BERT_ep8_lr2
This model is a fine-tuned version of ajtamayoh/NER_EHR_Spanish_model_Mulitlingual_BERT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0940
- Precision: 0.8489
- Recall: 0.8716
- F1: 0.8601
- Accuracy: 0.9771
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: 5e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 467 | 0.0850 | 0.8142 | 0.8377 | 0.8257 | 0.9730 |
0.1137 | 2.0 | 934 | 0.0799 | 0.8402 | 0.8534 | 0.8467 | 0.9757 |
0.0746 | 3.0 | 1401 | 0.0825 | 0.8416 | 0.8614 | 0.8514 | 0.9765 |
0.0588 | 4.0 | 1868 | 0.0863 | 0.8560 | 0.8652 | 0.8606 | 0.9769 |
0.0482 | 5.0 | 2335 | 0.0885 | 0.8553 | 0.8646 | 0.8599 | 0.9771 |
0.0402 | 6.0 | 2802 | 0.0893 | 0.8520 | 0.8668 | 0.8593 | 0.9776 |
0.0362 | 7.0 | 3269 | 0.0916 | 0.8480 | 0.8726 | 0.8601 | 0.9772 |
0.0336 | 8.0 | 3736 | 0.0940 | 0.8489 | 0.8716 | 0.8601 | 0.9771 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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