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---
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-v0.1-k0
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-v0.1-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: 0.3765
- F1: 0.5087
- Roc Auc: 0.6757
- Accuracy: 0.0333
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.3621 | 0.14 | 250 | 0.3791 | 0.4861 | 0.6678 | 0.0458 |
| 0.3199 | 0.28 | 500 | 0.3754 | 0.4969 | 0.6730 | 0.0375 |
| 0.3135 | 0.41 | 750 | 0.3785 | 0.4965 | 0.6715 | 0.0458 |
| 0.3176 | 0.55 | 1000 | 0.3755 | 0.4988 | 0.6725 | 0.0333 |
| 0.3056 | 0.69 | 1250 | 0.3734 | 0.5100 | 0.6756 | 0.0667 |
| 0.3016 | 0.83 | 1500 | 0.3749 | 0.5076 | 0.6755 | 0.0333 |
| 0.3044 | 0.97 | 1750 | 0.3763 | 0.5014 | 0.6738 | 0.0125 |
| 0.3009 | 1.11 | 2000 | 0.3781 | 0.5073 | 0.6751 | 0.0333 |
| 0.3044 | 1.24 | 2250 | 0.3782 | 0.5089 | 0.6755 | 0.0417 |
| 0.2979 | 1.38 | 2500 | 0.3770 | 0.5047 | 0.6745 | 0.0167 |
| 0.2977 | 1.52 | 2750 | 0.3772 | 0.5114 | 0.6764 | 0.0417 |
| 0.2998 | 1.66 | 3000 | 0.3747 | 0.5107 | 0.6762 | 0.0375 |
| 0.2916 | 1.8 | 3250 | 0.3741 | 0.5096 | 0.6758 | 0.0375 |
| 0.3107 | 1.94 | 3500 | 0.3757 | 0.5056 | 0.6748 | 0.0208 |
| 0.3023 | 2.07 | 3750 | 0.3767 | 0.5069 | 0.6752 | 0.025 |
| 0.3069 | 2.21 | 4000 | 0.3765 | 0.5087 | 0.6757 | 0.0333 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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