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bert-finetuned-ner-clinical-plncmm-large-2
This model is a fine-tuned version of plncmm/beto-clinical-wl-es on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2438
- Precision: 0.7552
- Recall: 0.8315
- F1: 0.7915
- Accuracy: 0.9335
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.337 | 1.0 | 857 | 0.2200 | 0.7204 | 0.8161 | 0.7653 | 0.9278 |
| 0.1605 | 2.0 | 1714 | 0.2386 | 0.7476 | 0.8293 | 0.7864 | 0.9310 |
| 0.105 | 3.0 | 2571 | 0.2438 | 0.7552 | 0.8315 | 0.7915 | 0.9335 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
