--- library_name: transformers base_model: Arthur-Tsai/histv4_pretrain_tssp-smlm tags: - generated_from_trainer metrics: - accuracy model-index: - name: histv4_ftis_pretrain_tssp-smlm_0329 results: [] --- # histv4_ftis_pretrain_tssp-smlm_0329 This model is a fine-tuned version of [Arthur-Tsai/histv4_pretrain_tssp-smlm](https://huggingface.co/Arthur-Tsai/histv4_pretrain_tssp-smlm) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.6648 - Accuracy: 0.9701 - Macro F1: 0.9279 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 8 - eval_batch_size: 4 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 6733 - training_steps: 134675 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 | |:-------------:|:--------:|:-----:|:---------------:|:--------:|:--------:| | 6.1814 | 0.0050 | 673 | 5.5662 | 0.5889 | 0.1547 | | 3.493 | 1.0050 | 1346 | 2.8356 | 0.6560 | 0.2007 | | 2.2738 | 2.0050 | 2019 | 2.0311 | 0.7206 | 0.2727 | | 1.8894 | 3.0050 | 2692 | 1.6718 | 0.7628 | 0.3672 | | 1.5981 | 4.0050 | 3365 | 1.4073 | 0.8069 | 0.4541 | | 1.4813 | 5.0050 | 4038 | 1.2843 | 0.8245 | 0.5214 | | 1.2253 | 6.0050 | 4711 | 1.0820 | 0.8590 | 0.5802 | | 1.1132 | 7.0049 | 5384 | 1.0108 | 0.8738 | 0.6193 | | 1.0131 | 8.0049 | 6057 | 0.9750 | 0.8674 | 0.6359 | | 0.924 | 9.0049 | 6730 | 0.8751 | 0.8956 | 0.6899 | | 0.8099 | 10.0049 | 7403 | 0.7859 | 0.9042 | 0.6947 | | 0.7125 | 11.0049 | 8076 | 0.7251 | 0.9188 | 0.7355 | | 0.7119 | 12.0049 | 8749 | 0.6956 | 0.9247 | 0.7625 | | 0.657 | 13.0049 | 9422 | 0.6414 | 0.9327 | 0.7860 | | 0.6067 | 14.0049 | 10095 | 0.6120 | 0.9409 | 0.8006 | | 0.6006 | 15.0049 | 10768 | 0.5977 | 0.9408 | 0.8023 | | 0.5399 | 16.0049 | 11441 | 0.6003 | 0.9448 | 0.8254 | | 0.4939 | 17.0049 | 12114 | 0.6105 | 0.9439 | 0.8215 | | 0.5075 | 18.0049 | 12787 | 0.5745 | 0.9483 | 0.8326 | | 0.4736 | 19.0049 | 13460 | 0.5954 | 0.9501 | 0.8352 | | 0.4643 | 20.0048 | 14133 | 0.5645 | 0.9522 | 0.8460 | | 0.4683 | 21.0048 | 14806 | 0.5745 | 0.9518 | 0.8533 | | 0.4654 | 22.0048 | 15479 | 0.5191 | 0.9573 | 0.8671 | | 0.4271 | 23.0048 | 16152 | 0.5669 | 0.9539 | 0.8525 | | 0.408 | 24.0048 | 16825 | 0.5903 | 0.9567 | 0.8668 | | 0.3991 | 25.0048 | 17498 | 0.5830 | 0.9580 | 0.8776 | | 0.3606 | 26.0048 | 18171 | 0.5854 | 0.9571 | 0.8759 | | 0.3948 | 27.0048 | 18844 | 0.5952 | 0.9583 | 0.8769 | | 0.3691 | 28.0048 | 19517 | 0.6049 | 0.9546 | 0.8726 | | 0.3651 | 29.0048 | 20190 | 0.6013 | 0.9597 | 0.8870 | | 0.3589 | 30.0048 | 20863 | 0.5842 | 0.9585 | 0.8801 | | 0.3601 | 31.0048 | 21536 | 0.5945 | 0.9593 | 0.8886 | | 0.3502 | 32.0048 | 22209 | 0.5607 | 0.9620 | 0.8935 | | 0.3693 | 33.0048 | 22882 | 0.6231 | 0.9635 | 0.8874 | | 0.3292 | 