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BERT_ep6_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: 0.1977
- Precision: 0.6776
- Recall: 0.7052
- F1: 0.6911
- Accuracy: 0.9476
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: 6
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 467 | 0.2591 | 0.6800 | 0.6636 | 0.6717 | 0.9439 |
0.2747 | 2.0 | 934 | 0.2325 | 0.6757 | 0.6824 | 0.6790 | 0.9452 |
0.2444 | 3.0 | 1401 | 0.2158 | 0.6761 | 0.6955 | 0.6857 | 0.9465 |
0.2184 | 4.0 | 1868 | 0.2052 | 0.6780 | 0.7025 | 0.6900 | 0.9471 |
0.2087 | 5.0 | 2335 | 0.1994 | 0.6777 | 0.7049 | 0.6910 | 0.9475 |
0.1984 | 6.0 | 2802 | 0.1977 | 0.6776 | 0.7052 | 0.6911 | 0.9476 |
Framework versions
- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.2