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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-v0.0-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-v0.0-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
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