BERT_ep8_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: 0.1511
- Precision: 0.8632
- Recall: 0.8810
- F1: 0.8720
- Accuracy: 0.9767
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: 8
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 467 | 0.0949 | 0.8056 | 0.8604 | 0.8321 | 0.9704 |
0.101 | 2.0 | 934 | 0.0978 | 0.8174 | 0.8876 | 0.8511 | 0.9725 |
0.0544 | 3.0 | 1401 | 0.0959 | 0.8384 | 0.8785 | 0.8580 | 0.9739 |
0.0331 | 4.0 | 1868 | 0.1018 | 0.8497 | 0.8841 | 0.8665 | 0.9749 |
0.0182 | 5.0 | 2335 | 0.1375 | 0.8658 | 0.8686 | 0.8672 | 0.9758 |
0.0133 | 6.0 | 2802 | 0.1458 | 0.8547 | 0.8843 | 0.8692 | 0.9753 |
0.0064 | 7.0 | 3269 | 0.1418 | 0.8628 | 0.8813 | 0.8719 | 0.9763 |
0.0041 | 8.0 | 3736 | 0.1511 | 0.8632 | 0.8810 | 0.8720 | 0.9767 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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