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---
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-v0.3-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-v0.3-k0
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: 0.3650
- F1: 0.4972
- Roc Auc: 0.6720
- 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: 5e-06
- train_batch_size: 2
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 8000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Accuracy | F1 | Validation Loss | Roc Auc |
|:-------------:|:-----:|:----:|:--------:|:------:|:---------------:|:-------:|
| 0.422 | 0.06 | 250 | 0.0 | 0.4972 | 0.3994 | 0.6720 |
| 0.3606 | 0.12 | 500 | 0.3604 | 0.4972 | 0.6720 | 0.0 |
| 0.3333 | 0.19 | 750 | 0.3548 | 0.4972 | 0.6720 | 0.0 |
| 0.3304 | 0.25 | 1000 | 0.3563 | 0.4972 | 0.6720 | 0.0 |
| 0.3416 | 0.31 | 1250 | 0.3628 | 0.4972 | 0.6720 | 0.0 |
| 0.3558 | 0.37 | 1500 | 0.3650 | 0.4972 | 0.6720 | 0.0 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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