BERT_ep7_lr1
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: 0.1449
- Precision: 0.8612
- Recall: 0.8723
- F1: 0.8667
- Accuracy: 0.9764
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-05
- 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: 7
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 467 | 0.0884 | 0.8278 | 0.8351 | 0.8314 | 0.9737 |
0.1032 | 2.0 | 934 | 0.0841 | 0.8327 | 0.8591 | 0.8457 | 0.9739 |
0.0556 | 3.0 | 1401 | 0.0941 | 0.8699 | 0.8654 | 0.8677 | 0.9762 |
0.0317 | 4.0 | 1868 | 0.1146 | 0.8697 | 0.8654 | 0.8676 | 0.9764 |
0.0202 | 5.0 | 2335 | 0.1323 | 0.8736 | 0.8621 | 0.8678 | 0.9767 |
0.0114 | 6.0 | 2802 | 0.1385 | 0.8563 | 0.8766 | 0.8663 | 0.9758 |
0.0064 | 7.0 | 3269 | 0.1449 | 0.8612 | 0.8723 | 0.8667 | 0.9764 |
Framework versions
- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
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