BERT_ep5_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: 0.0922
- Precision: 0.8259
- Recall: 0.8778
- F1: 0.8511
- Accuracy: 0.9740
Model description
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Intended uses & limitations
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Training and evaluation data
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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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 467 | 0.0878 | 0.7978 | 0.8576 | 0.8266 | 0.9708 |
0.1112 | 2.0 | 934 | 0.0861 | 0.8072 | 0.8780 | 0.8411 | 0.9718 |
0.0746 | 3.0 | 1401 | 0.0867 | 0.8212 | 0.8756 | 0.8475 | 0.9736 |
0.0586 | 4.0 | 1868 | 0.0901 | 0.8239 | 0.8780 | 0.8501 | 0.9737 |
0.0539 | 5.0 | 2335 | 0.0922 | 0.8259 | 0.8778 | 0.8511 | 0.9740 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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