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# roberta-base-bne-finetuned-detests-wandb

This model is a fine-tuned version of [BSC-TeMU/roberta-base-bne](https://huggingface.co/BSC-TeMU/roberta-base-bne) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3838
- Accuracy: 0.8543
- F1-score: 0.7832
- Precision: 0.7983
- Recall: 0.7712
- Auc: 0.7712

## 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: 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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-score | Precision | Recall | Auc    |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|:------:|
| 0.3307        | 1.0   | 87   | 0.3771          | 0.8560   | 0.7659   | 0.8224    | 0.7367 | 0.7367 |
| 0.1068        | 2.0   | 174  | 0.3838          | 0.8543   | 0.7832   | 0.7983    | 0.7712 | 0.7712 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "precision", "recall"], "base_model": "BSC-TeMU/roberta-base-bne", "model-index": [{"name": "roberta-base-bne-finetuned-detests-wandb", "results": []}]}
transformers tensorboard safetensors roberta text-classification generated_from_trainer base_model:BSC-TeMU/roberta-base-bne license:apache-2.0 autotrain_compatible endpoints_compatible region:us