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CeLLaTe-tapt_ulmfit-LR_2e-05
Mardiyyah/CeLLaTe-tapt_ulmfit-LR_2e-05
CeLLaTe-tapt_ulmfit-LR_2e-05 is a fill-mask model from Mardiyyah. Use it when you need the model to fill a missing word. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Fill-Mask
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Nov 21, 2025
- Updated
- Nov 21, 2025
- SHA
- 54f6e07e
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Model card
From the Hugging Face model README
<!-- 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. -->
CeLLaTe-tapt_ulmfit-LR_2e-05
This model is a fine-tuned version of microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext on the Mardiyyah/TAPT_data_V2_split dataset. It achieves the following results on the evaluation set:
- Loss: 1.0978
- Accuracy: 0.7612
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 3407
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.426 | 1.0 | 21 | 1.2594 | 0.7324 |
| 1.405 | 2.0 | 42 | 1.2467 | 0.7366 |
| 1.3785 | 3.0 | 63 | 1.2092 | 0.7403 |
| 1.364 | 4.0 | 84 | 1.2270 | 0.7360 |
| 1.3309 | 5.0 | 105 | 1.2189 | 0.7399 |
| 1.3407 | 6.0 | 126 | 1.2297 | 0.7370 |
| 1.3141 | 7.0 | 147 | 1.1691 | 0.7421 |
| 1.3039 | 8.0 | 168 | 1.1879 | 0.7474 |
| 1.2869 | 9.0 | 189 | 1.1552 | 0.7452 |
| 1.2759 | 10.0 | 210 | 1.1660 | 0.7483 |
| 1.2406 | 11.0 | 231 | 1.1348 | 0.7519 |
| 1.2622 | 12.0 | 252 | 1.1563 | 0.7457 |
| 1.271 | 13.0 | 273 | 1.1812 | 0.7414 |
| 1.259 | 14.0 | 294 | 1.1268 | 0.7505 |
| 1.2611 | 15.0 | 315 | 1.1653 | 0.7402 |
| 1.2179 | 16.0 | 336 | 1.1489 | 0.7458 |
| 1.2283 | 17.0 | 357 | 1.1930 | 0.7389 |
| 1.2087 | 18.0 | 378 | 1.1431 | 0.7512 |
| 1.2244 | 19.0 | 399 | 1.1522 | 0.7454 |
| 1.216 | 20.0 | 420 | 1.1481 | 0.7475 |
| 1.1772 | 21.0 | 441 | 1.1044 | 0.7527 |
| 1.1823 | 22.0 | 462 | 1.1526 | 0.7462 |
| 1.1769 | 23.0 | 483 | 1.1515 | 0.7464 |
| 1.165 | 24.0 | 504 | 1.1232 | 0.7523 |
| 1.1894 | 25.0 | 525 | 1.1750 | 0.7442 |
| 1.1824 | 26.0 | 546 | 1.1338 | 0.7470 |
| 1.1846 | 27.0 | 567 | 1.1422 | 0.7526 |
| 1.1713 | 28.0 | 588 | 1.1659 | 0.7448 |
| 1.1499 | 29.0 | 609 | 1.1670 | 0.7402 |
| 1.1797 | 30.0 | 630 | 1.1475 | 0.7501 |
| 1.1402 | 31.0 | 651 | 1.1668 | 0.7494 |
| 1.1691 | 32.0 | 672 | 1.1417 | 0.7485 |
| 1.1405 | 33.0 | 693 | 1.1255 | 0.7516 |
| 1.1515 | 34.0 | 714 | 1.1319 | 0.7486 |
| 1.1523 | 35.0 | 735 | 1.1606 | 0.7421 |
| 1.1479 | 36.0 | 756 | 1.1598 | 0.7477 |
| 1.1586 | 37.0 | 777 | 1.1303 | 0.7514 |
| 1.1431 | 38.0 | 798 | 1.1498 | 0.7470 |
| 1.1249 | 39.0 | 819 | 1.1198 | 0.7507 |
| 1.1488 | 40.0 | 840 | 1.0946 | 0.7597 |
| 1.1192 | 41.0 | 861 | 1.1658 | 0.7436 |
| 1.1422 | 42.0 | 882 | 1.1911 | 0.7411 |
