| --- |
| library_name: transformers |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| model-index: |
| - name: SignBart-ASL-400 |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # SignBart-ASL-400 |
|
|
| 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: 0.8715 |
| - Accuracy: 0.7804 |
| - Precision: 0.7968 |
| - Recall: 0.7804 |
|
|
| ## 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: 0.0002 |
| - train_batch_size: 256 |
| - eval_batch_size: 256 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - num_epochs: 1000 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:| |
| | 6.0768 | 1.0 | 35 | 5.9977 | 0.0034 | 0.0001 | 0.0034 | |
| | 6.0349 | 2.0 | 70 | 5.9374 | 0.0046 | 0.0004 | 0.0046 | |
| | 5.9294 | 3.0 | 105 | 5.6893 | 0.0154 | 0.0034 | 0.0154 | |
| | 5.6867 | 4.0 | 140 | 5.3946 | 0.0212 | 0.0094 | 0.0212 | |
| | 5.4328 | 5.0 | 175 | 5.1652 | 0.0298 | 0.0124 | 0.0298 | |
| | 5.2349 | 6.0 | 210 | 4.9791 | 0.0588 | 0.0395 | 0.0588 | |
| | 5.0643 | 7.0 | 245 | 4.8018 | 0.0742 | 0.0398 | 0.0742 | |
| | 4.9482 | 8.0 | 280 | 4.6428 | 0.1032 | 0.0799 | 0.1032 | |
| | 4.8503 | 9.0 | 315 | 4.4834 | 0.1393 | 0.0978 | 0.1393 | |
| | 4.6618 | 10.0 | 350 | 4.3149 | 0.1723 | 0.1382 | 0.1723 | |
| | 4.5032 | 11.0 | 385 | 4.1480 | 0.2108 | 0.2118 | 0.2108 | |
| | 4.378 | 12.0 | 420 | 4.0017 | 0.2533 | 0.2448 | 0.2533 | |
| | 4.313 | 13.0 | 455 | 3.8613 | 0.2794 | 0.2851 | 0.2794 | |
| | 4.2141 | 14.0 | 490 | 3.7279 | 0.3126 | 0.3257 | 0.3126 | |
| | 4.0236 | 15.0 | 525 | 3.5737 | 0.3448 | 0.3708 | 0.3448 | |
| | 4.0748 | 16.0 | 560 | 3.4735 | 0.3638 | 0.3895 | 0.3638 | |
| | 3.8336 | 17.0 | 595 | 3.3687 | 0.3763 | 0.3983 | 0.3763 | |
| | 3.7442 | 18.0 | 630 | 3.2452 | 0.4139 | 0.4401 | 0.4139 | |
| | 3.6543 | 19.0 | 665 | 3.1658 | 0.4131 | 0.4391 | 0.4131 | |
| | 3.5757 | 20.0 | 700 | 3.0657 | 0.4412 | 0.4715 | 0.4412 | |
| | 3.5742 | 21.0 | 735 | 2.9638 | 0.4561 | 0.4941 | 0.4561 | |
| | 3.4422 | 22.0 | 770 | 2.8810 | 0.4741 | 0.5117 | 0.4741 | |
| | 3.3174 | 23.0 | 805 | 2.7804 | 0.4868 | 0.5277 | 0.4868 | |
| | 3.1678 | 24.0 | 840 | 2.7162 | 0.5002 | 0.5339 | 0.5002 | |
| | 3.3057 | 25.0 | 875 | 2.6508 | 0.5010 | 0.5425 | 0.5010 | |
| | 3.0912 | 26.0 | 910 | 2.5528 | 0.5266 | 0.5597 | 0.5266 | |
| | 3.0476 | 27.0 | 945 | 2.4603 | 0.5566 | 0.5920 | 0.5566 | |
| | 2.9213 | 28.0 | 980 | 2.4284 | 0.5564 | 0.5957 | 0.5564 | |
