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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
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