cellate2.0-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: 1.2490
- Accuracy: 0.7374
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 |
|---|---|---|---|---|
| 1.3074 | 1.0 | 8 | 1.3493 | 0.7268 |
| 1.3334 | 2.0 | 16 | 1.2121 | 0.7454 |
| 1.2836 | 3.0 | 24 | 1.1923 | 0.7396 |
| 1.2573 | 4.0 | 32 | 1.2492 | 0.7325 |
| 1.2562 | 5.0 | 40 | 1.3008 | 0.7256 |
| 1.2574 | 6.0 | 48 | 1.3265 | 0.7330 |
| 1.2348 | 7.0 | 56 | 1.2669 | 0.7383 |
| 1.1934 | 8.0 | 64 | 1.3190 | 0.7299 |
| 1.2231 | 9.0 | 72 | 1.2762 | 0.7334 |
| 1.2189 | 10.0 | 80 | 1.2924 | 0.7359 |
| 1.1911 | 11.0 | 88 | 1.2681 | 0.7373 |
| 1.2217 | 12.0 | 96 | 1.2005 | 0.7410 |
| 1.196 | 13.0 | 104 | 1.2292 | 0.7256 |
| 1.1907 | 14.0 | 112 | 1.3222 | 0.7376 |
| 1.1601 | 15.0 | 120 | 1.2734 | 0.7341 |
| 1.1749 | 16.0 | 128 | 1.2456 | 0.7321 |
| 1.1432 | 17.0 | 136 | 1.1806 | 0.7382 |
| 1.2102 | 17.5333 | 140 | 1.2490 | 0.7374 |
Framework versions
- Transformers 4.48.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.21.0
- Downloads last month
- -