| 1.1417 | 43.0 | 903 | 1.1499 | 0.7456 |
| 1.13 | 44.0 | 924 | 1.1271 | 0.7513 |
| 1.1321 | 45.0 | 945 | 1.1536 | 0.7503 |
| 1.1297 | 46.0 | 966 | 1.1400 | 0.7464 |
| 1.1201 | 47.0 | 987 | 1.1694 | 0.7456 |
| 1.1116 | 48.0 | 1008 | 1.1379 | 0.7496 |
| 1.1438 | 49.0 | 1029 | 1.1962 | 0.7400 |
| 1.1286 | 50.0 | 1050 | 1.1648 | 0.7470 |
| 1.1178 | 51.0 | 1071 | 1.1946 | 0.7389 |
| 1.1045 | 52.0 | 1092 | 1.1552 | 0.7498 |
| 1.1239 | 53.0 | 1113 | 1.1641 | 0.7462 |
| 1.1091 | 54.0 | 1134 | 1.1907 | 0.7471 |
| 1.0978 | 55.0 | 1155 | 1.1708 | 0.7463 |
| 1.1087 | 56.0 | 1176 | 1.1300 | 0.7515 |
| 1.1212 | 57.0 | 1197 | 1.1515 | 0.7500 |
| 1.1249 | 58.0 | 1218 | 1.1530 | 0.7510 |
| 1.1021 | 59.0 | 1239 | 1.1405 | 0.7530 |
| 1.1024 | 60.0 | 1260 | 1.1327 | 0.7536 |
| 1.1015 | 61.0 | 1281 | 1.1644 | 0.7499 |
| 1.1103 | 62.0 | 1302 | 1.1186 | 0.7507 |
| 1.1259 | 63.0 | 1323 | 1.1596 | 0.7465 |
| 1.088 | 64.0 | 1344 | 1.1625 | 0.7454 |
| 1.0948 | 65.0 | 1365 | 1.1463 | 0.7467 |
| 1.1121 | 66.0 | 1386 | 1.2079 | 0.7424 |
| 1.0971 | 67.0 | 1407 | 1.1519 | 0.7487 |
| 1.0748 | 68.0 | 1428 | 1.1570 | 0.7433 |
| 1.1075 | 69.0 | 1449 | 1.1388 | 0.7519 |
| 1.0945 | 70.0 | 1470 | 1.1673 | 0.7484 |
| 1.0833 | 71.0 | 1491 | 1.1329 | 0.7516 |
| 1.0875 | 72.0 | 1512 | 1.1723 | 0.7418 |
| 1.0915 | 73.0 | 1533 | 1.1537 | 0.7478 |
| 1.0776 | 74.0 | 1554 | 1.1326 | 0.7550 |
| 1.0866 | 75.0 | 1575 | 1.1435 | 0.7490 |
| 1.0952 | 76.0 | 1596 | 1.1409 | 0.7436 |
| 1.0995 | 77.0 | 1617 | 1.1387 | 0.7516 |
| 1.0897 | 78.0 | 1638 | 1.1622 | 0.7446 |
| 1.0837 | 79.0 | 1659 | 1.1246 | 0.7522 |
| 1.1172 | 80.0 | 1680 | 1.1339 | 0.7490 |
| 1.0764 | 81.0 | 1701 | 1.1524 | 0.7537 |
| 1.0661 | 82.0 | 1722 | 1.1239 | 0.7547 |
| 1.1066 | 83.0 | 1743 | 1.1721 | 0.7495 |
| 1.0817 | 84.0 | 1764 | 1.1139 | 0.7548 |
| 1.0748 | 85.0 | 1785 | 1.1500 | 0.7459 |
| 1.0927 | 86.0 | 1806 | 1.1703 | 0.7445 |
| 1.1006 | 87.0 | 1827 | 1.1875 | 0.7432 |
| 1.0793 | 88.0 | 1848 | 1.1600 | 0.7454 |
| 1.0794 | 89.0 | 1869 | 1.1200 | 0.7554 |
| 1.0834 | 90.0 | 1890 | 1.1317 | 0.7464 |
| 1.091 | 91.0 | 1911 | 1.1384 | 0.7517 |
| 1.0903 | 92.0 | 1932 | 1.1452 | 0.7500 |
| 1.0838 | 93.0 | 1953 | 1.1264 | 0.7534 |
| 1.092 | 94.0 | 1974 | 1.1442 | 0.7471 |
| 1.0868 | 95.0 | 1995 | 1.1712 | 0.7412 |
| 1.0804 | 96.0 | 2016 | 1.1599 | 0.7472 |
| 1.1127 | 97.0 | 2037 | 1.1481 | 0.7516 |
| 1.0712 | 98.0 | 2058 | 1.1194 | 0.7519 |
| 1.0723 | 99.0 | 2079 | 1.1521 | 0.7447 |
| 1.099 | 100.0 | 2100 | 1.1281 | 0.7482 |
Framework versions
- Transformers 4.48.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.21.0
- Task
- Fill-Mask
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- Nov 21, 2025
- Updated
- Nov 21, 2025