cellate-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: 1.2573
- Accuracy: 0.7397
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 | 1.2847 | 0.7278 |
| 1.3505 | 2.0 | 12 | 1.2635 | 0.7379 |
| 1.3676 | 3.0 | 18 | 1.3146 | 0.7406 |
| 1.2871 | 4.0 | 24 | 1.2949 | 0.7277 |
| 1.26 | 5.0 | 30 | 1.3364 | 0.7255 |
| 1.2586 | 6.0 | 36 | 1.3626 | 0.7243 |
| 1.307 | 7.0 | 42 | 1.2961 | 0.7280 |
| 1.248 | 8.0 | 48 | 1.2761 | 0.7266 |
| 1.2549 | 9.0 | 54 | 1.2707 | 0.7302 |
| 1.2123 | 10.0 | 60 | 1.3332 | 0.7139 |
| 1.2096 | 11.0 | 66 | 1.2993 | 0.7317 |
| 1.2494 | 12.0 | 72 | 1.2903 | 0.7274 |
| 1.2028 | 13.0 | 78 | 1.4261 | 0.7158 |
| 1.1927 | 14.0 | 84 | 1.2636 | 0.7219 |
| 1.2186 | 15.0 | 90 | 1.3468 | 0.7187 |
| 1.2001 | 16.0 | 96 | 1.3215 | 0.7183 |
| 1.3421 | 16.7273 | 100 | 1.2573 | 0.7397 |
Framework versions
- Transformers 4.48.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.21.0
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