ]8;id=571971;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=308036;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.016201949678361416, 'model_time': 1.8842520350590348, 'learning_rate':   +  9.939860957691223e-05, 'epoch': 7.11})   +04/16 [20:16:18] INFO  | >> Step 45200, Loss: {'action_dit_loss': 0.022455770522356033, 'mse_score': 0.002878662198781967, ]8;id=693024;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=310000;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002590855583548546, 'model_time': 1.7225317703559995, 'learning_rate':   +  9.93956127017552e-05, 'epoch': 7.13})   +04/16 [20:20:24] INFO  | >> Step 45300, Loss: {'action_dit_loss': 0.019439399242401123, 'mse_score': 0.003007521852850914, ]8;id=446815;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=174739;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00035793427377939224, 'model_time': 1.3317335462197661, 'learning_rate':   +  9.939260842537284e-05, 'epoch': 7.14})   +04/16 [20:24:41] INFO  | >> Step 45400, Loss: {'action_dit_loss': 0.027502603828907013, 'mse_score': 0.0015806445319737708, ]8;id=44412;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=762120;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00026135891675949097, 'model_time': 2.0470287054777145, 'learning_rate':   +  9.938959674823433e-05, 'epoch': 7.16})   +04/16 [20:28:48] INFO  | >> Step 45500, Loss: {'action_dit_loss': 0.023970959708094597, 'mse_score': 0.0015013601098741805, ]8;id=456068;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=287892;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.013900624588131905, 'model_time': 1.7377993613481522, 'learning_rate':   +  9.938657767080996e-05, 'epoch': 7.17})   +04/16 [20:32:54] INFO  | >> Step 45600, Loss: {'action_dit_loss': 0.023130707442760468, 'mse_score': 0.0031108552856104715, ]8;id=78686;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=703787;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00024981796741485596, 'model_time': 1.3233875753358006, 'learning_rate':   +  9.938355119357122e-05, 'epoch': 7.19})   +04/16 [20:37:06] INFO  | >> Step 45700, Loss: {'action_dit_loss': 0.024208862334489822, 'mse_score': 0.0017073480412364006, ]8;id=840010;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=786325;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0004503568634390831, 'model_time': 8.780985243618488, 'learning_rate':   +  9.938051731699069e-05, 'epoch': 7.21})   +04/16 [20:41:13] INFO  | >> Step 45800, Loss: {'action_dit_loss': 0.018029537051916122, 'mse_score': 0.0016474443088684762, ]8;id=149715;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=889894;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00442879181355238, 'model_time': 1.7165463073179126, 'learning_rate':   +  9.937747604154212e-05, 'epoch': 7.22})   +04/16 [20:45:20] INFO  | >> Step 45900, Loss: {'action_dit_loss': 0.03201567009091377, 'mse_score': 0.0031081874455724445, ]8;id=36489;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=132361;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.011143643409013748, 'model_time': 1.3790302341803908, 'learning_rate':   +  9.937442736770046e-05, 'epoch': 7.24})   +04/16 [20:49:33] INFO  | >> Step 46000, Loss: {'action_dit_loss': 0.02949964627623558, 'mse_score': 0.003827212910567011, ]8;id=384123;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=379742;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0006645899266004562, 'model_time': 8.38237270154059, 'learning_rate':   +  9.937137129594178e-05, 'epoch': 7.25})   +04/16 [20:53:43] INFO  | >> Step 46100, Loss: {'action_dit_loss': 0.022811947390437126, 'mse_score': 0.0038088025259120123, ]8;id=634487;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=160891;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003513786941766739, 'model_time': 1.70711918361485, 'learning_rate':   +  9.936830782674329e-05, 'epoch': 7.27})   +04/16 [20:57:49] INFO  | >> Step 46200, Loss: {'action_dit_loss': 0.025515858083963394, 'mse_score': 0.0018022801460964339, ]8;id=390084;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=465504;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0047033559530973434, 'model_time': 1.3061378663405776, 'learning_rate':   +  9.93652369605834e-05, 'epoch': 7.28})   +04/16 [21:02:03] INFO  | >> Step 46300, Loss: {'action_dit_loss': 0.026353752240538597, 'mse_score': 0.00161107922238963, ]8;id=555178;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=384774;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.014426364563405514, 'model_time': 8.19897964131087, 'learning_rate':   +  9.936215869794167e-05, 'epoch': 7.3})   +04/16 [21:06:13] INFO  | >> Step 46400, Loss: {'action_dit_loss': 0.024871477857232094, 'mse_score': 0.004985549088035311, ]8;id=261736;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=118959;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003786170855164528, 'model_time': 1.698564963415265, 'learning_rate':   +  9.935907303929874e-05, 'epoch': 7.32})   +04/16 [21:10:19] INFO  | >> Step 46500, Loss: {'action_dit_loss': 0.0224886666983366, 'mse_score': 0.0016321142071059772, ]8;id=542895;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=405785;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003015166148543358, 'model_time': 1.3315747464075685, 'learning_rate':   +  9.935597998513651e-05, 'epoch': 7.33})   +04/16 [21:14:32] INFO  | >> Step 46600, Loss: {'action_dit_loss': 0.02150704339146614, 'mse_score': 0.0013263999883617675, ]8;id=812609;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=272933;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004181853495538235, 'model_time': 7.848392297513783, 'learning_rate':   +  9.935287953593794e-05, 'epoch': 7.35})   +04/16 [21:18:43] INFO  | >> Step 46700, Loss: {'action_dit_loss': 0.021080201491713524, 'mse_score': 0.0028385392257145475, ]8;id=299449;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=727691;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.011783629655838013, 'model_time': 1.6836350793018937, 'learning_rate':   +  9.934977169218726e-05, 'epoch': 7.36})   +04/16 [21:22:49] INFO  | >> Step 46800, Loss: {'action_dit_loss': 0.028495466336607933, 'mse_score': 0.004446929852877345, ]8;id=142321;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=894253;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0006691990420222282, 'model_time': 1.3422528533264995, 'learning_rate':   +  9.934665645436972e-05, 'epoch': 7.38})   +04/16 [21:27:03] INFO  | >> Step 46900, Loss: {'action_dit_loss': 0.029282912611961365, 'mse_score': 0.0028109760688883917, ]8;id=748022;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=466732;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002806391566991806, 'model_time': 8.348418361507356, 'learning_rate':   +  9.934353382297183e-05, 'epoch': 7.4})   +04/16 [21:31:13] INFO  | >> Step 47000, Loss: {'action_dit_loss': 0.020180046558380127, 'mse_score': 0.001669828114765031, ]8;id=335112;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=700280;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004534102976322174, 'model_time': 1.6838958580046892, 'learning_rate':   +  9.93404037984812e-05, 'epoch': 7.41})   +04/16 [21:35:19] INFO  | >> Step 47100, Loss: {'action_dit_loss': 0.014060910791158676, 'mse_score': 0.004843999764748982, ]8;id=568507;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=304466;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.01158156804740429, 'model_time': 1.3728867778554559, 'learning_rate':   +  9.933726638138662e-05, 'epoch': 7.43})   +04/16 [21:39:32] INFO  | >> Step 47200, Loss: {'action_dit_loss': 0.023496516048908234, 'mse_score': 0.001381197545145239, ]8;id=746385;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=744031;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0005868766456842422, 'model_time': 7.606322634033859, 'learning_rate':   +  9.9334121572178e-05, 'epoch': 7.44})   +04/16 [21:43:43] INFO  | >> Step 47300, Loss: {'action_dit_loss': 0.0275491401553154, 'mse_score': 0.002725625676768167, ]8;id=832250;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=379052;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003283880650997162, 'model_time': 1.7063008518889546, 'learning_rate':   +  9.933096937134647e-05, 'epoch': 7.46})   +04/16 [21:47:49] INFO  | >> Step 47400, Loss: {'action_dit_loss': 0.030263343825936317, 'mse_score': 0.0028241792959826334, ]8;id=830541;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=145622;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.005266668274998665, 'model_time': 1.3481524735689163, 'learning_rate':   +  9.932780977938423e-05, 'epoch': 7.47})   +04/16 [21:52:03] INFO  | >> Step 47500, Loss: {'action_dit_loss': 0.01919417455792427, 'mse_score': 0.003989845514297485, ]8;id=378427;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=580933;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.012402785941958427, 'model_time': 8.296964779496193, 'learning_rate':   +  9.932464279678471e-05, 'epoch': 7.49})   +04/16 [21:56:13] INFO  | >> Step 47600, Loss: {'action_dit_loss': 0.023432621732354164, 'mse_score': 0.00248930709702628, ]8;id=578443;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=136074;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00038791168481111526, 'model_time': 2.1162236565724015, 'learning_rate':   +  9.932146842404244e-05, 'epoch': 7.51})   +04/16 [22:00:20] INFO  | >> Step 47700, Loss: {'action_dit_loss': 0.019178709015250206, 'mse_score': 0.0014634176290460996, ]8;id=324314;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=417500;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0005799559876322746, 'model_time': 1.4647890254855156, 'learning_rate':   +  9.931828666165314e-05, 'epoch': 7.52})   +04/16 [22:04:32] INFO  | >> Step 47800, Loss: {'action_dit_loss': 0.020870771259069443, 'mse_score': 0.0013645671840224946, ]8;id=430749;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=806527;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0048835668712854385, 'model_time': 7.906722138635814, 'learning_rate':   +  9.931509751011362e-05, 'epoch': 7.54})   +04/16 [22:08:43] INFO  | >> Step 47900, Loss: {'action_dit_loss': 0.027187716215848923, 'mse_score': 0.0016326836443373135, ]8;id=131414;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=332427;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.01162974163889885, 'model_time': 1.6883839275687933, 'learning_rate':   +  9.931190096992199e-05, 