---
library_name: transformers
base_model: MatteoFasulo/xlm-roberta-base_69
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: xlm-roberta-base_69
  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. -->

# xlm-roberta-base_69

This model is a fine-tuned version of [MatteoFasulo/xlm-roberta-base_69](https://huggingface.co/MatteoFasulo/xlm-roberta-base_69) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4990
- F1-score: 0.8549
- Accuracy: 0.8549
- Precision: 0.8549
- Recall: 0.8550

## 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: 16
- eval_batch_size: 16
- seed: 69
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1-score | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|
| No log        | 1.0   | 379  | 0.4454          | 0.8611   | 0.8611   | 0.8620    | 0.8615 |
| 0.3451        | 2.0   | 758  | 0.4597          | 0.8469   | 0.8472   | 0.8488    | 0.8467 |
| 0.3027        | 3.0   | 1137 | 0.4418          | 0.8472   | 0.8472   | 0.8474    | 0.8474 |
| 0.2931        | 4.0   | 1516 | 0.5016          | 0.8392   | 0.8395   | 0.8444    | 0.8404 |
| 0.2931        | 5.0   | 1895 | 0.4875          | 0.8565   | 0.8565   | 0.8573    | 0.8569 |
| 0.2469        | 6.0   | 2274 | 0.4990          | 0.8549   | 0.8549   | 0.8549    | 0.8550 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0