| | 2.9069 | 29.0 | 1015 | 2.3612 | 0.5612 | 0.5947 | 0.5612 | |
| | 2.7931 | 30.0 | 1050 | 2.2954 | 0.5776 | 0.6164 | 0.5776 | |
| | 2.9095 | 31.0 | 1085 | 2.2388 | 0.5764 | 0.6103 | 0.5764 | |
| | 2.8603 | 32.0 | 1120 | 2.1720 | 0.5903 | 0.6279 | 0.5903 | |
| | 2.7008 | 33.0 | 1155 | 2.1129 | 0.5993 | 0.6244 | 0.5993 | |
| | 2.7811 | 34.0 | 1190 | 2.0643 | 0.6042 | 0.6385 | 0.6042 | |
| | 2.6529 | 35.0 | 1225 | 2.0183 | 0.6069 | 0.6361 | 0.6069 | |
| | 2.5363 | 36.0 | 1260 | 1.9997 | 0.6054 | 0.6484 | 0.6054 | |
| | 2.4029 | 37.0 | 1295 | 1.9467 | 0.6130 | 0.6404 | 0.6130 | |
| | 2.4787 | 38.0 | 1330 | 1.8683 | 0.6379 | 0.6574 | 0.6379 | |
| | 2.5173 | 39.0 | 1365 | 1.8616 | 0.6327 | 0.6602 | 0.6327 | |
| | 2.6548 | 40.0 | 1400 | 1.8232 | 0.6349 | 0.6638 | 0.6349 | |
| | 2.3104 | 41.0 | 1435 | 1.7686 | 0.6464 | 0.6701 | 0.6464 | |
| | 2.3891 | 42.0 | 1470 | 1.7388 | 0.6528 | 0.6840 | 0.6528 | |
| | 2.4407 | 43.0 | 1505 | 1.7080 | 0.6506 | 0.6763 | 0.6506 | |
| | 2.2347 | 44.0 | 1540 | 1.7102 | 0.6398 | 0.6742 | 0.6398 | |
| | 2.2116 | 45.0 | 1575 | 1.6484 | 0.6672 | 0.6908 | 0.6672 | |
| | 2.0694 | 46.0 | 1610 | 1.6012 | 0.6684 | 0.6917 | 0.6684 | |
| | 2.0869 | 47.0 | 1645 | 1.5758 | 0.6696 | 0.6900 | 0.6696 | |
| | 2.1581 | 48.0 | 1680 | 1.5490 | 0.6837 | 0.7098 | 0.6837 | |
| | 2.0666 | 49.0 | 1715 | 1.5222 | 0.6776 | 0.7003 | 0.6776 | |
| | 1.9592 | 50.0 | 1750 | 1.4896 | 0.6881 | 0.7135 | 0.6881 | |
| | 2.1065 | 51.0 | 1785 | 1.5038 | 0.6708 | 0.6935 | 0.6708 | |
| | 1.8903 | 52.0 | 1820 | 1.4422 | 0.6935 | 0.7182 | 0.6935 | |
| | 1.8887 | 53.0 | 1855 | 1.4312 | 0.6886 | 0.7062 | 0.6886 | |
| | 2.028 | 54.0 | 1890 | 1.3897 | 0.7020 | 0.7218 | 0.7020 | |
| | 1.937 | 55.0 | 1925 | 1.3826 | 0.6862 | 0.7075 | 0.6862 | |
| | 1.9876 | 56.0 | 1960 | 1.3687 | 0.6967 | 0.7185 | 0.6967 | |
| | 1.8689 | 57.0 | 1995 | 1.3580 | 0.6950 | 0.7192 | 0.6950 | |
| | 1.7962 | 58.0 | 2030 | 1.3743 | 0.6901 | 0.7156 | 0.6901 | |
| | 1.8528 | 59.0 | 2065 | 1.3034 | 0.7047 | 0.7323 | 0.7047 | |
| | 1.7134 | 60.0 | 2100 | 1.2906 | 0.7128 | 0.7316 | 0.7128 | |
| | 2.0335 | 61.0 | 2135 | 1.3115 | 0.7011 | 0.7241 | 0.7011 | |
| | 1.8349 | 62.0 | 2170 | 1.2628 | 0.7133 | 0.7368 | 0.7133 | |
| | 1.6479 | 63.0 | 2205 | 1.2390 | 0.7174 | 0.7385 | 0.7174 | |
| | 1.6653 | 64.0 | 2240 | 1.2174 | 0.7206 | 0.7364 | 0.7206 | |
| | 1.6352 | 65.0 | 2275 | 1.1998 | 0.7230 | 0.7418 | 0.7230 | |