'epoch': 7.55})   +04/16 [22:12:50] INFO  | >> Step 48000, Loss: {'action_dit_loss': 0.018834766000509262, 'mse_score': 0.0021957095180238995, ]8;id=713145;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=542491;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0005795536562800407, 'model_time': 1.3470627088099718, 'learning_rate':   +  9.930869704157732e-05, 'epoch': 7.57})   +04/16 [22:17:02] INFO  | >> Step 48100, Loss: {'action_dit_loss': 0.020302079617977142, 'mse_score': 0.0014434150819267546, ]8;id=818164;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=578083;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0006402125582098961, 'model_time': 8.053989314474165, 'learning_rate':   +  9.930548572558e-05, 'epoch': 7.58})   +04/16 [22:21:13] INFO  | >> Step 48200, Loss: {'action_dit_loss': 0.017651528120040894, 'mse_score': 0.003540937921830586, ]8;id=135300;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=453633;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004188009537756443, 'model_time': 1.6954391999170184, 'learning_rate':   +  9.930226702243146e-05, 'epoch': 7.6})   +04/16 [22:25:20] INFO  | >> Step 48300, Loss: {'action_dit_loss': 0.03150196373462677, 'mse_score': 0.0017709328926035336, ]8;id=871776;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=130192;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.01281772367656231, 'model_time': 1.4729927368462086, 'learning_rate':   +  9.929904093263433e-05, 'epoch': 7.62})   +04/16 [22:29:32] INFO  | >> Step 48400, Loss: {'action_dit_loss': 0.01954055391252041, 'mse_score': 0.0024922192096710205, ]8;id=169834;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=338334;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003018435090780258, 'model_time': 8.075359048321843, 'learning_rate':   +  9.929580745669243e-05, 'epoch': 7.63})   +04/16 [22:33:43] INFO  | >> Step 48500, Loss: {'action_dit_loss': 0.023555325344204903, 'mse_score': 0.003406586391585214, ]8;id=993508;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=986609;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00039128120988607407, 'model_time': 1.689018789678812, 'learning_rate':   +  9.929256659511064e-05, 'epoch': 7.65})   +04/16 [22:37:49] INFO  | >> Step 48600, Loss: {'action_dit_loss': 0.019550859928131104, 'mse_score': 0.003525905843291964, ]8;id=82690;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=262778;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0050122095271945, 'model_time': 1.3349442183971405, 'learning_rate':   +  9.92893183483951e-05, 'epoch': 7.66})   +04/16 [22:42:02] INFO  | >> Step 48700, Loss: {'action_dit_loss': 0.020992068573832512, 'mse_score': 0.0019321204828364508, ]8;id=131250;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=655383;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.01373948622494936, 'model_time': 7.657605511136353, 'learning_rate':   +  9.928606271705302e-05, 'epoch': 7.68})   +04/16 [22:46:13] INFO  | >> Step 48800, Loss: {'action_dit_loss': 0.020675186067819595, 'mse_score': 0.003012292885354587, ]8;id=526986;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=672124;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0006086062639951706, 'model_time': 1.7049953304231167, 'learning_rate':   +  9.92827997015928e-05, 'epoch': 7.69})   +04/16 [22:50:19] INFO  | >> Step 48900, Loss: {'action_dit_loss': 0.026239367201924324, 'mse_score': 0.003070083313754627, ]8;id=161684;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=179516;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0010495120659470558, 'model_time': 1.2981130201369524, 'learning_rate':   +  9.9279529302524e-05, 'epoch': 7.71})   +04/16 [22:54:33] INFO  | >> Step 49000, Loss: {'action_dit_loss': 0.017752304673194885, 'mse_score': 0.0030334158135311945, ]8;id=634534;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=354019;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004618550650775433, 'model_time': 8.450560696423054, 'learning_rate':   +  9.927625152035728e-05, 'epoch': 7.73})   +04/16 [22:58:43] INFO  | >> Step 49100, Loss: {'action_dit_loss': 0.02004174329340458, 'mse_score': 0.003345686144062451, ]8;id=865322;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=905740;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.011823697946965694, 'model_time': 1.7846939424052835, 'learning_rate':   +  9.927296635560454e-05, 'epoch': 7.74})   +04/16 [23:02:49] INFO  | >> Step 49200, Loss: {'action_dit_loss': 0.0162401981651783, 'mse_score': 0.0027687805039542063, ]8;id=672612;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=808475;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003713062033057213, 'model_time': 1.3306959047913551, 'learning_rate':   +  9.926967380877878e-05, 'epoch': 7.76})   +04/16 [23:07:03] INFO  | >> Step 49300, Loss: {'action_dit_loss': 0.024708028882741928, 'mse_score': 0.001650858936565263, ]8;id=804214;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=599929;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002491399645805359, 'model_time': 7.935171936638653, 'learning_rate':   +  9.926637388039414e-05, 'epoch': 7.77})   +04/16 [23:11:12] INFO  | >> Step 49400, Loss: {'action_dit_loss': 0.024135926738381386, 'mse_score': 0.002258169597813061, ]8;id=522230;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=932180;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004568774253129959, 'model_time': 1.6399868009611964, 'learning_rate':   +  9.926306657096595e-05, 'epoch': 7.79})   +04/16 [23:15:19] INFO  | >> Step 49500, Loss: {'action_dit_loss': 0.02411111444234848, 'mse_score': 0.001814606599509716, ]8;id=316768;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=506404;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.012189613655209541, 'model_time': 1.3612811816856265, 'learning_rate':   +  9.925975188101064e-05, 'epoch': 7.81})   +04/16 [23:19:33] INFO  | >> Step 49600, Loss: {'action_dit_loss': 0.022180860862135887, 'mse_score': 0.0017262069242341177, ]8;id=425818;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=311882;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003149360418319702, 'model_time': 8.513851327821612, 'learning_rate':   +  9.925642981104587e-05, 'epoch': 7.82})   +04/16 [23:23:43] INFO  | >> Step 49700, Loss: {'action_dit_loss': 0.028601091355085373, 'mse_score': 0.0015609340210046088, ]8;id=165759;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=460959;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0007286183536052704, 'model_time': 1.7339075934141874, 'learning_rate':   +  9.92531003615904e-05, 'epoch': 7.84})   +04/16 [23:27:49] INFO  | >> Step 49800, Loss: {'action_dit_loss': 0.02552909590303898, 'mse_score': 0.004112210124731064, ]8;id=356717;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=636129;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004394177347421646, 'model_time': 1.2914245119318366, 'learning_rate':   +  9.924976353316411e-05, 'epoch': 7.85})   +04/16 [23:32:03] INFO  | >> Step 49900, Loss: {'action_dit_loss': 0.022457754239439964, 'mse_score': 0.003161548769899777, ]8;id=334827;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=769864;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.014276894740760326, 'model_time': 8.28209789749235, 'learning_rate':   +  9.924641932628812e-05, 'epoch': 7.87})   +04/16 [23:36:13] INFO  | >> Step 50000, Loss: {'action_dit_loss': 0.018148165196180344, 'mse_score': 0.0013360099068709783, ]8;id=797615;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=388539;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00036081206053495407, 'model_time': 1.6700949808582664, 'learning_rate':   +  9.924306774148465e-05, 'epoch': 7.88})   +✅ Checkpoint saved at ./results/Checkpoints/0415_libero4in1_WanOFT/checkpoints/steps_50000 +04/16 [23:36:59] INFO  | >> 📊 Saving accessed configuration... ]8;id=253480;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=489131;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#238\238]8;;\ +  INFO  | >> 📦 Saving full merged configuration to ]8;id=147720;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=101514;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#242\242]8;;\ +  `results/Checkpoints/0415_libero4in1_WanOFT/config.full.yaml`...   +  INFO  | >> ✅ Configuration files saved ]8;id=906141;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=645270;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#244\244]8;;\ +04/16 [23:41:09] INFO  | >> Step 50100, Loss: {'action_dit_loss': 0.018328649923205376, 'mse_score': 0.0014499958072389876, ]8;id=167457;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=852993;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0005562929436564445, 'model_time': 1.3326050220057368, 'learning_rate':   +  9.923970877927707e-05, 'epoch': 7.9})   +04/16 [23:45:17] INFO  | >> Step 50200, Loss: {'action_dit_loss': 0.028043361380696297, 'mse_score': 0.003565445010151182, ]8;id=327905;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=199055;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004393245093524456, 'model_time': 1.9045689580962062, 'learning_rate':   +  9.92363424401899e-05, 'epoch': 7.92})   +04/16 [23:49:23] INFO  | >> Step 50300, Loss: {'action_dit_loss': 0.020491380244493484, 'mse_score': 0.0015949857022081102, ]8;id=489491;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=522987;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003051580861210823, 'model_time': 1.7051442991942167, 'learning_rate':   +  9.923296872474886e-05, 'epoch': 7.93})   +04/16 [23:53:39] INFO  | >> Step 50400, Loss: {'action_dit_loss': 0.022729504853487015, 'mse_score': 0.0013834952509828977, ]8;id=94423;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=991148;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00039461441338062286, 'model_time': 1.3339034728705883, 'learning_rate':   +  9.922958763348073e-05, 'epoch': 7.95})   +04/16 [23:57:46] INFO  | >> Step 50500, Loss: {'action_dit_loss': 0.023634307086467743, 'mse_score': 0.004450467548200062, ]8;id=225595;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=611680;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.01256992481648922, 'model_time': 1.9400946469977498, 'learning_rate':   +  9.922619916691353e-05, 'epoch': 7.96})   +04/17 [00:01:53] INFO  | >> Step 50600, Loss: {'action_dit_loss': 0.021007847040891647, 'mse_score': 0.0017855994935546602, ]8;id=518934;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=626543;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004064916633069515, 