--- library_name: transformers tags: - generated_from_trainer metrics: - accuracy model-index: - name: ht-finbert-cls-v5_ftis_noPretrain results: [] --- # ht-finbert-cls-v5_ftis_noPretrain This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 92.9445 - Accuracy: 0.8351 - Macro F1: 0.6489 ## 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: 6700 - training_steps: 134000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 | |:-------------:|:--------:|:-----:|:---------------:|:--------:|:--------:| | 47.3163 | 2.0002 | 100 | 30.8693 | 0.1303 | 0.0409 | | 18.3779 | 5.0002 | 200 | 73.9035 | 0.2042 | 0.0513 | | 8.2696 | 8.0002 | 300 | 147.5503 | 0.4564 | 0.1146 | | 6.7213 | 11.0002 | 400 | 171.8964 | 0.5408 | 0.1392 | | 6.132 | 14.0002 | 500 | 205.9964 | 0.5705 | 0.1495 | | 5.4198 | 17.0002 | 600 | 196.4142 | 0.5921 | 0.1633 | | 4.9322 | 20.0001 | 700 | 226.8508 | 0.6124 | 0.1847 | | 4.2859 | 23.0001 | 800 | 182.0064 | 0.6303 | 0.2069 | | 3.5424 | 26.0001 | 900 | 119.8234 | 0.6409 | 0.2184 | | 2.9893 | 29.0001 | 1000 | 94.5961 | 0.6575 | 0.2582 | | 2.388 | 32.0001 | 1100 | 67.4827 | 0.6717 | 0.2771 | | 1.9977 | 35.0001 | 1200 | 37.1315 | 0.6834 | 0.2970 | | 1.7116 | 38.0001 | 1300 | 23.7928 | 0.6906 | 0.3159 | | 1.5454 | 41.0000 | 1400 | 16.0731 | 0.7089 | 0.3520 | | 1.239 | 44.0000 | 1500 | 11.3044 | 0.7181 | 0.3888 | | 1.0348 | 47.0000 | 1600 | 8.7288 | 0.7154 | 0.3897 | | 0.9315 | 49.0003 | 1700 | 7.1351 | 0.7297 | 0.4125 | | 0.7517 | 52.0002 | 1800 | 5.4532 | 0.7377 | 0.4526 | | 0.6675 | 55.0002 | 1900 | 4.5291 | 0.7463 | 0.4581 | | 0.5866 | 58.0002 | 2000 | 4.1340 | 0.7497 | 0.4836 | | 0.5392 | 61.0002 | 2100 | 5.2211 | 0.7500 | 0.4725 | | 0.4744 | 64.0002 | 2200 | 4.0583 | 0.7573 | 0.4881 | | 0.4311 | 67.0002 | 2300 | 3.8780 | 0.7550 | 0.4983 | | 0.3422 | 70.0001 | 2400 | 4.1826 | 0.7612 | 0.5172 | | 0.3217 | 73.0001 | 2500 | 4.3735 | 0.7598 | 0.4986 | | 0.2984 | 76.0001 | 2600 | 3.9067 | 0.7668 | 0.5125 | | 0.2532 | 79.0001 | 2700 | 4.7464 | 0.7738 | 0.5218 | | 0.2438 | 82.0001 | 2800 | 5.1362 | 0.7645 | 0.5052 | | 0.2177 | 85.0001 | 2900 | 5.6936 | 0.7645 | 0.5229 | | 0.1968 | 88.0001 | 3000 | 5.4854 | 0.7752 | 0.5312 | | 0.1901 | 91.0000 | 3100 | 5.9959 | 0.7740 | 0.5294 | | 0.1645 | 94.0000 | 3200 | 7.4186 | 0.7812 | 0.5407 | | 0.1472 | 97.0000 | 3300 | 7.2000 | 0.7823 | 0.5439 | | 0.1409 | 99.0003 | 3400 | 8.4192 | 0.7740 | 0.5455 | | 0.1294 | 102.0002 | 3500 | 9.2161 | 0.7822 | 0.5527 | | 0.1213 | 105.0002 | 3600 | 10.7050 | 0.7800 | 0.5496 | | 0.1002 | 108.0002 | 3700 | 11.5795 | 0.7820 | 0.5526 | | 0.1016 | 111.0002 | 3800 | 12.5054 | 0.7788 | 0.5493 | | 0.0917 | 114.0002 | 3900 | 14.2625 | 0.7912 | 0.5581 | | 0.0871 | 117.0002 | 4000 | 16.3408 | 0.7845 | 0.5498 | | 0.0717 | 120.0001 | 4100 | 