BERT_ep7_lr4
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: 0.1921
- Precision: 0.6693
- Recall: 0.7023
- F1: 0.6854
- Accuracy: 0.9474
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-08
- 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 | 0.2637 | 0.6599 | 0.6468 | 0.6533 | 0.9429 |
0.2761 | 2.0 | 934 | 0.2367 | 0.6611 | 0.6683 | 0.6647 | 0.9440 |
0.2405 | 3.0 | 1401 | 0.2181 | 0.6579 | 0.6814 | 0.6694 | 0.9452 |
0.2172 | 4.0 | 1868 | 0.2057 | 0.6656 | 0.6928 | 0.6789 | 0.9462 |
0.2004 | 5.0 | 2335 | 0.1978 | 0.6698 | 0.6999 | 0.6845 | 0.9470 |
0.1935 | 6.0 | 2802 | 0.1934 | 0.6701 | 0.7020 | 0.6857 | 0.9473 |
0.1947 | 7.0 | 3269 | 0.1921 | 0.6693 | 0.7023 | 0.6854 | 0.9474 |
Framework versions
- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
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