'model_time': 1.6469147438183427, 'learning_rate':   +  9.922280332557638e-05, 'epoch': 7.98})   +04/17 [00:06:09] INFO  | >> Step 50700, Loss: {'action_dit_loss': 0.022354723885655403, 'mse_score': 0.001321363795016493, ]8;id=493446;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=299628;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00033863820135593414, 'model_time': 1.3394438046962023, 'learning_rate':   +  9.921940010999959e-05, 'epoch': 7.99})   +04/17 [00:10:16] INFO  | >> Step 50800, Loss: {'action_dit_loss': 0.014767928048968315, 'mse_score': 0.004453024161713464, ]8;id=451860;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=140440;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00040087103843688965, 'model_time': 1.8948090989142656, 'learning_rate':   +  9.92159895207146e-05, 'epoch': 8.01})   +04/17 [00:14:23] INFO  | >> Step 50900, Loss: {'action_dit_loss': 0.018612606450915337, 'mse_score': 0.0016534818070275442, ]8;id=800961;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=422842;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.013228369876742363, 'model_time': 1.678060150705278, 'learning_rate':   +  9.921257155825398e-05, 'epoch': 8.03})   +04/17 [00:18:39] INFO  | >> Step 51000, Loss: {'action_dit_loss': 0.015432560816407204, 'mse_score': 0.001532129677278655, ]8;id=597983;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=589107;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004577883519232273, 'model_time': 1.2857981324195862, 'learning_rate':   +  9.920914622315151e-05, 'epoch': 8.04})   +04/17 [00:22:46] INFO  | >> Step 51100, Loss: {'action_dit_loss': 0.026557553559541702, 'mse_score': 0.0027303453534841537, ]8;id=77103;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=405116;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00023475848138332367, 'model_time': 1.8892444698140025, 'learning_rate':   +  9.920571351594203e-05, 'epoch': 8.06})   +04/17 [00:26:53] INFO  | >> Step 51200, Loss: {'action_dit_loss': 0.021387290209531784, 'mse_score': 0.0028776039502450396, ]8;id=293308;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=865401;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00036274734884500504, 'model_time': 1.6954013286158442, 'learning_rate':   +  9.920227343716164e-05, 'epoch': 8.07})   +04/17 [00:31:10] INFO  | >> Step 51300, Loss: {'action_dit_loss': 0.02164285071194172, 'mse_score': 0.0013321332101311003, ]8;id=134913;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=101377;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.012370014563202858, 'model_time': 1.314377224072814, 'learning_rate':   +  9.919882598734751e-05, 'epoch': 8.09})   +04/17 [00:35:17] INFO  | >> Step 51400, Loss: {'action_dit_loss': 0.022390790283679962, 'mse_score': 0.0014467404357024602, ]8;id=584929;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=984558;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.005208862014114857, 'model_time': 2.0684730065986514, 'learning_rate':   +  9.919537116703797e-05, 'epoch': 8.1})   +04/17 [00:39:23] INFO  | >> Step 51500, Loss: {'action_dit_loss': 0.017568567767739296, 'mse_score': 0.001534556970000267, ]8;id=631728;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=533853;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.000706622377038002, 'model_time': 1.719033864326775, 'learning_rate':   +  9.919190897677257e-05, 'epoch': 8.12})   +04/17 [00:43:39] INFO  | >> Step 51600, Loss: {'action_dit_loss': 0.019853420555591583, 'mse_score': 0.0022796738360609326, ]8;id=40804;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=143693;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0004131915047764778, 'model_time': 1.3019890030846, 'learning_rate':   +  9.918843941709193e-05, 'epoch': 8.14})   +04/17 [00:47:46] INFO  | >> Step 51700, Loss: {'action_dit_loss': 0.03208555281162262, 'mse_score': 0.0036860198846885134, ]8;id=544559;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=479187;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.012951456010341644, 'model_time': 1.921158703044057, 'learning_rate':   +  9.918496248853786e-05, 'epoch': 8.15})   +04/17 [00:51:53] INFO  | >> Step 51800, Loss: {'action_dit_loss': 0.03984677046537399, 'mse_score': 0.0024277509323188235, ]8;id=146570;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=343897;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0037417635321617126, 'model_time': 1.6525567937642336, 'learning_rate':   +  9.91814781916533e-05, 'epoch': 8.17})   +04/17 [00:56:10] INFO  | >> Step 51900, Loss: {'action_dit_loss': 0.01660800538957119, 'mse_score': 0.004136209509202412, ]8;id=412042;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=646447;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00038621481508016586, 'model_time': 1.3879162222146988, 'learning_rate':   +  9.917798652698238e-05, 'epoch': 8.18})   +04/17 [01:00:17] INFO  | >> Step 52000, Loss: {'action_dit_loss': 0.022646542638540268, 'mse_score': 0.0025274083018302917, ]8;id=352713;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=531958;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002937614917755127, 'model_time': 1.954510012641549, 'learning_rate':   +  9.91744874950703e-05, 'epoch': 8.2})   +04/17 [01:04:23] INFO  | >> Step 52100, Loss: {'action_dit_loss': 0.022204678505659103, 'mse_score': 0.00266599389059203, ]8;id=743167;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=590268;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.012451927177608013, 'model_time': 1.6914929253980517, 'learning_rate':   +  9.917098109646351e-05, 'epoch': 8.22})   +04/17 [01:08:36] INFO  | >> Step 52200, Loss: {'action_dit_loss': 0.022220049053430557, 'mse_score': 0.0013777901019368852, ]8;id=386251;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=347329;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004831441678106785, 'model_time': 2.168640893884003, 'learning_rate':   +  9.916746733170954e-05, 'epoch': 8.23})   +04/17 [01:12:41] INFO  | >> Step 52300, Loss: {'action_dit_loss': 0.026048623025417328, 'mse_score': 0.0028058194688388278, ]8;id=322623;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=835457;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003066333010792732, 'model_time': 1.9412362659350038, 'learning_rate':   +  9.916394620135712e-05, 'epoch': 8.25})   +04/17 [01:16:48] INFO  | >> Step 52400, Loss: {'action_dit_loss': 0.022370416671037674, 'mse_score': 0.0017403610316770418, ]8;id=659827;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=27941;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002972446382045746, 'model_time': 1.7154345018789172, 'learning_rate':   +  9.916041770595608e-05, 'epoch': 8.26})   +04/17 [01:20:54] INFO  | >> Step 52500, Loss: {'action_dit_loss': 0.01667872443795204, 'mse_score': 0.0015640764364174434, ]8;id=820934;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=813864;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009526591747999191, 'model_time': 1.3777653640136123, 'learning_rate':   +  9.915688184605742e-05, 'epoch': 8.28})   +04/17 [01:25:12] INFO  | >> Step 52600, Loss: {'action_dit_loss': 0.021906770765781403, 'mse_score': 0.00233959752534117, ]8;id=53849;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=611868;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008768612518906593, 'model_time': 1.935862342827022, 'learning_rate':   +  9.915333862221332e-05, 'epoch': 8.29})   +04/17 [01:29:18] INFO  | >> Step 52700, Loss: {'action_dit_loss': 0.0296698659658432, 'mse_score': 0.0037221919213022503, ]8;id=756215;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=649840;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0008081449195742607, 'model_time': 1.868833290413022, 'learning_rate':   +  9.914978803497707e-05, 'epoch': 8.31})   +04/17 [01:33:24] INFO  | >> Step 52800, Loss: {'action_dit_loss': 0.02224375121295452, 'mse_score': 0.002581442041056497, ]8;id=861574;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=713793;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00024884380400180817, 'model_time': 1.3398757157847285, 'learning_rate':   +  9.914623008490312e-05, 'epoch': 8.33})   +04/17 [01:37:41] INFO  | >> Step 52900, Loss: {'action_dit_loss': 0.01904566027224064, 'mse_score': 0.001561249074126993, ]8;id=734549;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=115233;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.010332118719816208, 'model_time': 1.9388893460854888, 'learning_rate':   +  9.914266477254706e-05, 'epoch': 8.34})   +04/17 [01:41:48] INFO  | >> Step 53000, Loss: {'action_dit_loss': 0.02595035545527935, 'mse_score': 0.0017188448192817824, ]8;id=439122;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=158787;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008873186074197292, 'model_time': 1.718142595142126, 'learning_rate':   +  9.91390920984657e-05, 'epoch': 8.36})   +04/17 [01:45:52] INFO  | >> Step 53100, Loss: {'action_dit_loss': 0.025186624377965927, 'mse_score': 0.0030450067882026944, ]8;id=526195;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=812617;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00027154386043548584, 'model_time': 1.3300894377753139, 'learning_rate':   +  9.913551206321687e-05, 'epoch': 8.37})   +04/17 [01:50:03] INFO  | >> Step 53200, Loss: {'action_dit_loss': 0.02555878274142742, 'mse_score': 0.002653084695339203, ]8;id=889587;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=771581;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003013312816619873, 'model_time': 8.349841299466789, 'learning_rate':   +  9.913192466735967e-05, 'epoch': 8.39})   +04/17 [01:54:13] INFO  | >> Step 53300, Loss: {'action_dit_loss': 0.025445831939578056, 'mse_score': 0.0013177028990217618, ]8;id=543878;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=217413;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.011528021655976772, 'model_time': 1.6780478339642286, 'learning_rate':   +  9.912832991145429e-05, 'epoch': 8.4})   +04/17 [01:58:19] INFO  | >> Step 53400, Loss: {'action_dit_loss': 0.023687686771154404, 'mse_score': 0.003204404243401119, ]8;id=551002;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=395129;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009051837958395481, 'model_time': 1.3471632711589336, 'learning_rate':   +  9.912472779606209e-05, 'epoch': 8.42})   +04/17 [02:02:32] INFO  | >> Step 53500, Loss: {'action_dit_loss': 