---
license: mit
base_model: papluca/xlm-roberta-base-language-detection
tags:
- Italian
- legal ruling
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: ribesstefano/RuleBert-v0.4-k4
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# ribesstefano/RuleBert-v0.4-k4

This model is a fine-tuned version of [papluca/xlm-roberta-base-language-detection](https://huggingface.co/papluca/xlm-roberta-base-language-detection) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3517
- F1: 0.5190
- Roc Auc: 0.6864
- 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: 0.0005
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.3447        | 0.12  | 250  | 0.3402          | 0.4810 | 0.6688  | 0.0      |
| 0.3501        | 0.24  | 500  | 0.3548          | 0.4884 | 0.6786  | 0.0      |
| 0.3433        | 0.36  | 750  | 0.3596          | 0.4946 | 0.6885  | 0.0      |
| 0.3521        | 0.48  | 1000 | 0.3762          | 0.4861 | 0.6648  | 0.0      |
| 0.3466        | 0.6   | 1250 | 0.3496          | 0.4861 | 0.6648  | 0.0      |
| 0.3285        | 0.72  | 1500 | 0.3519          | 0.4861 | 0.6648  | 0.0      |
| 0.333         | 0.84  | 1750 | 0.3550          | 0.4861 | 0.6648  | 0.0      |
| 0.3268        | 0.96  | 2000 | 0.3436          | 0.5190 | 0.6864  | 0.0      |
| 0.3376        | 1.08  | 2250 | 0.3637          | 0.4978 | 0.6891  | 0.0      |
| 0.3319        | 1.19  | 2500 | 0.3459          | 0.5190 | 0.6864  | 0.0      |
| 0.3169        | 1.31  | 2750 | 0.3430          | 0.4810 | 0.6688  | 0.0      |
| 0.3293        | 1.43  | 3000 | 0.3480          | 0.4861 | 0.6648  | 0.0      |
| 0.3293        | 1.55  | 3250 | 0.3517          | 0.5190 | 0.6864  | 0.0      |


### Framework versions

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