---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: trainer_output
  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. -->

# trainer_output

This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0023
- Accuracy: 0.8598
- F1: 0.8668
- Precision: 0.8770
- Recall: 0.8598

## 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: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 0.2439 | 20   | 1.6724          | 0.8537   | 0.8597 | 0.8721    | 0.8537 |
| No log        | 0.4878 | 40   | 2.1847          | 0.8598   | 0.8618 | 0.8640    | 0.8598 |
| 0.3126        | 0.7317 | 60   | 2.0168          | 0.8598   | 0.8630 | 0.8673    | 0.8598 |
| 0.3126        | 0.9756 | 80   | 2.4119          | 0.8780   | 0.8804 | 0.8904    | 0.8780 |
| 0.2521        | 1.2195 | 100  | 2.2020          | 0.8902   | 0.8884 | 0.8899    | 0.8902 |
| 0.2521        | 1.4634 | 120  | 2.2252          | 0.8902   | 0.8893 | 0.8908    | 0.8902 |
| 0.2521        | 1.7073 | 140  | 1.9534          | 0.8476   | 0.8579 | 0.8738    | 0.8476 |
| 0.2102        | 1.9512 | 160  | 2.0566          | 0.8963   | 0.8952 | 0.8948    | 0.8963 |
| 0.2102        | 2.1951 | 180  | 2.1647          | 0.8659   | 0.8714 | 0.8799    | 0.8659 |
| 0.0475        | 2.4390 | 200  | 2.2178          | 0.8659   | 0.8713 | 0.8795    | 0.8659 |
| 0.0475        | 2.6829 | 220  | 2.2616          | 0.8659   | 0.8713 | 0.8795    | 0.8659 |
| 0.0475        | 2.9268 | 240  | 2.2667          | 0.8659   | 0.8713 | 0.8795    | 0.8659 |


### Framework versions

- Transformers 4.56.2
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1