0.02192135900259018, 'mse_score': 0.003050448639052255, ]8;id=559024;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=358955;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0007622633129358292, 'model_time': 7.518385345116258, 'learning_rate':   +  9.912111832174556e-05, 'epoch': 8.44})   +04/17 [02:06:43] INFO  | >> Step 53600, Loss: {'action_dit_loss': 0.022256528958678246, 'mse_score': 0.0016069041032876288, ]8;id=909801;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=755944;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003210660070180893, 'model_time': 1.7171167777851224, 'learning_rate':   +  9.911750148906836e-05, 'epoch': 8.45})   +04/17 [02:10:47] INFO  | >> Step 53700, Loss: {'action_dit_loss': 0.023019088432192802, 'mse_score': 0.0014690994950277464, ]8;id=277203;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=639711;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007658426649868488, 'model_time': 1.326679457910359, 'learning_rate':   +  9.911387729859527e-05, 'epoch': 8.47})   +04/17 [02:14:51] INFO  | >> Step 53800, Loss: {'action_dit_loss': 0.02808738686144352, 'mse_score': 0.001765759794839791, ]8;id=585196;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=312999;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008104178123176098, 'model_time': 1.869740467518568, 'learning_rate':   +  9.911024575089226e-05, 'epoch': 8.48})   +04/17 [02:19:08] INFO  | >> Step 53900, Loss: {'action_dit_loss': 0.01996964029967785, 'mse_score': 0.0016881568091256277, ]8;id=303042;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=739142;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003160899505019188, 'model_time': 5.825121330097318, 'learning_rate':   +  9.91066068465264e-05, 'epoch': 8.5})   +04/17 [02:23:14] INFO  | >> Step 54000, Loss: {'action_dit_loss': 0.018986383453011513, 'mse_score': 0.0014314244368246623, ]8;id=332441;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=503110;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002319440245628357, 'model_time': 1.3223155597224832, 'learning_rate':   +  9.910296058606596e-05, 'epoch': 8.51})   +04/17 [02:27:21] INFO  | >> Step 54100, Loss: {'action_dit_loss': 0.015349131077528, 'mse_score': 0.001191227829882077, ]8;id=834042;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=756719;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009496591985225677, 'model_time': 2.0324757555499673, 'learning_rate':   +  9.909930697008033e-05, 'epoch': 8.53})   +04/17 [02:31:38] INFO  | >> Step 54200, Loss: {'action_dit_loss': 0.017299186438322067, 'mse_score': 0.0011415741007242883, ]8;id=709489;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=569576;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008641048334538937, 'model_time': 5.514773840084672, 'learning_rate':   +  9.909564599914004e-05, 'epoch': 8.55})   +04/17 [02:35:44] INFO  | >> Step 54300, Loss: {'action_dit_loss': 0.019583426415920258, 'mse_score': 0.0016469358067427362, ]8;id=361899;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=810616;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0005977954715490341, 'model_time': 1.308077361434698, 'learning_rate':   +  9.90919776738168e-05, 'epoch': 8.56})   +04/17 [02:39:51] INFO  | >> Step 54400, Loss: {'action_dit_loss': 0.02246149070560932, 'mse_score': 0.0014065498752253397, ]8;id=301602;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=748831;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0005643414333462715, 'model_time': 1.9951050095260143, 'learning_rate':   +  9.908830199468344e-05, 'epoch': 8.58})   +04/17 [02:44:08] INFO  | >> Step 54500, Loss: {'action_dit_loss': 0.019736051559448242, 'mse_score': 0.0039053293211119516, ]8;id=687836;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=268900;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007794411852955818, 'model_time': 5.111243984661996, 'learning_rate':   +  9.908461896231394e-05, 'epoch': 8.59})   +04/17 [02:48:14] INFO  | >> Step 54600, Loss: {'action_dit_loss': 0.021256260573863983, 'mse_score': 0.0019014042669108935, ]8;id=868170;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=564739;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008302588947117329, 'model_time': 1.3136250721290708, 'learning_rate':   +  9.908092857728345e-05, 'epoch': 8.61})   +04/17 [02:52:21] INFO  | >> Step 54700, Loss: {'action_dit_loss': 0.02127673476934433, 'mse_score': 0.0015347945903028762, ]8;id=284815;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=143941;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00027416646480560303, 'model_time': 1.9364067614078522, 'learning_rate':   +  9.907723084016827e-05, 'epoch': 8.63})   +04/17 [02:56:38] INFO  | >> Step 54800, Loss: {'action_dit_loss': 0.02292264811694622, 'mse_score': 0.003093996484364782, ]8;id=250905;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=254235;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.000380469486117363, 'model_time': 5.164431684650481, 'learning_rate':   +  9.907352575154578e-05, 'epoch': 8.64})   +04/17 [03:00:45] INFO  | >> Step 54900, Loss: {'action_dit_loss': 0.016355786472558975, 'mse_score': 0.001081606506236962, ]8;id=236633;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=668933;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008508085273206234, 'model_time': 1.325715346261859, 'learning_rate':   +  9.906981331199461e-05, 'epoch': 8.66})   +04/17 [03:04:51] INFO  | >> Step 55000, Loss: {'action_dit_loss': 0.027115140110254288, 'mse_score': 0.0029649239565644947, ]8;id=346337;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=752204;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00961998850107193, 'model_time': 2.0107539761811495, 'learning_rate':   +  9.906609352209448e-05, 'epoch': 8.67})   +04/17 [03:09:08] INFO  | >> Step 55100, Loss: {'action_dit_loss': 0.019636793062090874, 'mse_score': 0.002440836014492171, ]8;id=144144;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=5433;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0004944596439599991, 'model_time': 5.142214518971741, 'learning_rate':   +  9.906236638242625e-05, 'epoch': 8.69})   +04/17 [03:13:14] INFO  | >> Step 55200, Loss: {'action_dit_loss': 0.023955410346388817, 'mse_score': 0.0015499078269515718, ]8;id=684607;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=980452;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00026963837444782257, 'model_time': 1.2859623283147812, 'learning_rate':   +  9.905863189357196e-05, 'epoch': 8.7})   +04/17 [03:17:21] INFO  | >> Step 55300, Loss: {'action_dit_loss': 0.0206467155367136, 'mse_score': 0.0012184714100190572, ]8;id=682139;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=209144;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008871729485690594, 'model_time': 1.9513212125748396, 'learning_rate':   +  9.905489005611478e-05, 'epoch': 8.72})   +04/17 [03:21:38] INFO  | >> Step 55400, Loss: {'action_dit_loss': 0.02131984755396843, 'mse_score': 0.0013834418995039804, ]8;id=677273;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=62036;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008371811360120773, 'model_time': 5.569684434682131, 'learning_rate':   +  9.905114087063903e-05, 'epoch': 8.74})   +04/17 [03:25:44] INFO  | >> Step 55500, Loss: {'action_dit_loss': 0.01998966373503208, 'mse_score': 0.0013414907402225903, ]8;id=602022;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=243500;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003413064405322075, 'model_time': 1.338280144147575, 'learning_rate':   +  9.904738433773016e-05, 'epoch': 8.75})   +04/17 [03:29:51] INFO  | >> Step 55600, Loss: {'action_dit_loss': 0.021558327600359917, 'mse_score': 0.001739762324307646, ]8;id=982169;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=39110;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003679124638438225, 'model_time': 1.9120779195800424, 'learning_rate':   +  9.904362045797479e-05, 'epoch': 8.77})   +04/17 [03:34:08] INFO  | >> Step 55700, Loss: {'action_dit_loss': 0.0215781107544899, 'mse_score': 0.0015289079664008959, ]8;id=925100;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=878292;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009518689475953579, 'model_time': 5.0280337985605, 'learning_rate':   +  9.903984923196068e-05, 'epoch': 8.78})   +04/17 [03:38:15] INFO  | >> Step 55800, Loss: {'action_dit_loss': 0.02161262370646, 'mse_score': 0.0014634664569582259, ]8;id=876822;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=416278;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009916183538734913, 'model_time': 1.3116396395489573, 'learning_rate':   +  9.903607066027678e-05, 'epoch': 8.8})   +04/17 [03:42:21] INFO  | >> Step 55900, Loss: {'action_dit_loss': 0.020302748307585716, 'mse_score': 0.0013464460415499552, ]8;id=785386;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=914663;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003709206357598305, 'model_time': 1.8876497242599726, 'learning_rate':   +  9.90322847435131e-05, 'epoch': 8.81})   +04/17 [03:46:37] INFO  | >> Step 56000, Loss: {'action_dit_loss': 0.02514447644352913, 'mse_score': 0.0017212126404047012, ]8;id=9717;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=312886;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.000356798991560936, 'model_time': 6.263356403447688, 'learning_rate':   +  9.902849148226086e-05, 'epoch': 8.83})   +04/17 [03:50:43] INFO  | >> Step 56100, Loss: {'action_dit_loss': 0.020023217424750328, 'mse_score': 0.00123089605144092, ]8;id=351317;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=298384;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009009336121380329, 'model_time': 1.316628858447075, 'learning_rate':   +  9.902469087711239e-05, 'epoch': 8.85})   +04/17 [03:54:51] INFO  | >> Step 56200, Loss: {'action_dit_loss': 0.025742165744304657, 'mse_score': 0.001727670431137085, ]8;id=517904;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=932456;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007790976203978062, 'model_time': 1.9211164144799113, 'learning_rate':   +  9.902088292866122e-05, 'epoch': 8.86})   +04/17 [03:59:08] INFO  | >> Step 56300, Loss: {'action_dit_loss': 0.02403803914785385, 'mse_score': 0.002460391659821783, ]8;id=490755;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=286090;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003991667181253433, 'model_time': 5.905205767601728, 'learning_rate':   +  