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# distilbert-base-uncased-finetuned-discharge

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9049
- Accuracy: 0.7425
- F1: 0.7419

## 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: 5e-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: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 814  | 0.5448          | 0.7052   | 0.7020 |
| 0.5626        | 2.0   | 1628 | 0.5420          | 0.7323   | 0.7322 |
| 0.5626        | 3.0   | 2442 | 0.5337          | 0.7535   | 0.7516 |
| 0.3498        | 4.0   | 3256 | 0.6277          | 0.7491   | 0.7482 |
| 0.3498        | 5.0   | 4070 | 0.7642          | 0.7432   | 0.7421 |
| 0.2189        | 6.0   | 4884 | 0.9049          | 0.7425   | 0.7419 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "distilbert-base-uncased-finetuned-discharge", "results": []}]}
transformers tensorboard safetensors distilbert text-classification generated_from_trainer base_model:distilbert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us