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# roBERTa

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: 0.7581
- Accuracy: 0.8307

## 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: 3e-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: 15750
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.5914        | 1.0   | 5250  | 0.9909          | 0.5628   |
| 0.5792        | 2.0   | 10500 | 0.9334          | 0.7436   |
| 0.5905        | 3.0   | 15750 | 0.5907          | 0.9454   |
| 0.6576        | 4.0   | 21000 | 1.2153          | 0.5174   |
| 0.5898        | 5.0   | 26250 | 0.6647          | 0.7933   |
| 0.5896        | 6.0   | 31500 | 0.7914          | 0.8132   |
| 0.6578        | 7.0   | 36750 | 0.6739          | 0.3249   |
| 0.5846        | 8.0   | 42000 | 0.6237          | 0.8294   |
| 0.549         | 9.0   | 47250 | 0.7103          | 0.8514   |
| 0.5497        | 10.0  | 52500 | 0.7581          | 0.8307   |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "roberta-base", "model-index": [{"name": "roBERTa", "results": []}]}
transformers tensorboard safetensors roberta text-classification generated_from_trainer base_model:roberta-base license:mit autotrain_compatible endpoints_compatible region:us