9.901706763750195e-05, 'epoch': 8.88})   +04/17 [04:03:14] INFO  | >> Step 56400, Loss: {'action_dit_loss': 0.018880197778344154, 'mse_score': 0.0025070224489484516, ]8;id=170387;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=766634;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00023644324392080307, 'model_time': 1.3604387110099196, 'learning_rate':   +  9.901324500423044e-05, 'epoch': 8.89})   +04/17 [04:07:20] INFO  | >> Step 56500, Loss: {'action_dit_loss': 0.03153521567583084, 'mse_score': 0.0021467989842806545, ]8;id=195243;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=14768;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00912044383585453, 'model_time': 2.0179522028192878, 'learning_rate':   +  9.900941502944354e-05, 'epoch': 8.91})   +04/17 [04:11:38] INFO  | >> Step 56600, Loss: {'action_dit_loss': 0.025587376207113266, 'mse_score': 0.002677977883390018, ]8;id=595361;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=707160;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0005027856677770615, 'model_time': 5.267831820063293, 'learning_rate':   +  9.90055777137394e-05, 'epoch': 8.92})   +04/17 [04:15:44] INFO  | >> Step 56700, Loss: {'action_dit_loss': 0.02562580443918705, 'mse_score': 0.0013604987678783281, ]8;id=897734;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=669752;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.017314905300736427, 'model_time': 1.2830134695395827, 'learning_rate':   +  9.900173305771721e-05, 'epoch': 8.94})   +04/17 [04:19:51] INFO  | >> Step 56800, Loss: {'action_dit_loss': 0.028439009562134743, 'mse_score': 0.0021506912474121365, ]8;id=540310;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=343856;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0004034917801618576, 'model_time': 1.9672360913828015, 'learning_rate':   +  9.899788106197736e-05, 'epoch': 8.96})   +04/17 [04:24:08] INFO  | >> Step 56900, Loss: {'action_dit_loss': 0.021839972585439682, 'mse_score': 0.0010535522097987787, ]8;id=193757;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=147442;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0004954114556312561, 'model_time': 4.186906175687909, 'learning_rate':   +  9.899402172712137e-05, 'epoch': 8.97})   +04/17 [04:28:15] INFO  | >> Step 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{'action_dit_loss': 0.02036910131573677, 'mse_score': 0.0016573666195784295, ]8;id=11991;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=274258;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00040012411773204803, 'model_time': 5.122550997883081, 'learning_rate':   +  9.898239969388901e-05, 'epoch': 9.02})   +04/17 [04:40:45] INFO  | >> Step 57300, Loss: {'action_dit_loss': 0.02442730776965618, 'mse_score': 0.0015047405447278703, ]8;id=65142;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=700224;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0004892032593488693, 'model_time': 1.4172891043126583, 'learning_rate':   +  9.897851100860662e-05, 'epoch': 9.04})   +04/17 [04:44:51] INFO  | >> Step 57400, Loss: {'action_dit_loss': 0.015985216945409775, 'mse_score': 0.0015450177182044303, ]8;id=425110;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=719400;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004851606674492359, 'model_time': 1.9819611953571439, 'learning_rate':   +  9.897461498723288e-05, 'epoch': 9.05})   +04/17 [04:49:08] INFO  | >> Step 57500, Loss: {'action_dit_loss': 0.021922023966908455, 'mse_score': 0.001461103026356016, ]8;id=737733;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=807236;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.011282974854111671, 'model_time': 5.19329796358943, 'learning_rate':   +  9.89707116303762e-05, 'epoch': 9.07})   +04/17 [04:53:13] INFO  | >> Step 57600, Loss: {'action_dit_loss': 0.020426202565431595, 'mse_score': 0.0026212848190750393, ]8;id=960632;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=986327;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0006240410730242729, 'model_time': 1.3120542988181114, 'learning_rate':   +  9.896680093864611e-05, 'epoch': 9.08})   +04/17 [04:57:21] INFO  | >> Step 57700, Loss: {'action_dit_loss': 0.020560014992952347, 'mse_score': 0.0021461062133312225, ]8;id=229772;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=140057;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003200685605406761, 'model_time': 1.9317791629582644, 'learning_rate':   +  9.896288291265333e-05, 'epoch': 9.1})   +04/17 [05:01:38] INFO  | >> Step 57800, Loss: {'action_dit_loss': 0.01659730263054371, 'mse_score': 0.0037185041499989374, ]8;id=635163;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=391774;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004692644812166691, 'model_time': 6.254156379029155, 'learning_rate':   +  9.895895755300963e-05, 'epoch': 9.11})   +04/17 [05:05:44] INFO  | >> Step 57900, Loss: {'action_dit_loss': 0.028268352150917053, 'mse_score': 0.004803257861307689, ]8;id=493699;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=794139;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.011907857842743397, 'model_time': 1.3487679418176413, 'learning_rate':   +  9.895502486032803e-05, 'epoch': 9.13})   +04/17 [05:09:51] INFO  | >> Step 58000, Loss: {'action_dit_loss': 0.01932479813694954, 'mse_score': 0.0013168222670044219, ]8;id=229021;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=798867;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00032506417483091354, 'model_time': 1.8758216360583901, 'learning_rate':   +  9.895108483522268e-05, 'epoch': 9.15})   +04/17 [05:14:08] INFO  | >> Step 58100, Loss: {'action_dit_loss': 0.02114894799888134, 'mse_score': 0.0014992080894964083, ]8;id=915548;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=825618;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0006161639466881752, 'model_time': 4.635331533849239, 'learning_rate':   +  9.89471374783088e-05, 'epoch': 9.16})   +04/17 [05:18:12] INFO  | >> Step 58200, Loss: {'action_dit_loss': 0.02397383563220501, 'mse_score': 0.002077110377805574, ]8;id=737952;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=379358;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004564004950225353, 'model_time': 1.3321130936965346, 'learning_rate':   +  9.894318279020282e-05, 'epoch': 9.18})   +04/17 [05:22:16] INFO  | >> Step 58300, Loss: {'action_dit_loss': 0.015759266912937164, 'mse_score': 0.0013003760416592871, ]8;id=64758;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=869032;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.013217482715845108, 'model_time': 1.922318808734417, 'learning_rate':   +  9.89392207715223e-05, 'epoch': 9.19})   +04/17 [05:26:22] INFO  | >> Step 58400, Loss: {'action_dit_loss': 0.024765755981206894, 'mse_score': 0.0014691795887691633, ]8;id=600521;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=562728;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003425152972340584, 'model_time': 1.6993052419275045, 'learning_rate':   +  9.893525142288593e-05, 'epoch': 9.21})   +04/17 [05:30:40] INFO  | >> Step 58500, Loss: {'action_dit_loss': 0.019596602767705917, 'mse_score': 0.0014007570488112314, ]8;id=545617;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=463303;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0009548366069793701, 'model_time': 1.3132319198921323, 'learning_rate':   +  9.893127474491359e-05, 'epoch': 9.22})   +04/17 [05:34:46] INFO  | >> Step 58600, Loss: {'action_dit_loss': 0.020949674770236015, 'mse_score': 0.003843065085155623, ]8;id=611474;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=512573;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004435879178345203, 'model_time': 1.9442998049780726, 'learning_rate':   +  9.892729073822624e-05, 'epoch': 9.24})   +04/17 [05:38:53] INFO  | >> Step 58700, Loss: {'action_dit_loss': 0.017407841980457306, 'mse_score': 0.0016910174329366004, ]8;id=847975;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=58338;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.012097067199647427, 'model_time': 1.7049381472170353, 'learning_rate':   +  9.892329940344603e-05, 'epoch': 9.26})   +04/17 [05:43:09] INFO  | >> Step 58800, Loss: {'action_dit_loss': 0.02007771097123623, 'mse_score': 0.002925143444112369, ]8;id=478987;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=591303;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002730051055550575, 'model_time': 1.345305754803121, 'learning_rate':   +  9.891930074119623e-05, 'epoch': 9.27})   +04/17 [05:47:16] INFO  | >> Step 58900, Loss: {'action_dit_loss': 0.02237843908369541, 'mse_score': 0.001373150385916233, ]8;id=846112;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=323139;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003067348152399063, 'model_time': 1.8916665762662888, 'learning_rate':   +  9.891529475210128e-05, 'epoch': 9.29})   +04/17 [05:51:23] INFO  | >> Step 59000, Loss: {'action_dit_loss': 0.02188701368868351, 'mse_score': 0.003441937267780304, ]8;id=856113;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=3161;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.005008745938539505, 'model_time': 1.7492559663951397, 'learning_rate':   +  9.891128143678675e-05, 'epoch': 9.3})   +04/17 [05:55:39] INFO  | >> Step 59100, Loss: {'action_dit_loss': 0.018771952018141747, 'mse_score': 0.0026761825595583233, ]8;id=47489;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=444278;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.012243123725056648, 'model_time': 1.3075798004865646, 'learning_rate':   +  9.890726079587932e-05, 'epoch': 9.32})   +04/17 [05:59:46] INFO  | >> Step 59200, Loss: {'action_dit_loss': 0.023618290200829506, 'mse_score': 0.00264667347073555, ]8;id=63182;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=979981;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002755839377641678, 'model_time': 1.9252827325835824, 'learning_rate':   +  9.89032328300069e-05, 'epoch': 9.33})   +04/17 [06:03:52] INFO  | >> Step 59300, Loss: {'action_dit_loss': 0.024019740521907806, 'mse_score': 0.003292543813586235, ]8;id=33276;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=301036;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0005595171824097633, 'model_time': 1.6905055698007345, 'learning_rate':   +  9.889919753979845e-05, 'epoch': 9.35})   +04/17 [06:08:09] INFO  | >> Step 59400, Loss: {'action_dit_loss': 0.024071235209703445, 'mse_score': 