16.0609 | 0.7878 | 0.5545 | | 0.0711 | 123.0001 | 4200 | 15.5629 | 0.7920 | 0.5594 | | 0.0648 | 126.0001 | 4300 | 16.5698 | 0.7914 | 0.5558 | | 0.0625 | 129.0001 | 4400 | 17.8345 | 0.7899 | 0.5609 | | 0.0574 | 132.0001 | 4500 | 19.8641 | 0.7975 | 0.5593 | | 0.0584 | 135.0001 | 4600 | 20.1964 | 0.7913 | 0.5737 | | 0.0492 | 138.0001 | 4700 | 20.8334 | 0.7966 | 0.5695 | | 0.0485 | 141.0000 | 4800 | 18.2647 | 0.7973 | 0.5623 | | 0.0449 | 144.0000 | 4900 | 19.5311 | 0.8019 | 0.5760 | | 0.0403 | 147.0000 | 5000 | 16.6079 | 0.8009 | 0.5660 | | 0.042 | 149.0003 | 5100 | 19.8222 | 0.8000 | 0.5709 | | 0.049 | 152.0002 | 5200 | 15.4262 | 0.7929 | 0.5741 | | 0.0474 | 155.0002 | 5300 | 15.9017 | 0.7948 | 0.5733 | | 0.0492 | 158.0002 | 5400 | 16.0189 | 0.8028 | 0.5844 | | 0.0404 | 161.0002 | 5500 | 18.5286 | 0.7974 | 0.5851 | | 0.0297 | 164.0002 | 5600 | 20.1967 | 0.7979 | 0.5785 | | 0.0433 | 167.0002 | 5700 | 19.7008 | 0.8016 | 0.5811 | | 0.0367 | 170.0001 | 5800 | 25.0676 | 0.8015 | 0.5834 | | 0.0252 | 173.0001 | 5900 | 20.9383 | 0.8091 | 0.5882 | | 0.024 | 176.0001 | 6000 | 23.0352 | 0.8096 | 0.5913 | | 0.0281 | 179.0001 | 6100 | 19.2521 | 0.8087 | 0.5910 | | 0.0366 | 182.0001 | 6200 | 15.7690 | 0.8063 | 0.5857 | | 0.0583 | 185.0001 | 6300 | 16.3419 | 0.8062 | 0.5854 | | 0.0416 | 188.0001 | 6400 | 18.7125 | 0.8054 | 0.5898 | | 0.0225 | 191.0000 | 6500 | 22.5244 | 0.8105 | 0.5938 | | 0.044 | 194.0000 | 6600 | 21.5082 | 0.8059 | 0.5915 | | 0.0361 | 197.0000 | 6700 | 20.1734 | 0.8054 | 0.5811 | | 0.0245 | 199.0003 | 6800 | 20.5808 | 0.8165 | 0.6041 | | 0.0129 | 202.0002 | 6900 | 27.7038 | 0.8173 | 0.6062 | | 0.0109 | 205.0002 | 7000 | 22.6937 | 0.8188 | 0.6094 | | 0.0097 | 208.0002 | 7100 | 20.1624 | 0.8186 | 0.6085 | | 0.0088 | 211.0002 | 7200 | 19.8737 | 0.8191 | 0.6078 | | 0.0078 | 214.0002 | 7300 | 21.2022 | 0.8195 | 0.6102 | | 0.0077 | 217.0002 | 7400 | 17.8276 | 0.8184 | 0.6077 | | 0.0215 | 220.0001 | 7500 | 10.9249 | 0.8127 | 0.5990 | | 0.0609 | 223.0001 | 7600 | 13.1890 | 0.8032 | 0.5912 | | 0.0709 | 226.0001 | 7700 | 13.2116 | 0.8067 | 0.5872 | | 0.0393 | 229.0001 | 7800 | 16.6301 | 0.7959 | 0.5827 | | 0.0242 | 232.0001 | 7900 | 11.3938 | 0.8107 | 0.6046 | | 0.0444 | 235.0001 | 8000 | 10.1589 | 0.8149 | 0.5994 | | 0.0171 | 238.0001 | 8100 | 17.5608 | 0.8170 | 0.6128 | | 0.0088 | 241.0000 | 8200 | 31.8106 | 0.8201 | 0.6131 | | 0.006 | 244.0000 | 8300 | 31.6438 | 0.8201 | 0.6153 | | 0.0045 | 247.0000 | 8400 | 43.1105 | 0.8211 | 0.6166 | | 0.0042 | 249.0003 | 8500 | 48.9958 | 0.8210 | 0.6145 | | 0.0042 | 252.0002 | 8600 | 48.2911 | 0.8192 | 0.6153 | | 0.0041 | 255.0002 | 8700 | 58.6606 | 0.8205 | 0.6101 | | 0.0037 | 258.0002 | 8800 | 49.3388 | 0.8197 | 0.6140 | | 0.0034 | 261.0002 | 8900 | 43.3330 | 0.8210 | 0.6148 | | 0.0028 | 264.0002 | 9000 | 70.6156 | 0.8209 | 0.6167 | | 0.0027 | 267.0002 | 9100 | 58.1277 | 0.8208 | 0.6143 | | 0.0026 | 270.0001 | 9200 | 60.0669 | 0.8214 | 0.6174 | | 0.0023 | 273.0001 | 9300 | 59.1947 | 0.8211 | 0.6142 | | 0.0022 | 276.0001 | 9400 | 70.9149 | 0.8218 | 0.6161 | | 0.0034 | 279.0001 | 9500 | 67.0878 | 0.8201 | 0.6067 | | 0.0146 | 282.0001 | 9600 | 16.9134 | 0.8133 | 0.6036 | | 0.0726 | 285.0001 | 9700 | 6.7295 | 0.8017 | 0.5961 | | 0.0781 | 288.0001 | 9800 | 22.6693 | 0.8067 | 0.6121 | | 0.0339 | 291.0000 | 9900 | 21.5826 | 0.8182 | 0.6164 | | 0.01 | 294.0000 | 10000 | 44.6430 | 0.8216 | 0.6243 | | 0.0034 | 297.0000 | 10100 | 77.8298 | 0.8262 | 0.6292 | | 0.0025 | 299.0003 | 10200 | 96.9464 | 0.8257 | 0.6286 | | 0.0025 | 302.0002 | 10300 | 102.0366 | 0.8259 | 0.6314 | | 0.002 | 305.0002 | 10400 | 103.6177 | 0.8254 | 0.6278 | | 0.0019 | 308.0002 | 10500 | 103.6782 | 0.8253 | 0.6281 | | 0.0016 | 311.0002 | 10600 | 110.3705 | 0.8251 | 0.6291 | | 0.0016 | 314.0002 | 10700 | 119.2593 | 0.8256 | 0.6295 | | 0.0012 | 317.0002 | 10800 | 133.0785 | 0.8250 | 0.6285 | | 0.0011 | 320.0001 | 10900 | 139.8087 | 0.8265 | 0.6316 | | 0.0014 | 323.0001 | 11000 | 133.1513 | 0.8253 | 0.6296 | | 0.0013 | 326.0001 | 11100 | 131.9007 | 0.8258 | 0.6285 | | 0.001 | 329.0001 | 11200 | 132.4369 | 0.8260 | 0.6287 | | 0.001 | 332.0001 | 11300 | 140.8848 | 0.8259 | 0.6300 | | 0.001 | 335.0001 | 11400 | 134.3902 | 0.8259 | 0.6319 | | 0.0011 | 338.0001 | 11500 | 145.7966 | 0.8251 | 0.6278 | | 0.0102 | 341.0000 | 11600 | 81.0544 | 0.8162 | 0.6099 | | 0.0988 | 344.0000 | 11700 | 6.4441 | 0.8081 | 0.5983 | | 0.0383 | 347.0000 | 11800 | 15.7353 | 0.8171 | 0.6236 | | 0.0269 | 349.0003 | 11900 | 15.4510 | 0.8231 | 0.6299 | | 0.0056 | 352.0002 | 12000 | 39.3317 | 0.8310 | 0.6388 | | 0.002 | 355.0002 | 12100 | 64.9580 | 0.8321 | 0.6369 | | 0.0014 | 358.0002 | 12200 | 100.9092 | 0.8320 | 0.6356 | | 0.0015 | 361.0002 | 12300 | 132.6300 | 0.8308 | 0.6354 | | 0.0019 | 364.0002 | 12400 | 143.8231 | 0.8318 | 0.6366 | | 0.002 | 367.0002 | 12500 | 142.8417 | 0.8311 | 0.6350 | | 0.001 | 370.0001 | 12600 | 173.5246 | 0.8316 | 0.6363 | | 0.0009 | 373.0001 | 12700 | 169.8688 | 0.8314 | 0.6361 | | 0.0009 | 376.0001 | 12800 | 160.1022 | 0.8314 | 0.6367 | | 0.0007 | 379.0001 | 12900 | 171.5284 | 0.8316 | 0.6352 | | 0.0008 | 382.0001 | 13000 | 178.9394 | 0.8319 | 0.6365 | | 0.0007 | 385.0001 | 13100 | 169.9729 | 0.8310 | 0.6334 | | 0.0011 | 388.0001 | 13200 | 195.4408 | 0.8311 | 0.6363 | | 0.0062 | 391.0000 | 13300 | 171.9105 | 0.8207 | 0.6237 | | 0.0142 | 394.0000 | 13400 | 41.0027 | 0.8229 | 0.6282 | | 0.0302 | 397.0000 | 13500 | 24.5782 | 0.8197 | 0.6255 | | 0.0264 | 399.0003 | 13600 | 40.6889 | 0.8246 | 0.6186 | | 0.0084 | 402.0002 | 13700 | 105.5886 | 0.8247 | 0.6312 | | 0.0017 | 405.0002 | 13800 | 152.7374 | 0.8303 | 0.6388 | | 0.0011 | 408.0002 | 13900 | 159.2113 | 0.8314 | 0.6389 | | 0.0009 | 411.0002 | 14000 | 153.1523 | 0.8307 | 0.6377 | | 0.001 | 414.0002 | 14100 | 157.6186 | 0.8318 | 0.6400 | | 0.0008 | 417.0002 | 14200 | 182.1874 | 0.8315 | 0.6404 | | 0.0007 | 420.0001 | 14300 | 190.1730 | 0.8317 | 0.6393 | | 0.0006 | 423.0001 | 14400 | 195.1539 | 0.8308 | 0.6408 | | 0.0006 | 426.0001 | 14500 | 208.1863 | 0.8310 | 0.6392 | | 0.0008 | 429.0001 | 14600 | 204.0640 | 0.8310 | 0.6383 | | 0.0007 | 432.0001 | 14700 | 215.0364 | 0.8308 | 0.6408 | | 0.0007 | 435.0001 | 14800 | 218.7525 | 0.8307 | 0.6402 | | 0.0006 | 438.0001 | 14900 | 197.6684 | 0.8305 | 0.6407 | | 0.0006 | 441.0000 | 15000 | 185.9242 | 0.8306 | 0.6388 | | 0.0006 | 444.0000 | 15100 | 214.7215 | 0.8316 | 0.6412 | | 0.001 | 447.0000 | 15200 | 208.3420 | 0.8309 | 0.6395 | | 0.0006 | 449.0003 | 15300 | 234.3956 | 0.8324 | 0.6390 | | 0.0005 | 452.0002 | 15400 | 239.8244 | 0.8320 | 0.6384 | | 0.0004 | 455.0002 | 15500 | 244.7468 | 0.8327 | 0.6414 | | 0.0006 | 458.0002 | 15600 | 222.3871 | 0.8317 | 0.6354 | | 0.0007 | 461.0002 | 15700 | 201.6138 | 0.8325 | 0.6429 | | 0.0058 | 464.0002 | 15800 | 149.7280 | 0.8270 | 0.6376 | | 0.1063 | 467.0002 | 15900 | 3.3431 | 0.8018 | 0.6118 | | 0.0731 | 470.0001 | 16000 | 9.8959 | 0.8106 | 0.6004 | | 0.0164 | 473.0001 | 16100 | 75.8666 | 0.8310 | 0.6363 | | 0.0047 | 476.0001 | 16200 | 96.5890 | 0.8351 | 0.6489 | | 0.0013 | 479.0001 | 16300 | 128.9747 | 0.8350 | 0.6453 | | 0.0009 | 482.0001 | 16400 | 149.2739 | 0.8362 | 0.6472 | | 0.0009 | 485.0001 | 16500 | 163.3597 | 0.8355 | 0.6444 | | 0.0014 | 488.0001 | 16600 | 163.6047 | 0.8352 | 0.6450 | | 0.0008 | 491.0000 | 16700 | 181.5134 | 0.8357 | 0.6467 | | 0.0006 | 494.0000 | 16800 | 173.8016 | 0.8361 | 0.6457 | | 0.0006 | 497.0000 | 16900 | 181.4426 | 0.8352 | 0.6459 | | 0.0006 | 499.0003 | 17000 | 206.2824 | 0.8353 | 0.6437 | | 0.0005 | 502.0002 | 17100 | 231.8197 | 0.8352 | 0.6442 | | 0.0005 | 505.0002 | 17200 | 216.9023 | 0.8347 | 0.6448 | | 0.0004 | 508.0002 | 17300 | 221.9971 | 0.8351 | 0.6439 | | 0.0004 | 511.0002 | 17400 | 225.0059 | 0.8349 | 0.6429 | | 0.0005 | 514.0002 | 17500 | 224.4912 | 0.8345 | 0.6459 | | 0.0004 | 517.0002 | 17600 | 226.5936 | 0.8355 | 0.6445 | | 0.0004 | 520.0001 | 17700 | 226.1902 | 0.8350 | 0.6435 | | 0.0003 | 523.0001 | 17800 | 214.3505 | 0.8355 | 0.6439 | | 0.0003 | 526.0001 | 17900 | 242.6153 | 0.8352 | 0.6443 | | 0.0003 | 529.0001 | 18000 | 233.4839 | 0.8342 | 0.6421 | | 0.0004 | 532.0001 | 18100 | 207.2473 | 0.8350 | 0.6426 | | 0.0004 | 535.0001 | 18200 | 212.7851 | 0.8347 | 0.6421 | ### Framework versions - Transformers 4.46.0 - Pytorch 2.3.1+cu121 - Datasets 2.20.0 - Tokenizers 0.20.1