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TAPT-V1-Bioformer-16L
Mardiyyah/TAPT-V1-Bioformer-16L
TAPT-V1-Bioformer-16L 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
- Nov 10, 2025
- Updated
- Nov 10, 2025
- SHA
- 04a10b1a
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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. -->
TAPT-V1-Bioformer-16L
This model is a fine-tuned version of bioformers/bioformer-16L on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.0032
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: 16
- eval_batch_size: 16
- seed: 42
- 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.0908 | 1.0 | 150 | 1.9890 |
| 1.862 | 2.0 | 300 | 2.1129 |
| 1.6906 | 3.0 | 450 | 2.1431 |
| 1.5674 | 4.0 | 600 | 2.1108 |
| 1.5622 | 5.0 | 750 | 2.1245 |
| 1.4715 | 6.0 | 900 | 2.1117 |
| 1.4321 | 7.0 | 1050 | 2.1577 |
| 1.3189 | 8.0 | 1200 | 2.1733 |
| 1.2598 | 9.0 | 1350 | 2.1789 |
| 1.3167 | 10.0 | 1500 | 2.2537 |
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
- Created
- Nov 10, 2025
- Updated
- Nov 10, 2025