0.0029480744685445514, ]8;id=803028;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=672687;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004277067258954048, 'model_time': 1.3603820307180285, 'learning_rate':   +  9.889515492588413e-05, 'epoch': 9.37})   +04/17 [06:12:16] INFO  | >> Step 59500, Loss: {'action_dit_loss': 0.022059069946408272, 'mse_score': 0.0032194184937647413, ]8;id=934631;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=401058;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.01186408568173647, 'model_time': 1.9034466231241822, 'learning_rate':   +  9.889110498889522e-05, 'epoch': 9.38})   +04/17 [06:16:23] INFO  | >> Step 59600, Loss: {'action_dit_loss': 0.016516590490937233, 'mse_score': 0.004860713545765195, ]8;id=395833;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=393892;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0006397105753421783, 'model_time': 1.7298287339508533, 'learning_rate':   +  9.888704772946417e-05, 'epoch': 9.4})   +04/17 [06:20:40] INFO  | >> Step 59700, Loss: {'action_dit_loss': 0.015870671719312668, 'mse_score': 0.0013572376753602708, ]8;id=565497;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=139449;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.000390482135117054, 'model_time': 1.3230038667097688, 'learning_rate':   +  9.888298314822453e-05, 'epoch': 9.41})   +04/17 [06:24:46] INFO  | >> Step 59800, Loss: {'action_dit_loss': 0.011408335529267788, 'mse_score': 0.001011370015995843, ]8;id=187143;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=563356;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004832142032682896, 'model_time': 1.8686208743602037, 'learning_rate':   +  9.887891124581104e-05, 'epoch': 9.43})   +04/17 [06:28:54] INFO  | >> Step 59900, Loss: {'action_dit_loss': 0.020212164148688316, 'mse_score': 0.003338578822357314, ]8;id=233507;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=875373;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.012824692763388157, 'model_time': 1.7223400296643376, 'learning_rate':   +  9.887483202285955e-05, 'epoch': 9.44})   +04/17 [06:33:09] INFO  | >> Step 60000, Loss: {'action_dit_loss': 0.016377003863453865, 'mse_score': 0.0011905812259231294, ]8;id=485494;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=706215;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0004961239174008369, 'model_time': 1.3340780809521675, 'learning_rate':   +  9.887074548000705e-05, 'epoch': 9.46})   +✅ Checkpoint saved at ./results/Checkpoints/0415_libero4in1_WanOFT/checkpoints/steps_60000 +04/17 [06:33:48] INFO  | >> 📊 Saving accessed configuration... ]8;id=397700;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=863355;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#238\238]8;;\ +  INFO  | >> 📦 Saving full merged configuration to ]8;id=162656;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=289039;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#242\242]8;;\ +  `results/Checkpoints/0415_libero4in1_WanOFT/config.full.yaml`...   +  INFO  | >> ✅ Configuration files saved ]8;id=802674;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=118326;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#244\244]8;;\ +04/17 [06:38:02] INFO  | >> Step 60100, Loss: {'action_dit_loss': 0.014222029596567154, 'mse_score': 0.0026731155812740326, ]8;id=644793;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=803265;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00023625977337360382, 'model_time': 7.413697154261172, 'learning_rate':   +  9.886665161789172e-05, 'epoch': 9.48})   +04/17 [06:42:13] INFO  | >> Step 60200, Loss: {'action_dit_loss': 0.023683378472924232, 'mse_score': 0.0015919881739786693, ]8;id=252356;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=216092;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004732510074973106, 'model_time': 1.7320037428289652, 'learning_rate':   +  9.886255043715285e-05, 'epoch': 9.49})   +04/17 [06:46:19] INFO  | >> Step 60300, Loss: {'action_dit_loss': 0.022829586640000343, 'mse_score': 0.0020801997078316553, ]8;id=468127;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=626822;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.01343446969985962, 'model_time': 1.3626563474535942, 'learning_rate':   +  9.885844193843085e-05, 'epoch': 9.51})   +04/17 [06:50:33] INFO  | >> Step 60400, Loss: {'action_dit_loss': 0.01773836277425289, 'mse_score': 0.0017169336123125894, ]8;id=256622;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=776513;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0007401993498206139, 'model_time': 8.381197981536388, 'learning_rate':   +  9.885432612236731e-05, 'epoch': 9.52})   +04/17 [06:54:43] INFO  | >> Step 60500, Loss: {'action_dit_loss': 0.020782945677638054, 'mse_score': 0.0023427757301500867, ]8;id=565979;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=227823;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002888888120651245, 'model_time': 1.7432318003848195, 'learning_rate':   +  9.885020298960495e-05, 'epoch': 9.54})   +04/17 [06:58:49] INFO  | >> Step 60600, Loss: {'action_dit_loss': 0.029130881652235985, 'mse_score': 0.0016170676265444075, ]8;id=146942;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=528373;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004461940377950668, 'model_time': 1.3495625564828515, 'learning_rate':   +  9.884607254078762e-05, 'epoch': 9.56})   +04/17 [07:03:03] INFO  | >> Step 60700, Loss: {'action_dit_loss': 0.015822533518075943, 'mse_score': 0.0016987245263797896, ]8;id=767051;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=604095;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.011819180101156235, 'model_time': 8.725967101752758, 'learning_rate':   +  9.884193477656035e-05, 'epoch': 9.57})   +04/17 [07:07:13] INFO  | >> Step 60800, Loss: {'action_dit_loss': 0.015038174577057362, 'mse_score': 0.0018902930564114026, ]8;id=705200;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=858136;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00031838566064834595, 'model_time': 1.7516195513308048, 'learning_rate':   +  9.883778969756928e-05, 'epoch': 9.59})   +04/17 [07:11:19] INFO  | >> Step 60900, Loss: {'action_dit_loss': 0.021212970837950706, 'mse_score': 0.002545560843178204, ]8;id=150219;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=692282;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0010606292635202408, 'model_time': 1.3159825587645173, 'learning_rate':   +  9.883363730446167e-05, 'epoch': 9.6})   +04/17 [07:15:33] INFO  | >> Step 61000, Loss: {'action_dit_loss': 0.021706299856305122, 'mse_score': 0.0035131975476230893, ]8;id=288519;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=63918;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004858477972447872, 'model_time': 8.55535585153848, 'learning_rate':   +  9.882947759788597e-05, 'epoch': 9.62})   +04/17 [07:19:43] INFO  | >> Step 61100, Loss: {'action_dit_loss': 0.02502010203897953, 'mse_score': 0.0018094039655157498, ]8;id=770925;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=955858;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.011773614212870598, 'model_time': 1.6890315860509872, 'learning_rate':   +  9.882531057849176e-05, 'epoch': 9.63})   +04/17 [07:23:49] INFO  | >> Step 61200, Loss: {'action_dit_loss': 0.0216169785708189, 'mse_score': 0.0015917115711740085, ]8;id=582851;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=519696;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00033729802817106247, 'model_time': 1.3198085771873593, 'learning_rate':   +  9.882113624692976e-05, 'epoch': 9.65})   +04/17 [07:28:02] INFO  | >> Step 61300, Loss: {'action_dit_loss': 0.017170153558254242, 'mse_score': 0.0027100414569888797, ]8;id=703953;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=399669;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002454221248626709, 'model_time': 8.177986120805144, 'learning_rate':   +  9.881695460385181e-05, 'epoch': 9.67})   +04/17 [07:32:13] INFO  | >> Step 61400, Loss: {'action_dit_loss': 0.01586480438709259, 'mse_score': 0.0025382153689861298, ]8;id=436548;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=428090;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.005205738358199596, 'model_time': 1.7434398969635367, 'learning_rate':   +  9.881276564991092e-05, 'epoch': 9.68})   +04/17 [07:36:19] INFO  | >> Step 61500, Loss: {'action_dit_loss': 0.02196025475859642, 'mse_score': 0.002879442647099495, ]8;id=791062;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=564058;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.012526530772447586, 'model_time': 1.2948099207133055, 'learning_rate':   +  9.880856938576123e-05, 'epoch': 9.7})   +04/17 [07:40:33] INFO  | >> Step 61600, Loss: {'action_dit_loss': 0.01587522402405739, 'mse_score': 0.0037580757801021847, ]8;id=315344;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=899197;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00029164738953113556, 'model_time': 8.506187155842781, 'learning_rate':   +  9.880436581205801e-05, 'epoch': 9.71})   +04/17 [07:44:43] INFO  | >> Step 61700, Loss: {'action_dit_loss': 0.025827936828136444, 'mse_score': 0.0011199191212654114, ]8;id=959175;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=60423;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0006775213405489922, 'model_time': 1.7286866419017315, 'learning_rate':   +  9.88001549294577e-05, 'epoch': 9.73})   +04/17 [07:48:49] INFO  | >> Step 61800, Loss: {'action_dit_loss': 0.020298434421420097, 'mse_score': 0.001373530232480594, ]8;id=555736;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=140606;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.005030499771237373, 'model_time': 1.377591478638351, 'learning_rate':   +  9.879593673861785e-05, 'epoch': 9.74})   +04/17 [07:53:03] INFO  | >> Step 61900, Loss: {'action_dit_loss': 0.012534124776721, 'mse_score': 0.0015729273270283426, ]8;id=346305;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=678120;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009564287029206753, 'model_time': 8.793931443244219, 'learning_rate':   +  9.879171124019719e-05, 'epoch': 9.76})   +04/17 [07:57:12] INFO  | >> Step 62000, Loss: {'action_dit_loss': 0.02072560228407383, 'mse_score': 0.0008464059792459011, ]8;id=389102;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=96955;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004793325439095497, 'model_time': 1.6791264517232776, 'learning_rate':   +  9.878747843485552e-05, 'epoch': 9.78})   +04/17 [08:01:20] INFO  | >> Step 62100, Loss: {'action_dit_loss': 0.01749594323337078, 'mse_score': 0.0028779607798371997, ]8;id=54040;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=281502;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0009139850735664368, 'model_time': 1.3011950319632888, 'learning_rate':   +  9.878323832325389e-05, 'epoch': 9.79})   +04/17 [08:05:33] INFO  | >> Step 62200, Loss: {'action_dit_loss': 0.01826968789100647, 'mse_score': 0.0015938208837594306, ]8;id=41468;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=916057;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004585123620927334, 'model_time': 8.627146933227777, 'learning_rate':   +  9.877899090605438e-05, 'epoch': 9.81})   +04/17 [08:09:42] INFO  | >> Step 62300, Loss: {'action_dit_loss': 0.01494005136191845, 'mse_score': 0.001205032957451684, ]8;id=616126;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=759489;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007950836792588234, 'model_time': 1.6964572248980403, 'learning_rate':   +  9.877473618392029e-05, 'epoch': 9.82})   +04/17 [08:13:49] INFO  | >> Step 62400, Loss: {'action_dit_loss': 0.013794951140880585, 'mse_score': 0.001438012080533164, ]8;id=219036;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=911709;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004423194564878941, 'model_time': 1.351631734520197, 'learning_rate':   +  9.8770474157516e-05, 'epoch': 9.84})   +04/17 [08:18:03] INFO  | >> Step 62500, Loss: {'action_dit_loss': 0.024180816486477852, 'mse_score': 0.0011256126953022821, ]8;id=16078;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=222096;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.000775420106947422, 'model_time': 8.83145194966346, 'learning_rate':   +  9.87662048275071e-05, 'epoch': 9.85})   +04/17 [08:22:13] INFO  | >> Step 62600, Loss: {'action_dit_loss': 0.021663513034582138, 'mse_score': 0.0015485852158495358, ]8;id=783159;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=790973;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0048325927928090096, 'model_time': 1.672341225668788, 'learning_rate':   +  9.876192819456026e-05, 'epoch': 9.87})   +04/17 [08:26:19] INFO  | >> Step 62700, Loss: {'action_dit_loss': 0.019430948421359062, 'mse_score': 0.0012075556442141533, ]8;id=633760;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=737954;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008977354504168034, 'model_time': 1.3115541469305754, 'learning_rate':   +  9.875764425934332e-05, 'epoch': 9.89})   +04/17 [08:30:39] INFO  | >> Step 62800, Loss: {'action_dit_loss': 0.017786094918847084, 'mse_score': 0.0008997083641588688, ]8;id=578897;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=337237;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004239351488649845, 'model_time': 5.863404844887555, 'learning_rate':   +  9.875335302252522e-05, 'epoch': 9.9})   +04/17 [08:34:43] INFO  | >> Step 62900, Loss: {'action_dit_loss': 0.020252978429198265, 'mse_score': 0.0013686665999037878, ]8;id=559572;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=680233;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008678589016199112, 'model_time': 1.6445586625486612, 'learning_rate':   +  9.874905448477613e-05, 'epoch': 9.92})   +04/17 [08:38:49] INFO  | >> Step 63000, Loss: {'action_dit_loss': 0.03451709821820259, 'mse_score': 0.0011609562539628574, ]8;id=537727;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=925695;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003597484901547432, 'model_time': 1.3357210736721754, 'learning_rate':   +  9.874474864676726e-05, 'epoch': 9.93})   +04/17 [08:43:02] INFO  | >> Step 63100, Loss: {'action_dit_loss': 0.025179008021950722, 'mse_score': 0.0025943762489727567, ]8;id=757505;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=492296;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004927994683384895, 'model_time': 7.643239326775074, 'learning_rate':   +  9.874043550917101e-05, 'epoch': 9.95})   +04/17 [08:47:13] INFO  | >> Step 63200, Loss: {'action_dit_loss': 0.018633946776390076, 'mse_score': 0.001762282502438341, ]8;id=212994;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=388712;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004820453003048897, 'model_time': 1.7574317129328847, 'learning_rate':   +  9.873611507266094e-05, 'epoch': 9.97})   +04/17 [08:51:19] INFO  | >> Step 63300, Loss: {'action_dit_loss': 0.018965575844049454, 'mse_score': 0.0017393881987248147, ]8;id=906058;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=232022;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008411125279963017, 'model_time': 1.407003411091864, 'learning_rate':   +  9.873178733791169e-05, 'epoch': 9.98})   +04/17 [08:55:32] INFO  | >> Step 63400, Loss: {'action_dit_loss': 0.02472885325551033, 'mse_score': 0.0013567243835755757, ]8;id=580189;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=980165;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00032521411776542664, 'model_time': 8.16653312370181, 'learning_rate':   +  9.87274523055991e-05, 'epoch': 10.0})   +04/17 [08:59:43] INFO  | >> Step 63500, Loss: {'action_dit_loss': 0.01737116277217865, 'mse_score': 0.001341585602079119, ]8;id=309531;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=159814;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004412388429045677, 'model_time': 1.6839311020448804, 'learning_rate':   +  9.87231099764001e-05, 'epoch': 10.01})   +04/17 [09:03:49] INFO  | >> Step 63600, Loss: {'action_dit_loss': 0.015770744532346725, 'mse_score': 0.0013049801013299397, ]8;id=597467;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=873844;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004469679668545723, 'model_time': 1.3393349964171648, 'learning_rate':   +  9.871876035099277e-05, 'epoch': 10.03})   +04/17 [09:08:02] INFO  | >> Step 63700, Loss: {'action_dit_loss': 0.016530921682715416, 'mse_score': 0.0013377838102834566, ]8;id=989294;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=718113;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.007833223789930344, 'model_time': 7.989783335477114, 'learning_rate':   +  9.871440343005637e-05, 'epoch': 10.04})   +04/17 [09:12:13] INFO  | >> Step 63800, Loss: {'action_dit_loss': 0.019177842885255814, 'mse_score': 0.002475507291299956, ]8;id=512356;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=758705;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00038513634353876114, 'model_time': 1.682078338228166, 'learning_rate':   +  9.871003921427126e-05, 'epoch': 10.06})   +04/17 [09:16:19] INFO  | >> Step 63900, Loss: {'action_dit_loss': 0.020816797390580177, 'mse_score': 0.001387454303247588, ]8;id=176405;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=768367;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0063750240951776505, 'model_time': 1.3614553213119507, 'learning_rate':   +  9.870566770431894e-05, 'epoch': 10.08})   +04/17 [09:20:32] INFO  | >> Step 64000, Loss: {'action_dit_loss': 0.020383616909384727, 'mse_score': 0.002391357773116657, ]8;id=755303;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=573095;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0049827080219984055, 'model_time': 8.05451148469001, 'learning_rate':   +  9.870128890088209e-05, 'epoch': 10.09})   +04/17 [09:24:43] INFO  | >> Step 64100, Loss: {'action_dit_loss': 0.01538911648094654, 'mse_score': 0.004302314083491053, ]8;id=568471;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=672985;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008424111641943455, 'model_time': 1.8365376871079206, 'learning_rate':   +  9.869690280464444e-05, 'epoch': 10.11})   +04/17 [09:28:50] INFO  | >> Step 64200, Loss: {'action_dit_loss': 0.01613755337893963, 'mse_score': 0.0018653362723333494, ]8;id=887826;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=77941;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0007626311853528023, 'model_time': 1.3065017368644476, 'learning_rate':   +  9.869250941629095e-05, 'epoch': 10.12})   +04/17 [09:33:03] INFO  | >> Step 64300, Loss: {'action_dit_loss': 0.021114371716976166, 'mse_score': 0.0013700215412037714, ]8;id=801467;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=6693;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004919658415019512, 'model_time': 8.428709694184363, 'learning_rate':   +  9.868810873650771e-05, 'epoch': 10.14})   +04/17 [09:37:13] INFO  | >> Step 64400, Loss: {'action_dit_loss': 0.022277195006608963, 'mse_score': 0.002094380557537079, ]8;id=242675;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=71269;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0038853036239743233, 'model_time': 1.7194583909586072, 'learning_rate':   +  9.86837007659819e-05, 'epoch': 10.15})   +04/17 [09:41:19] INFO  | >> Step 64500, Loss: {'action_dit_loss': 0.025205066427588463, 'mse_score': 0.0029388091393879484, ]8;id=530299;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=478160;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.009824476204812527, 'model_time': 1.3433206528425217, 'learning_rate':   +  9.867928550540183e-05, 'epoch': 10.17})   +04/17 [09:45:34] INFO  | >> Step 64600, Loss: {'action_dit_loss': 0.025717975571751595, 'mse_score': 0.0026180395590407507, ]8;id=699143;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=979269;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0002683298662304878, 'model_time': 8.943240392953157, 'learning_rate':   +  9.867486295545701e-05, 'epoch': 10.19})   +04/17 [09:49:43] INFO  | >> Step 64700, Loss: {'action_dit_loss': 0.017894310876727104, 'mse_score': 0.0010305349715054035, ]8;id=511552;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=16495;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004623539745807648, 'model_time': 1.707870160229504, 'learning_rate':   +  9.867043311683808e-05, 'epoch': 10.2})   +04/17 [09:53:48] INFO  | >> Step 64800, Loss: {'action_dit_loss': 0.014905331656336784, 'mse_score': 0.0012553783931902476, ]8;id=12426;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=17538;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0045039840042591095, 'model_time': 1.3237791182473302, 'learning_rate':   +  9.866599599023676e-05, 'epoch': 10.22})   +04/17 [09:58:02] INFO  | >> Step 64900, Loss: {'action_dit_loss': 0.018399899825453758, 'mse_score': 0.002649780096752303, ]8;id=300614;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=17975;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008553843945264816, 