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# ribesstefano/RuleBert-v0.1-k2

This model is a fine-tuned version of [classla/xlm-roberta-base-multilingual-text-genre-classifier](https://huggingface.co/classla/xlm-roberta-base-multilingual-text-genre-classifier) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3049
- F1: 0.5103
- Roc Auc: 0.6747
- Accuracy: 0.0

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.3592        | 0.14  | 250  | 0.3131          | 0.5179 | 0.6796  | 0.0      |
| 0.3369        | 0.27  | 500  | 0.3063          | 0.5109 | 0.6758  | 0.0      |
| 0.3352        | 0.41  | 750  | 0.3087          | 0.5110 | 0.6750  | 0.0      |
| 0.3283        | 0.54  | 1000 | 0.3042          | 0.5105 | 0.6749  | 0.0      |
| 0.3246        | 0.68  | 1250 | 0.3068          | 0.5101 | 0.6747  | 0.0      |
| 0.3264        | 0.82  | 1500 | 0.3028          | 0.5152 | 0.6771  | 0.0      |
| 0.3365        | 0.95  | 1750 | 0.3051          | 0.5103 | 0.6747  | 0.0      |
| 0.3269        | 1.09  | 2000 | 0.3042          | 0.5103 | 0.6747  | 0.0      |
| 0.3173        | 1.22  | 2250 | 0.3059          | 0.5103 | 0.6747  | 0.0      |
| 0.3127        | 1.36  | 2500 | 0.3053          | 0.5110 | 0.6750  | 0.0      |
| 0.3211        | 1.49  | 2750 | 0.3067          | 0.5103 | 0.6747  | 0.0      |
| 0.3155        | 1.63  | 3000 | 0.3067          | 0.5103 | 0.6747  | 0.0      |
| 0.319         | 1.77  | 3250 | 0.3051          | 0.5103 | 0.6747  | 0.0      |
| 0.3286        | 1.9   | 3500 | 0.3042          | 0.5103 | 0.6747  | 0.0      |
| 0.3243        | 2.04  | 3750 | 0.3051          | 0.5103 | 0.6747  | 0.0      |
| 0.3111        | 2.17  | 4000 | 0.3049          | 0.5103 | 0.6747  | 0.0      |


### Framework versions

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

{"license": "mit", "tags": ["Italian", "legal ruling", "generated_from_trainer"], "metrics": ["f1", "accuracy"], "base_model": "classla/xlm-roberta-base-multilingual-text-genre-classifier", "model-index": [{"name": "ribesstefano/RuleBert-v0.1-k2", "results": []}]}
transformers tensorboard safetensors xlm-roberta text-classification Italian legal ruling generated_from_trainer base_model:classla/xlm-roberta-base-multilingual-text-genre-classifier license:mit autotrain_compatible endpoints_compatible region:us