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# roberta-base-autextification

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the au_tex_tification dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3253
- Accuracy: 0.6297
- Roc Auc: 0.8980

## 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
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Roc Auc |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------:|
| 0.4844        | 1.0   | 3385  | 0.2904          | 0.9057   | 0.9745  |
| 0.1311        | 2.0   | 6770  | 0.4360          | 0.8997   | 0.9817  |
| 0.1576        | 3.0   | 10155 | 0.5514          | 0.9088   | 0.9837  |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.1

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["au_tex_tification"], "metrics": ["accuracy"], "base_model": "roberta-base", "model-index": [{"name": "roberta-base-autextification", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "au_tex_tification", "type": "au_tex_tification", "config": "detection_en", "split": "train", "args": "detection_en"}, "metrics": [{"type": "accuracy", "value": 0.6296720410406742, "name": "Accuracy"}]}]}]}
transformers safetensors roberta text-classification generated_from_trainer dataset:au_tex_tification base_model:roberta-base license:mit model-index autotrain_compatible endpoints_compatible region:us