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# biomedNLP-text-classifier

This model is a fine-tuned version of [microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2520
- Precision: 0.9256
- Recall: 0.9251
- Accuracy: 0.9251
- F1: 0.9253

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|
| No log        | 1.0   | 154  | 0.2925          | 0.8883    | 0.8880 | 0.8877   | 0.8881 |
| No log        | 2.0   | 308  | 0.2752          | 0.9051    | 0.8903 | 0.8910   | 0.8920 |
| No log        | 3.0   | 462  | 0.2553          | 0.9252    | 0.9201 | 0.9203   | 0.9206 |
| 0.2957        | 4.0   | 616  | 0.2520          | 0.9256    | 0.9251 | 0.9251   | 0.9253 |
| 0.2957        | 5.0   | 770  | 0.2689          | 0.9261    | 0.9260 | 0.9260   | 0.9260 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "accuracy", "f1"], "base_model": "microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract", "model-index": [{"name": "biomedNLP-text-classifier", "results": []}]}
transformers tf tensorboard safetensors bert text-classification generated_from_trainer base_model:microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract license:mit autotrain_compatible endpoints_compatible region:us