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CeLLaTe-tapt-bioformer16l-tokenizer-adapted_v2
Mardiyyah/CeLLaTe-tapt-bioformer16l-tokenizer-adapted_v2
CeLLaTe-tapt-bioformer16l-tokenizer-adapted_v2 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 apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Fill-Mask
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Jul 20, 2026
- Updated
- Jul 20, 2026
- SHA
- fa347d4b
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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-bioformer16l-tokenizer-adapted_v2
This model is a fine-tuned version of Mardiyyah/CeLLaTe-bioformer16l-tokenizer-adapted_v2 on the Mardiyyah/TAPT_CeLLaTe2.0 dataset. It achieves the following results on the evaluation set:
- Loss: 2.1972
- Accuracy: 0.6595
- Perplexity: 8.9995
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 3407
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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 | Perplexity |
|---|---|---|---|---|---|
| No log | 1.0 | 15 | 10.0400 | 0.0001 | 22925.8849 |
| No log | 2.0 | 30 | 8.3449 | 0.0151 | 4208.6382 |
| No log | 3.0 | 45 | 7.4704 | 0.0487 | 1755.2841 |
| No log | 4.0 | 60 | 6.6988 | 0.1537 | 811.4223 |
| No log | 5.0 | 75 | 5.7744 | 0.2423 | 321.9416 |
| No log | 6.0 | 90 | 5.0991 | 0.2929 | 163.8712 |
| 7.2448 | 7.0 | 105 | 4.6161 | 0.3352 | 101.1012 |
| 7.2448 | 8.0 | 120 | 4.3294 | 0.3684 | 75.9018 |
| 7.2448 | 9.0 | 135 | 4.0365 | 0.4165 | 56.6304 |
| 7.2448 | 10.0 | 150 | 3.7739 | 0.4547 | 43.5498 |
| 7.2448 | 11.0 | 165 | 3.6480 | 0.4708 | 38.3989 |
| 7.2448 | 12.0 | 180 | 3.5158 | 0.4929 | 33.6412 |
| 7.2448 | 13.0 | 195 | 3.3748 | 0.5207 | 29.2174 |
| 3.7694 | 14.0 | 210 | 3.3173 | 0.5312 | 27.5857 |
| 3.7694 | 15.0 | 225 | 3.1718 | 0.5520 | 23.8504 |
| 3.7694 | 16.0 | 240 | 3.0936 | 0.5672 | 22.0569 |
| 3.7694 | 17.0 | 255 | 2.9628 | 0.5847 | 19.3523 |
| 3.7694 | 18.0 | 270 | 2.9632 | 0.5905 | 19.3593 |
| 3.7694 | 19.0 | 285 | 2.8408 | 0.6028 | 17.1289 |
| 2.9131 | 20.0 | 300 | 2.8172 | 0.6016 | 16.7297 |
| 2.9131 | 21.0 | 315 | 2.7721 | 0.6076 | 15.9929 |
| 2.9131 | 22.0 | 330 | 2.6897 | 0.6212 | 14.7273 |
| 2.9131 | 23.0 | 345 | 2.7109 | 0.6143 | 15.0433 |
| 2.9131 | 24.0 | 360 | 2.6392 | 0.6273 | 14.0017 |
| 2.9131 | 25.0 | 375 | 2.5636 | 0.6340 | 12.9831 |
| 2.9131 | 26.0 | 390 | 2.6081 | 0.6283 | 13.5731 |
| 2.5444 | 27.0 | 405 | 2.5520 | 0.6382 | 12.8327 |
| 2.5444 | 28.0 | 420 | 2.5556 | 0.6311 | 12.8793 |
| 2.5444 | 29.0 | 435 | 2.4450 | 0.6420 | 11.5305 |
| 2.5444 | 30.0 | 450 | 2.4491 | 0.6444 | 11.5782 |
| 2.5444 | 31.0 | 465 | 2.4579 | 0.6372 | 11.6799 |
| 2.5444 | 32.0 | 480 | 2.4132 | 0.6445 | 11.1694 |
| 2.5444 | 33.0 | 495 | 2.4018 | 0.6413 | 11.0430 |
| 2.3127 | 34.0 | 510 | 2.4056 | 0.6424 | 11.0851 |
| 2.3127 | 35.0 | 525 | 2.3329 | 0.6547 | 10.3082 |
| 2.3127 | 36.0 | 540 | 2.3531 | 0.6487 | 10.5180 |
| 2.3127 | 37.0 | 555 | 2.3558 | 0.6461 | 10.5470 |
| 2.3127 | 38.0 | 570 | 2.3010 | 0.6507 | 9.9838 |
| 2.3127 | 39.0 | 585 | 2.3393 | 0.6503 | 10.3739 |
| 2.1667 | 40.0 | 600 | 2.3152 | 0.6504 | 10.1271 |
| 2.1667 | 41.0 | 615 | 2.2805 | 0.6537 | 9.7815 |
| 2.1667 | 42.0 | 630 | 2.3036 | 0.6549 | 10.0099 |
| 2.1667 | 43.0 | 645 | 2.2601 | 0.6543 | 9.5840 |
| 2.1667 | 44.0 | 660 | 2.2526 | 0.6575 | 9.5124 |
| 2.1667 | 45.0 | 675 | 2.2620 | 0.6560 | 9.6025 |
| 2.1667 | 46.0 | 690 | 2.2442 | 0.6563 | 9.4332 |
| 2.0694 | 47.0 | 705 | 2.2202 | 0.6594 | 9.2095 |
| 2.0694 | 48.0 | 720 | 2.2120 | 0.6605 | 9.1335 |
| 2.0694 | 49.0 | 735 | 2.1944 | 0.6616 | 8.9749 |
| 2.0694 | 50.0 | 750 | 2.1647 | 0.6646 | 8.7118 |
| 2.0694 | 51.0 | 765 | 2.2410 | 0.6562 | 9.4024 |
| 2.0694 | 52.0 | 780 | 2.1533 | 0.6645 | 8.6136 |
| 2.0694 | 53.0 | 795 | 2.1766 | 0.6628 | 8.8162 |
| 1.9781 | 54.0 | 810 | 2.1730 | 0.6596 | 8.7850 |
| 1.9781 | 55.0 | 825 | 2.1170 | 0.6672 | 8.3063 |
| 1.9781 | 56.0 | 840 | 2.1476 | 0.6655 | 8.5644 |
| 1.9781 | 57.0 | 855 | 2.1318 | 0.6683 | 8.4299 |
| 1.9781 | 58.0 | 870 | 2.1554 | 0.6620 | 8.6312 |
| 1.9781 | 59.0 | 885 | 2.1558 | 0.6613 | 8.6352 |
| 1.9185 | 60.0 | 900 | 2.1578 | 0.6582 | 8.6522 |
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
- apache-2.0
- Languages
- en
- Created
- Jul 20, 2026
- Updated
- Jul 20, 2026