cellate-tapt_base-LR_1e-05
This model is a fine-tuned version of Mardiyyah/biomedbert_model_extended_untrained on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 6.1339
- Accuracy: 0.2568
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: 0.06
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 10.1673 | 1.0 | 6 | 11.0601 | 0.0 |
| 9.7047 | 2.0 | 12 | 10.0083 | 0.0 |
| 8.7667 | 3.0 | 18 | 9.2391 | 0.0025 |
| 8.0493 | 4.0 | 24 | 8.5184 | 0.0256 |
| 7.555 | 5.0 | 30 | 7.9435 | 0.0637 |
| 7.1487 | 6.0 | 36 | 7.7096 | 0.0716 |
| 6.8066 | 7.0 | 42 | 7.3534 | 0.0997 |
| 6.5712 | 8.0 | 48 | 7.2085 | 0.1537 |
| 6.3437 | 9.0 | 54 | 6.9363 | 0.1856 |
| 6.1888 | 10.0 | 60 | 6.8290 | 0.1927 |
| 5.9906 | 11.0 | 66 | 6.6097 | 0.2204 |
| 5.8675 | 12.0 | 72 | 6.4388 | 0.2308 |
| 5.7465 | 13.0 | 78 | 6.2943 | 0.2438 |
| 5.7011 | 14.0 | 84 | 6.2983 | 0.2472 |
| 5.5803 | 15.0 | 90 | 6.4921 | 0.2250 |
| 5.598 | 16.0 | 96 | 6.2085 | 0.2488 |
| 5.9767 | 16.7273 | 100 | 6.1339 | 0.2568 |
Framework versions
- Transformers 4.48.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.21.0
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