| | 2.1608 | 66.0 | 2310 | 1.1977 | 0.7247 | 0.7449 | 0.7247 | |
| | 1.6582 | 67.0 | 2345 | 1.2085 | 0.7174 | 0.7425 | 0.7174 | |
| | 1.6359 | 68.0 | 2380 | 1.1698 | 0.7252 | 0.7462 | 0.7252 | |
| | 1.6276 | 69.0 | 2415 | 1.1569 | 0.7282 | 0.7459 | 0.7282 | |
| | 1.6379 | 70.0 | 2450 | 1.1647 | 0.7262 | 0.7458 | 0.7262 | |
| | 1.6273 | 71.0 | 2485 | 1.1557 | 0.7269 | 0.7490 | 0.7269 | |
| | 1.6997 | 72.0 | 2520 | 1.1177 | 0.7304 | 0.7473 | 0.7304 | |
| | 1.3425 | 73.0 | 2555 | 1.1140 | 0.7418 | 0.7602 | 0.7418 | |
| | 1.3719 | 74.0 | 2590 | 1.0945 | 0.7399 | 0.7522 | 0.7399 | |
| | 1.6558 | 75.0 | 2625 | 1.0909 | 0.7457 | 0.7651 | 0.7457 | |
| | 1.3146 | 76.0 | 2660 | 1.0984 | 0.7399 | 0.7606 | 0.7399 | |
| | 1.4204 | 77.0 | 2695 | 1.0874 | 0.7347 | 0.7523 | 0.7347 | |
| | 1.4834 | 78.0 | 2730 | 1.0677 | 0.7430 | 0.7604 | 0.7430 | |
| | 1.318 | 79.0 | 2765 | 1.0695 | 0.7367 | 0.7563 | 0.7367 | |
| | 1.5943 | 80.0 | 2800 | 1.0558 | 0.7428 | 0.7638 | 0.7428 | |
| | 1.4331 | 81.0 | 2835 | 1.0573 | 0.7396 | 0.7588 | 0.7396 | |
| | 1.7275 | 82.0 | 2870 | 1.0503 | 0.7457 | 0.7649 | 0.7457 | |
| | 1.4237 | 83.0 | 2905 | 1.0315 | 0.7491 | 0.7676 | 0.7491 | |
| | 1.348 | 84.0 | 2940 | 1.0464 | 0.7413 | 0.7632 | 0.7413 | |
| | 1.4183 | 85.0 | 2975 | 1.0038 | 0.7543 | 0.7710 | 0.7543 | |
| | 1.3382 | 86.0 | 3010 | 1.0062 | 0.7535 | 0.7726 | 0.7535 | |
| | 1.3279 | 87.0 | 3045 | 1.0036 | 0.7484 | 0.7659 | 0.7484 | |
| | 1.2822 | 88.0 | 3080 | 1.0072 | 0.7501 | 0.7665 | 0.7501 | |
| | 1.205 | 89.0 | 3115 | 0.9785 | 0.7609 | 0.7743 | 0.7609 | |
| | 1.1973 | 90.0 | 3150 | 0.9826 | 0.7521 | 0.7703 | 0.7521 | |
| | 1.3498 | 91.0 | 3185 | 0.9904 | 0.7533 | 0.7704 | 0.7533 | |
| | 1.3605 | 92.0 | 3220 | 0.9947 | 0.7526 | 0.7682 | 0.7526 | |
| | 1.4065 | 93.0 | 3255 | 0.9897 | 0.7562 | 0.7747 | 0.7562 | |
| | 1.1482 | 94.0 | 3290 | 0.9745 | 0.7552 | 0.7744 | 0.7552 | |
| | 1.1124 | 95.0 | 3325 | 0.9712 | 0.7560 | 0.7751 | 0.7560 | |
| | 1.2142 | 96.0 | 3360 | 0.9556 | 0.7599 | 0.7732 | 0.7599 | |
| | 1.2644 | 97.0 | 3395 | 0.9534 | 0.7604 | 0.7761 | 0.7604 | |
| | 1.2449 | 98.0 | 3430 | 0.9559 | 0.7565 | 0.7730 | 0.7565 | |
| | 1.42 | 99.0 | 3465 | 0.9568 | 0.7516 | 0.7692 | 0.7516 | |
| | 1.5439 | 100.0 | 3500 | 0.9487 | 0.7579 | 0.7741 | 0.7579 | |
| | 1.2883 | 101.0 | 3535 | 0.9348 | 0.7628 | 0.7784 | 0.7628 | |
| | 1.2313 | 102.0 | 3570 | 0.9478 | 0.7638 | 0.7804 | 0.7638 | |
