BERT_ep8_lr3
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: 0.1048
- Precision: 0.7641
- Recall: 0.8235
- F1: 0.7927
- Accuracy: 0.9666
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-07
- 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 | 0.1361 | 0.6936 | 0.7475 | 0.7195 | 0.9568 |
0.1814 | 2.0 | 934 | 0.1187 | 0.7168 | 0.7849 | 0.7493 | 0.9613 |
0.1202 | 3.0 | 1401 | 0.1118 | 0.7361 | 0.7990 | 0.7662 | 0.9635 |
0.1109 | 4.0 | 1868 | 0.1088 | 0.7508 | 0.8072 | 0.7780 | 0.9650 |
0.1006 | 5.0 | 2335 | 0.1069 | 0.7570 | 0.8158 | 0.7853 | 0.9657 |
0.0987 | 6.0 | 2802 | 0.1056 | 0.7604 | 0.8191 | 0.7887 | 0.9662 |
0.0969 | 7.0 | 3269 | 0.1050 | 0.7651 | 0.8224 | 0.7927 | 0.9665 |
0.0993 | 8.0 | 3736 | 0.1048 | 0.7641 | 0.8235 | 0.7927 | 0.9666 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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