---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: model
  results: []
datasets:
- simoneteglia/europarl_for_language_detection_10k
language:
- en
- it
- de
- nl
- lt
- es
- sv
- el
- pl
- sl
- hu
- bg
- fi
- pt
- sk
- da
- cs
- et
- lv
- ro
- fr
---

<!-- 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. -->

# model

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the [Europarl language detection](https://huggingface.co/datasets/simoneteglia/europarl_for_language_detection_10k) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0237
- Accuracy: 0.9967
- F1: 0.9967

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 256
- eval_batch_size: 512
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 821  | 0.0270          | 0.9965   | 0.9965 |
| 0.2372        | 2.0   | 1642 | 0.0237          | 0.9967   | 0.9967 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3