---
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-k2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ribesstefano/RuleBert-v0.4-k2

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: 0.3021
- F1: 0.5409
- Roc Auc: 0.6961
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.3653        | 0.12  | 250  | 0.3184          | 0.5103 | 0.6747  | 0.0      |
| 0.3513        | 0.24  | 500  | 0.3022          | 0.5103 | 0.6747  | 0.0      |
| 0.3758        | 0.36  | 750  | 0.2956          | 0.5103 | 0.6747  | 0.0      |
| 0.355         | 0.48  | 1000 | 0.3073          | 0.5409 | 0.6961  | 0.0      |
| 0.3499        | 0.6   | 1250 | 0.3098          | 0.5103 | 0.6747  | 0.0      |
| 0.3484        | 0.72  | 1500 | 0.3009          | 0.5103 | 0.6747  | 0.0      |
| 0.3394        | 0.85  | 1750 | 0.2978          | 0.5103 | 0.6747  | 0.0      |
| 0.3469        | 0.97  | 2000 | 0.2975          | 0.5103 | 0.6747  | 0.0      |
| 0.3522        | 1.09  | 2250 | 0.3021          | 0.5409 | 0.6961  | 0.0      |


### Framework versions

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