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bert-finetuned-ner-clinical-plncmm-large-1
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: 0.2406
- Precision: 0.7503
- Recall: 0.8227
- F1: 0.7848
- Accuracy: 0.9318
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: 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 |
---|---|---|---|---|---|---|---|
0.3906 | 1.0 | 857 | 0.2271 | 0.7130 | 0.8101 | 0.7585 | 0.9253 |
0.1758 | 2.0 | 1714 | 0.2378 | 0.7460 | 0.8222 | 0.7822 | 0.9290 |
0.125 | 3.0 | 2571 | 0.2406 | 0.7503 | 0.8227 | 0.7848 | 0.9318 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3