EXP_5_MULTI_DISEASE_BIO_FULL-bert-base-cased
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1490
- Precision: 0.6542
- Recall: 0.5823
- F1: 0.6161
- Accuracy: 0.9598
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: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1856 | 1.0 | 220 | 0.1754 | 0.6449 | 0.4784 | 0.5493 | 0.9557 |
| 0.1492 | 2.0 | 440 | 0.1528 | 0.6556 | 0.5669 | 0.6080 | 0.9591 |
| 0.134 | 3.0 | 660 | 0.1490 | 0.6542 | 0.5823 | 0.6161 | 0.9598 |
Framework versions
- Transformers 4.57.2
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
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Model tree for irebil/EXP_3_MULTI_DISEASE_BIO_FULL-bert-base-cased
Base model
google-bert/bert-base-cased