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# ClinicalBERT_BioNLP13CG_NER_new

This model is a fine-tuned version of [medicalai/ClinicalBERT](https://huggingface.co/medicalai/ClinicalBERT) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2843
- Precision: 0.7607
- Recall: 0.7531
- F1: 0.7569
- Accuracy: 0.9232

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 191  | 0.3654          | 0.7025    | 0.6984 | 0.7005 | 0.9035   |
| No log        | 2.0   | 382  | 0.2958          | 0.7563    | 0.7429 | 0.7495 | 0.9203   |
| 0.4451        | 3.0   | 573  | 0.2843          | 0.7607    | 0.7531 | 0.7569 | 0.9232   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

{"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "medicalai/ClinicalBERT", "model-index": [{"name": "ClinicalBERT_BioNLP13CG_NER_new", "results": []}]}
transformers tensorboard safetensors distilbert token-classification generated_from_trainer base_model:medicalai/ClinicalBERT autotrain_compatible endpoints_compatible region:us