bert-finetuned-ner-clinical-plncmm-large-21
This model is a fine-tuned version of plncmm/beto-clinical-wl-es on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2547
- Precision: 0.7735
- Recall: 0.8321
- F1: 0.8017
- Accuracy: 0.9358
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: 3e-05
- train_batch_size: 8
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 400
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.236 | 1.0 | 1714 | 0.2390 | 0.7219 | 0.8106 | 0.7637 | 0.9257 |
0.156 | 2.0 | 3428 | 0.2498 | 0.7413 | 0.8271 | 0.7818 | 0.9306 |
0.096 | 3.0 | 5142 | 0.2547 | 0.7735 | 0.8321 | 0.8017 | 0.9358 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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