bert-finetuned-ner-clinical-plncmm-large-7
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: 0.2317
- Precision: 0.7503
- Recall: 0.8227
- F1: 0.7848
- Accuracy: 0.9326
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: 32
- 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: 500
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 429 | 0.2497 | 0.6860 | 0.7794 | 0.7297 | 0.9201 |
0.6187 | 2.0 | 858 | 0.2391 | 0.7384 | 0.8134 | 0.7741 | 0.9293 |
0.1936 | 3.0 | 1287 | 0.2317 | 0.7503 | 0.8227 | 0.7848 | 0.9326 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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