| | 1.2525 | 103.0 | 3605 | 0.9521 | 0.7621 | 0.7801 | 0.7621 | |
| | 1.0693 | 104.0 | 3640 | 0.9183 | 0.7672 | 0.7854 | 0.7672 | |
| | 1.2183 | 105.0 | 3675 | 0.9488 | 0.7606 | 0.7810 | 0.7606 | |
| | 1.0968 | 106.0 | 3710 | 0.9239 | 0.7640 | 0.7790 | 0.7640 | |
| | 1.146 | 107.0 | 3745 | 0.9285 | 0.7606 | 0.7779 | 0.7606 | |
| | 1.061 | 108.0 | 3780 | 0.9320 | 0.7618 | 0.7801 | 0.7618 | |
| | 1.4022 | 109.0 | 3815 | 0.9174 | 0.7640 | 0.7802 | 0.7640 | |
| | 1.1946 | 110.0 | 3850 | 0.9197 | 0.7604 | 0.7747 | 0.7604 | |
| | 1.0868 | 111.0 | 3885 | 0.9124 | 0.7662 | 0.7819 | 0.7662 | |
| | 0.9491 | 112.0 | 3920 | 0.9253 | 0.7689 | 0.7839 | 0.7689 | |
| | 1.1374 | 113.0 | 3955 | 0.9254 | 0.7643 | 0.7797 | 0.7643 | |
| | 1.1835 | 114.0 | 3990 | 0.9142 | 0.7653 | 0.7821 | 0.7653 | |
| | 1.1594 | 115.0 | 4025 | 0.9279 | 0.7611 | 0.7808 | 0.7611 | |
| | 1.0603 | 116.0 | 4060 | 0.9025 | 0.7770 | 0.7927 | 0.7770 | |
| | 1.174 | 117.0 | 4095 | 0.8895 | 0.7726 | 0.7891 | 0.7726 | |
| | 1.0453 | 118.0 | 4130 | 0.8904 | 0.7748 | 0.7892 | 0.7748 | |
| | 1.2013 | 119.0 | 4165 | 0.9123 | 0.7672 | 0.7831 | 0.7672 | |
| | 1.1358 | 120.0 | 4200 | 0.9235 | 0.7701 | 0.7880 | 0.7701 | |
| | 1.1468 | 121.0 | 4235 | 0.8970 | 0.7723 | 0.7871 | 0.7723 | |
| | 0.9599 | 122.0 | 4270 | 0.8889 | 0.7738 | 0.7893 | 0.7738 | |
| | 0.9898 | 123.0 | 4305 | 0.8958 | 0.7743 | 0.7898 | 0.7743 | |
| | 0.9008 | 124.0 | 4340 | 0.8854 | 0.7757 | 0.7901 | 0.7757 | |
| | 0.9634 | 125.0 | 4375 | 0.8892 | 0.7775 | 0.7925 | 0.7775 | |
| | 1.1803 | 126.0 | 4410 | 0.8921 | 0.7687 | 0.7828 | 0.7687 | |
| | 0.9796 | 127.0 | 4445 | 0.8758 | 0.7777 | 0.7911 | 0.7777 | |
| | 0.979 | 128.0 | 4480 | 0.8849 | 0.7753 | 0.7919 | 0.7753 | |
| | 0.9416 | 129.0 | 4515 | 0.8756 | 0.7816 | 0.7974 | 0.7816 | |
| | 1.1879 | 130.0 | 4550 | 0.8878 | 0.7755 | 0.7905 | 0.7755 | |
| | 0.9852 | 131.0 | 4585 | 0.8923 | 0.7748 | 0.7918 | 0.7748 | |
| | 0.8054 | 132.0 | 4620 | 0.8682 | 0.7836 | 0.7980 | 0.7836 | |
| | 0.8866 | 133.0 | 4655 | 0.8755 | 0.7777 | 0.7913 | 0.7777 | |
| | 1.0883 | 134.0 | 4690 | 0.8875 | 0.7740 | 0.7884 | 0.7740 | |
| | 1.0614 | 135.0 | 4725 | 0.8807 | 0.7770 | 0.7930 | 0.7770 | |
| | 0.9038 | 136.0 | 4760 | 0.8823 | 0.7831 | 0.7977 | 0.7831 | |
| | 0.8942 | 137.0 | 4795 | 0.8715 | 0.7804 | 0.7968 | 0.7804 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.45.1 |
| - Pytorch 2.4.0 |
| - Datasets 3.0.1 |
| - Tokenizers 0.20.0 |
|
|
