---
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_top20
  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-20

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: 0.1968
- Accuracy: 0.9607
- F1: 0.9610
- Precision: 0.9627
- Recall: 0.9607

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.8509        | 1.0   | 584  | 0.6074          | 0.8533   | 0.8547 | 0.8792    | 0.8533 |
| 0.5597        | 2.0   | 1168 | 0.3286          | 0.9167   | 0.9176 | 0.9303    | 0.9167 |
| 0.2302        | 3.0   | 1752 | 0.2387          | 0.9413   | 0.9422 | 0.9491    | 0.9413 |
| 0.1052        | 4.0   | 2336 | 0.2314          | 0.9487   | 0.9494 | 0.9528    | 0.9487 |
| 0.0662        | 5.0   | 2920 | 0.1968          | 0.9607   | 0.9610 | 0.9627    | 0.9607 |


### Framework versions

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