'model_time': 8.253332979045808, 'learning_rate':   +  9.866155157634595e-05, 'epoch': 10.23})   +04/17 [10:02:13] INFO  | >> Step 65000, Loss: {'action_dit_loss': 0.018441636115312576, 'mse_score': 0.0012242366958941733, ]8;id=451488;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=845328;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00041152816265821457, 'model_time': 1.713347563520074, 'learning_rate':   +  9.865709987585973e-05, 'epoch': 10.25})   +04/17 [10:06:19] INFO  | >> Step 65100, Loss: {'action_dit_loss': 0.026503631845116615, 'mse_score': 0.001967733326767172, ]8;id=962643;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=100992;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004764329642057419, 'model_time': 1.3049269868060946, 'learning_rate':   +  9.865264088947321e-05, 'epoch': 10.26})   +04/17 [10:10:31] INFO  | >> Step 65200, Loss: {'action_dit_loss': 0.02182397060096264, 'mse_score': 0.0009178279766014644, ]8;id=649887;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=552029;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004075925797224045, 'model_time': 7.492158726789057, 'learning_rate':   +  9.86481746178827e-05, 'epoch': 10.28})   +04/17 [10:14:40] INFO  | >> Step 65300, Loss: {'action_dit_loss': 0.02461855858564377, 'mse_score': 0.0023771444601672037, ]8;id=833551;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=416176;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008010906167328358, 'model_time': 1.6953403893858194, 'learning_rate':   +  9.864370106178569e-05, 'epoch': 10.3})   +04/17 [10:18:44] INFO  | >> Step 65400, Loss: {'action_dit_loss': 0.016118204221129417, 'mse_score': 0.002004929818212986, ]8;id=592447;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=255021;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0003704456612467766, 'model_time': 1.3454821724444628, 'learning_rate':   +  9.863922022188075e-05, 'epoch': 10.31})   +04/17 [10:22:51] INFO  | >> Step 65500, Loss: {'action_dit_loss': 0.018499264493584633, 'mse_score': 0.002487647214106151, ]8;id=868286;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=889053;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.005984357558190823, 'model_time': 1.9106543557718396, 'learning_rate':   +  9.863473209886756e-05, 'epoch': 10.33})   +04/17 [10:27:07] INFO  | >> Step 65600, Loss: {'action_dit_loss': 0.020944299176335335, 'mse_score': 0.0010031257489962237, ]8;id=796483;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=33223;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004080587066709995, 'model_time': 5.8197065917775035, 'learning_rate':   +  9.863023669344704e-05, 'epoch': 10.34})   +04/17 [10:31:14] INFO  | >> Step 65700, Loss: {'action_dit_loss': 0.018103793263435364, 'mse_score': 0.0030061453580856323, ]8;id=579549;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=499127;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008717196062207222, 'model_time': 1.3298105066642165, 'learning_rate':   +  9.862573400632114e-05, 'epoch': 10.36})   +04/17 [10:35:21] INFO  | >> Step 65800, Loss: {'action_dit_loss': 0.01542181521654129, 'mse_score': 0.0012069416365453175, ]8;id=179708;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=86702;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.000317990779876709, 'model_time': 1.9630331732332706, 'learning_rate':   +  9.862122403819302e-05, 'epoch': 10.38})   +04/17 [10:39:38] INFO  | >> Step 65900, Loss: {'action_dit_loss': 0.02682214230298996, 'mse_score': 0.0013477570776428496, ]8;id=822478;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=347362;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004457109607756138, 'model_time': 5.541346346028149, 'learning_rate':   +  9.861670678976692e-05, 'epoch': 10.39})   +04/17 [10:43:45] INFO  | >> Step 66000, Loss: {'action_dit_loss': 0.016636742278933525, 'mse_score': 0.0025239496358803342, ]8;id=553815;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=963800;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.005005156621336937, 'model_time': 1.3467795830219984, 'learning_rate':   +  9.861218226174828e-05, 'epoch': 10.41})   +04/17 [10:47:51] INFO  | >> Step 66100, Loss: {'action_dit_loss': 0.023797716945409775, 'mse_score': 0.0015273832583001681, ]8;id=910286;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=725916;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008842531591653824, 'model_time': 1.9456458557397127, 'learning_rate':   +  9.860765045484362e-05, 'epoch': 10.42})   +04/17 [10:52:08] INFO  | >> Step 66200, Loss: {'action_dit_loss': 0.01732267439365387, 'mse_score': 0.002575770818761417, ]8;id=48823;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=969051;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00039146002382040024, 'model_time': 5.8134304555132985, 'learning_rate':   +  9.860311136976061e-05, 'epoch': 10.44})   +04/17 [10:56:14] INFO  | >> Step 66300, Loss: {'action_dit_loss': 0.027327900752425194, 'mse_score': 0.0013550488012177603, ]8;id=942996;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=569408;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004807690158486366, 'model_time': 1.3042436288669705, 'learning_rate':   +  9.859856500720813e-05, 'epoch': 10.45})   +04/17 [11:00:22] INFO  | >> Step 66400, Loss: {'action_dit_loss': 0.028732530772686005, 'mse_score': 0.0013121220150164195, ]8;id=973882;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=891737;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00462851207703352, 'model_time': 1.9698354909196496, 'learning_rate':   +  9.859401136789604e-05, 'epoch': 10.47})   +04/17 [11:04:38] INFO  | >> Step 66500, Loss: {'action_dit_loss': 0.014846637845039368, 'mse_score': 0.003063572570681572, ]8;id=151195;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=788795;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.010862788185477257, 'model_time': 4.604443497955799, 'learning_rate':   +  9.858945045253549e-05, 'epoch': 10.49})   +04/17 [11:08:44] INFO  | >> Step 66600, Loss: {'action_dit_loss': 0.024824317544698715, 'mse_score': 0.0009918612028871263, ]8;id=973995;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=80674;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00023568887263536453, 'model_time': 1.3929723361507058, 'learning_rate':   +  9.85848822618387e-05, 'epoch': 10.5})   +04/17 [11:12:51] INFO  | >> Step 66700, Loss: {'action_dit_loss': 0.01795995607972145, 'mse_score': 0.0011132215149700642, ]8;id=594223;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=875194;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00428333505988121, 'model_time': 1.9491146057844162, 'learning_rate':   +  9.858030679651901e-05, 'epoch': 10.52})   +04/17 [11:17:08] INFO  | >> Step 66800, Loss: {'action_dit_loss': 0.015932433307170868, 'mse_score': 0.0012040437598313605, ]8;id=566820;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=347843;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004680116660892963, 'model_time': 5.047028427943587, 'learning_rate':   +  9.857572405729095e-05, 'epoch': 10.53})   +04/17 [11:21:15] INFO  | >> Step 66900, Loss: {'action_dit_loss': 0.01828598976135254, 'mse_score': 0.0033574657780783518, ]8;id=828897;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=722794;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.01097550243139267, 'model_time': 1.340281187556684, 'learning_rate':   +  9.857113404487012e-05, 'epoch': 10.55})   +04/17 [11:25:21] INFO  | >> Step 67000, Loss: {'action_dit_loss': 0.015230859629809856, 'mse_score': 0.0025220531970262527, ]8;id=362659;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=56304;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00035767629742622375, 'model_time': 1.919157368130982, 'learning_rate':   +  9.856653675997333e-05, 'epoch': 10.56})   +04/17 [11:29:38] INFO  | >> Step 67100, Loss: {'action_dit_loss': 0.02064521238207817, 'mse_score': 0.0013037326612642833, ]8;id=79710;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=357137;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.0045883916318416595, 'model_time': 6.242886405438185, 'learning_rate':   +  9.856193220331842e-05, 'epoch': 10.58})   +04/17 [11:33:45] INFO  | >> Step 67200, Loss: {'action_dit_loss': 0.02336304448544979, 'mse_score': 0.001134888269007206, ]8;id=415973;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=811131;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004393366165459156, 'model_time': 1.4400842720642686, 'learning_rate':   +  9.855732037562448e-05, 'epoch': 10.6})   +04/17 [11:37:51] INFO  | >> Step 67300, Loss: {'action_dit_loss': 0.018415875732898712, 'mse_score': 0.0026746985635587145, ]8;id=821609;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=472436;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008338594809174538, 'model_time': 2.034493776038289, 'learning_rate':   +  9.855270127761169e-05, 'epoch': 10.61})   +04/17 [11:42:08] INFO  | >> Step 67400, Loss: {'action_dit_loss': 0.019436249509453773, 'mse_score': 0.0018960095143743924, ]8;id=986859;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=393663;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.00035661179572343826, 'model_time': 5.626687983050942, 'learning_rate':   +  9.854807491000133e-05, 'epoch': 10.63})   +04/17 [11:46:14] INFO  | >> Step 67500, Loss: {'action_dit_loss': 0.01774800755083561, 'mse_score': 0.002714761399797031, ]8;id=692764;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=398535;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004599256440997124, 'model_time': 1.3668240793049335, 'learning_rate':   +  9.854344127351586e-05, 'epoch': 10.64})   +04/17 [11:50:21] INFO  | >> Step 67600, Loss: {'action_dit_loss': 0.021529829129576683, 'mse_score': 0.0025747868099382947, ]8;id=836821;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=258421;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.004639214836061001, 'model_time': 1.9087118608877063, 'learning_rate':   +  9.853880036887886e-05, 'epoch': 10.66})   +04/17 [11:54:36] INFO  | >> Step 67700, Loss: {'action_dit_loss': 0.015544261783361435, 'mse_score': 0.0036240419639008386, ]8;id=161712;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=398458;file:///project/vonneumann1/jye624/Projcets/starVLA/starVLA/training/train_starvla.py#254\254]8;;\ +  'data_time': 0.008363479748368263, 'model_time': 6.195423766039312, 'learning_rate':   +  9.853415219681506e-05, 'epoch': 10.67})