tapt_reinit_only_4K_no_reinit_classifier_llrd0.9_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: 1.6722
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
- 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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.8199 | 1.0 | 609 | 1.6390 |
| 1.6303 | 2.0 | 1218 | 1.6489 |
| 1.5042 | 3.0 | 1827 | 1.5989 |
| 1.4113 | 4.0 | 2436 | 1.6950 |
| 1.3254 | 5.0 | 3045 | 1.6834 |
| 1.2811 | 6.0 | 3654 | 1.7477 |
| 1.2411 | 7.0 | 4263 | 1.7607 |
| 1.1898 | 8.0 | 4872 | 1.7285 |
| 1.146 | 9.0 | 5481 | 1.7246 |
| 1.1379 | 10.0 | 6090 | 1.7101 |
| 1.1208 | 11.0 | 6699 | 1.6693 |
| 1.0634 | 12.0 | 7308 | 1.7053 |
| 1.0582 | 13.0 | 7917 | 1.6786 |
| 1.0313 | 14.0 | 8526 | 1.7939 |
| 1.0062 | 15.0 | 9135 | 1.7675 |
| 0.9965 | 16.0 | 9744 | 1.7152 |
| 0.9845 | 17.0 | 10353 | 1.6762 |
| 0.9914 | 18.0 | 10962 | 1.7251 |
| 0.9665 | 19.0 | 11571 | 1.7469 |
| 0.9734 | 20.0 | 12180 | 1.7760 |
Framework versions
- Transformers 4.48.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.21.0
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