---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: xlm_roberta_top10
  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-csfd-10

This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1591
- Accuracy: 0.9613
- F1: 0.9617
- Precision: 0.9630
- Recall: 0.9613

## 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: 12
- eval_batch_size: 12
- seed: 42
- 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 292  | 0.5781          | 0.8427   | 0.8432 | 0.8710    | 0.8427 |
| 1.0772        | 2.0   | 584  | 0.2642          | 0.9213   | 0.9213 | 0.9327    | 0.9213 |
| 1.0772        | 3.0   | 876  | 0.2215          | 0.9413   | 0.9408 | 0.9484    | 0.9413 |
| 0.1222        | 4.0   | 1168 | 0.1546          | 0.96     | 0.9604 | 0.9618    | 0.9600 |
| 0.1222        | 5.0   | 1460 | 0.1591          | 0.9613   | 0.9617 | 0.9630    | 0.9613 |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.4.0
- Tokenizers 0.21.1