34.0047 | 23555 | 0.5569 | 0.9626 | 0.8892 | | 0.3451 | 35.0047 | 24228 | 0.5738 | 0.9652 | 0.8999 | | 0.3247 | 36.0047 | 24901 | 0.5274 | 0.9646 | 0.8876 | | 0.3214 | 37.0047 | 25574 | 0.5932 | 0.9639 | 0.8955 | | 0.3111 | 38.0047 | 26247 | 0.6105 | 0.9623 | 0.8991 | | 0.326 | 39.0047 | 26920 | 0.5824 | 0.9643 | 0.8998 | | 0.3243 | 40.0047 | 27593 | 0.6213 | 0.9633 | 0.9029 | | 0.3068 | 41.0047 | 28266 | 0.5972 | 0.9647 | 0.9026 | | 0.3022 | 42.0047 | 28939 | 0.5485 | 0.9660 | 0.9091 | | 0.3055 | 43.0047 | 29612 | 0.5928 | 0.9667 | 0.8992 | | 0.2979 | 44.0047 | 30285 | 0.6059 | 0.9645 | 0.9037 | | 0.301 | 45.0047 | 30958 | 0.5866 | 0.9661 | 0.9073 | | 0.3043 | 46.0047 | 31631 | 0.6022 | 0.9644 | 0.9019 | | 0.2982 | 47.0046 | 32304 | 0.5707 | 0.9675 | 0.9077 | | 0.2852 | 48.0046 | 32977 | 0.6089 | 0.9632 | 0.9036 | | 0.2967 | 49.0046 | 33650 | 0.6050 | 0.9657 | 0.8864 | | 0.297 | 50.0046 | 34323 | 0.6383 | 0.9638 | 0.9099 | | 0.2865 | 51.0046 | 34996 | 0.6180 | 0.9669 | 0.9101 | | 0.2992 | 52.0046 | 35669 | 0.5531 | 0.9645 | 0.9085 | | 0.2805 | 53.0046 | 36342 | 0.6031 | 0.9661 | 0.9055 | | 0.2839 | 54.0046 | 37015 | 0.6427 | 0.9639 | 0.9068 | | 0.2754 | 55.0046 | 37688 | 0.6178 | 0.9679 | 0.9135 | | 0.2818 | 56.0046 | 38361 | 0.6087 | 0.9667 | 0.9143 | | 0.2719 | 57.0046 | 39034 | 0.6322 | 0.9670 | 0.9051 | | 0.2768 | 58.0046 | 39707 | 0.6345 | 0.9677 | 0.9157 | | 0.2709 | 59.0046 | 40380 | 0.5874 | 0.9699 | 0.9189 | | 0.2836 | 60.0046 | 41053 | 0.5807 | 0.9685 | 0.9195 | | 0.2708 | 61.0045 | 41726 | 0.5494 | 0.9703 | 0.9196 | | 0.2669 | 62.0045 | 42399 | 0.6052 | 0.9665 | 0.9137 | | 0.2701 | 63.0045 | 43072 | 0.6167 | 0.9646 | 0.9113 | | 0.2659 | 64.0045 | 43745 | 0.5991 | 0.9689 | 0.9155 | | 0.2598 | 65.0045 | 44418 | 0.5505 | 0.9700 | 0.9157 | | 0.2701 | 66.0045 | 45091 | 0.5899 | 0.9688 | 0.9194 | | 0.2757 | 67.0045 | 45764 | 0.6226 | 0.9680 | 0.9167 | | 0.2728 | 68.0045 | 46437 | 0.5976 | 0.9677 | 0.9174 | | 0.2661 | 69.0045 | 47110 | 0.6157 | 0.9667 | 0.8972 | | 0.2646 | 70.0045 | 47783 | 0.6418 | 0.9657 | 0.9163 | | 0.2621 | 71.0045 | 48456 | 0.6507 | 0.9692 | 0.9189 | | 0.2628 | 72.0045 | 49129 | 0.6470 | 0.9660 | 0.9151 | | 0.2652 | 73.0045 | 49802 | 0.6170 | 0.9668 | 0.9205 | | 0.2604 | 74.0044 | 50475 | 0.6195 | 0.9697 | 0.9175 | | 0.2547 | 75.0044 | 51148 | 0.5727 | 0.9683 | 0.9215 | | 0.2639 | 76.0044 | 51821 | 0.6014 | 0.9694 | 0.9207 | | 0.2539 | 77.0044 | 52494 | 0.6089 | 0.9686 | 0.9161 | | 0.2586 | 78.0044 | 53167 | 0.6274 | 0.9688 | 0.9185 | | 0.258 | 79.0044 | 53840 | 0.6107 | 0.9694 | 0.9234 | | 0.2513 | 80.0044 | 54513 | 0.5746 | 0.9708 | 0.9223 | | 0.2593 | 81.0044 | 55186 | 0.5986 | 0.9686 | 0.9236 | | 0.2556 | 82.0044 | 55859 | 0.6483 | 0.9670 | 0.9232 | | 0.2542 | 83.0044 | 56532 | 0.6052 | 0.9666 | 0.9201 | | 0.2543 | 84.0044 | 57205 | 0.6558 | 0.9684 | 0.9230 | | 0.2541 | 85.0044 | 57878 | 0.6251 | 0.9669 | 0.9206 | | 0.2459 | 86.0044 | 58551 | 0.5984 | 0.9692 | 0.9224 | | 0.247 | 87.0044 | 59224 | 0.6171 | 0.9693 | 0.9261 | | 0.2477 | 88.0043 | 59897 | 0.6986 | 0.9679 | 0.9229 | | 0.2476 | 89.0043 | 60570 | 0.7201 | 0.9691 | 0.9246 | | 0.2447 | 90.0043 | 61243 | 0.6508 | 0.9693 | 0.9275 | | 0.2441 | 91.0043 | 61916 | 0.6397 | 0.9672 | 0.9204 | | 0.2446 | 92.0043 | 62589 | 0.6003 | 0.9683 | 0.9230 | | 0.2479 | 93.0043 | 63262 | 0.5893 | 0.9704 | 0.9240 | | 0.2508 | 94.0043 | 63935 | 0.5721 | 0.9689 | 0.9296 | | 0.2429 | 95.0043 | 64608 | 0.6701 | 0.9704 | 0.9291 | | 0.2415 | 96.0043 | 65281 | 0.5967 | 0.9695 | 0.9262 | | 0.245 | 97.0043 | 65954 | 0.6655 | 0.9711 | 0.9277 | | 0.2415 | 98.0043 | 66627 | 0.5518 | 0.9692 | 0.9240 | | 0.2414 | 99.0043 | 67300 | 0.6633 | 0.9691 | 0.9257 | | 0.2456 | 100.0043 | 67973 | 0.6249 | 0.9707 | 0.9305 | | 0.2386 | 101.0042 | 68646 | 0.5712 | 0.9699 | 0.9274 | | 0.2428 | 102.0042 | 69319 | 0.6618 | 0.9702 | 0.9296 | | 0.242 | 103.0042 | 69992 | 0.5995 | 0.9685 | 0.9248 | | 0.2353 | 104.0042 | 70665 | 0.6375 | 0.9706 | 0.9271 | | 0.242 | 105.0042 | 71338 | 0.6279 | 0.9710 | 0.9265 | | 0.2388 | 106.0042 | 72011 | 0.6067 | 0.9708 | 0.9346 | | 0.2375 | 107.0042 | 72684 | 0.6514 | 0.9713 | 0.9297 | | 0.2378 | 108.0042 | 73357 | 0.6535 | 0.9699 | 0.9246 | | 0.2341 | 109.0042 | 74030 | 0.6010 | 0.9710 | 0.9053 | | 0.2383 | 110.0042 | 74703 | 0.6420 | 0.9692 | 0.9271 | | 0.2418 | 111.0042 | 75376 | 0.5911 | 0.9724 | 0.9336 | | 0.2366 | 112.0042 | 76049 | 0.6536 | 0.9706 | 0.9234 | | 0.2388 | 113.0042 | 76722 | 0.6341 | 0.9693 | 0.9238 | | 0.2365 | 114.0042 | 77395 | 0.6533 | 0.9703 | 0.9260 | | 0.2346 | 115.0041 | 78068 | 0.5889 | 0.9712 | 0.9324 | | 0.2371 | 116.0041 | 78741 | 0.6251 | 0.9706 | 0.9295 | | 0.2367 | 117.0041 | 79414 | 0.5921 | 0.9706 | 0.9284 | | 0.2405 | 118.0041 | 80087 | 0.5847 | 0.9695 | 0.9314 | | 0.2357 | 119.0041 | 80760 | 0.6325 | 0.9706 | 0.9259 | | 0.2347 | 120.0041 | 81433 | 0.6381 | 0.9710 | 0.9276 | | 0.2369 | 121.0041 | 82106 | 0.6613 | 0.9696 | 0.9274 | | 0.2388 | 122.0041 | 82779 | 0.6684 | 0.9719 | 0.9309 | | 0.2327 | 123.0041 | 83452 | 0.6534 | 0.9703 | 0.9251 | | 0.2353 | 124.0041 | 84125 | 0.6549 | 0.9724 | 0.9321 | | 0.237 | 125.0041 | 84798 | 0.6008 | 0.9720 | 0.9334 | | 0.2353 | 126.0041 | 85471 | 0.6333 | 0.9706 | 0.9288 | ### Framework versions - Transformers 4.46.0 - Pytorch 2.3.1+cu121 - Datasets 2.20.0 - Tokenizers 0.20.1