---
license: mit
base_model: classla/xlm-roberta-base-multilingual-text-genre-classifier
tags:
- Italian
- legal ruling
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: ribesstefano/RuleBert-v0.0-k0
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ribesstefano/RuleBert-v0.0-k0

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: 0.3777
- F1: 0.5004
- Roc Auc: 0.6722
- Accuracy: 0.0375

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.3811        | 0.88  | 50   | 0.3716          | 0.4904 | 0.6685  | 0.0583   |
| 0.3257        | 1.77  | 100  | 0.3708          | 0.4953 | 0.6701  | 0.0583   |
| 0.3178        | 2.65  | 150  | 0.3745          | 0.4977 | 0.6712  | 0.0417   |
| 0.3091        | 3.54  | 200  | 0.3750          | 0.4989 | 0.6719  | 0.0417   |
| 0.3115        | 4.42  | 250  | 0.3768          | 0.5007 | 0.6724  | 0.0417   |
| 0.3092        | 5.31  | 300  | 0.3762          | 0.5021 | 0.6727  | 0.0458   |
| 0.3057        | 6.19  | 350  | 0.3772          | 0.5005 | 0.6723  | 0.0375   |
| 0.3062        | 7.08  | 400  | 0.3777          | 0.5002 | 0.6721  | 0.0417   |
| 0.3086        | 7.96  | 450  | 0.3777          | 0.5005 | 0.6723  | 0.0417   |
| 0.3075        | 8.85  | 500  | 0.3777          | 0.5004 | 0.6722  | 0.0375   |


### Framework versions

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