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cellate2.0_grouped_txt-tapt_base-LR_1e-05
Mardiyyah/cellate2.0_grouped_txt-tapt_base-LR_1e-05
cellate2.0_grouped_txt-tapt_base-LR_1e-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
- Feb 24, 2026
- Updated
- Feb 24, 2026
- SHA
- 6ddb514e
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Base models
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. -->
cellate2.0_grouped_txt-tapt_base-LR_1e-05
This model is a fine-tuned version of microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2581
- Accuracy: 0.7389
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: 1e-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: 0.1
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.3595 | 1.0 | 6 | 1.2848 | 0.7278 |
| 1.3505 | 2.0 | 12 | 1.2635 | 0.7375 |
| 1.3674 | 3.0 | 18 | 1.3147 | 0.7406 |
| 1.2867 | 4.0 | 24 | 1.2947 | 0.7277 |
| 1.2594 | 5.0 | 30 | 1.3362 | 0.7246 |
| 1.2579 | 6.0 | 36 | 1.3625 | 0.7243 |
| 1.306 | 7.0 | 42 | 1.2952 | 0.7280 |
| 1.246 | 8.0 | 48 | 1.2754 | 0.7266 |
| 1.2535 | 9.0 | 54 | 1.2704 | 0.7289 |
| 1.2113 | 10.0 | 60 | 1.3327 | 0.7147 |
| 1.2085 | 11.0 | 66 | 1.2989 | 0.7317 |
| 1.2484 | 12.0 | 72 | 1.2919 | 0.7283 |
| 1.2019 | 13.0 | 78 | 1.4255 | 0.7158 |
| 1.1917 | 14.0 | 84 | 1.2635 | 0.7224 |
| 1.2182 | 15.0 | 90 | 1.3473 | 0.7179 |
| 1.1995 | 16.0 | 96 | 1.3205 | 0.7196 |
| 1.3415 | 16.7273 | 100 | 1.2581 | 0.7389 |
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
- Feb 24, 2026
- Updated
- Feb 24, 2026