CeLLaTe3.0_no_vague_pubmed
This model is a fine-tuned version of Mardiyyah/cellate1.0-tapt_freeze_llrd_ww_mask-LR_2e-05 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2279
- Precision: 0.7706
- Recall: 0.8273
- F1: 0.7979
- Accuracy: 0.9672
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-08 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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.8103 | 1.0 | 402 | 0.1761 | 0.5832 | 0.7740 | 0.6652 | 0.9529 |
| 0.1291 | 2.0 | 804 | 0.1448 | 0.6999 | 0.7842 | 0.7396 | 0.9618 |
| 0.0705 | 3.0 | 1206 | 0.1829 | 0.6816 | 0.8217 | 0.7451 | 0.9572 |
| 0.0393 | 4.0 | 1608 | 0.1870 | 0.6990 | 0.7938 | 0.7434 | 0.9620 |
| 0.0253 | 5.0 | 2010 | 0.2277 | 0.7128 | 0.7826 | 0.7461 | 0.9612 |
| 0.0155 | 6.0 | 2412 | 0.2306 | 0.7044 | 0.7877 | 0.7437 | 0.9641 |
| 0.0115 | 7.0 | 2814 | 0.2300 | 0.7706 | 0.8273 | 0.7979 | 0.9672 |
| 0.0082 | 8.0 | 3216 | 0.2642 | 0.7331 | 0.8121 | 0.7706 | 0.9644 |
| 0.006 | 9.0 | 3618 | 0.2808 | 0.7183 | 0.7887 | 0.7519 | 0.9634 |
| 0.0046 | 10.0 | 4020 | 0.2718 | 0.7441 | 0.8151 | 0.7780 | 0.9648 |
| 0.0034 | 11.0 | 4422 | 0.2977 | 0.7215 | 0.8172 | 0.7664 | 0.9635 |
| 0.0024 | 12.0 | 4824 | 0.3096 | 0.7462 | 0.8151 | 0.7791 | 0.9637 |
| 0.0022 | 13.0 | 5226 | 0.3120 | 0.7335 | 0.8217 | 0.7751 | 0.9643 |
| 0.0017 | 14.0 | 5628 | 0.3049 | 0.7420 | 0.8238 | 0.7807 | 0.9652 |
| 0.0014 | 15.0 | 6030 | 0.3178 | 0.7311 | 0.8273 | 0.7763 | 0.9649 |
| 0.0014 | 16.0 | 6432 | 0.3172 | 0.7349 | 0.8167 | 0.7736 | 0.9647 |
| 0.0009 | 17.0 | 6834 | 0.3216 | 0.7516 | 0.8192 | 0.7840 | 0.9644 |
| 0.0007 | 18.0 | 7236 | 0.3236 | 0.7441 | 0.8228 | 0.7815 | 0.9655 |
| 0.0007 | 19.0 | 7638 | 0.3225 | 0.7543 | 0.8217 | 0.7866 | 0.9657 |
| 0.0008 | 20.0 | 8040 | 0.3233 | 0.7513 | 0.8207 | 0.7845 | 0.9655 |
Framework versions
- Transformers 4.48.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.21.0
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