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# roberta-base-finetuned

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2253
- F1: 0.9351
- Precision: 0.9356
- Recall: 0.935

## 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: 8
- eval_batch_size: 8
- 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|
| 0.426         | 1.0   | 1250 | 0.2329          | 0.9206 | 0.9218    | 0.92   |
| 0.6112        | 2.0   | 2500 | 0.3298          | 0.9212 | 0.9293    | 0.92   |
| 0.2796        | 3.0   | 3750 | 0.2613          | 0.9248 | 0.9267    | 0.926  |
| 0.0908        | 4.0   | 5000 | 0.1831          | 0.9419 | 0.9431    | 0.942  |
| 0.101         | 5.0   | 6250 | 0.2253          | 0.9351 | 0.9356    | 0.935  |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["f1", "precision", "recall"], "base_model": "roberta-base", "model-index": [{"name": "roberta-base-finetuned", "results": []}]}
transformers pytorch roberta text-classification generated_from_trainer base_model:roberta-base license:mit autotrain_compatible endpoints_compatible region:us