ClinicalBERT_JNLPBA_NER_new
This model is a fine-tuned version of medicalai/ClinicalBERT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1699
- Precision: 0.7855
- Recall: 0.8043
- F1: 0.7948
- Accuracy: 0.9439
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.2204 | 1.0 | 1164 | 0.1821 | 0.7652 | 0.7719 | 0.7685 | 0.9380 |
| 0.1618 | 2.0 | 2328 | 0.1716 | 0.7884 | 0.7886 | 0.7885 | 0.9426 |
| 0.1338 | 3.0 | 3492 | 0.1699 | 0.7855 | 0.8043 | 0.7948 | 0.9439 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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Model tree for judithrosell/ClinicalBERT_JNLPBA_NER_new
Base model
medicalai/ClinicalBERT