---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: language_detector
  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. -->

# language_detector

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: 0.0019
- Accuracy: 0.9998
- F1 Macro: 0.9994
- Precision Macro: 0.9994
- Recall Macro: 0.9994

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|
| 0.0026        | 1.0   | 9188  | 0.0044          | 0.9995   | 0.9986   | 0.9993          | 0.9979       |
| 0.0041        | 2.0   | 18376 | 0.0094          | 0.9990   | 0.9970   | 0.9946          | 0.9994       |
| 0.0001        | 3.0   | 27564 | 0.0050          | 0.9993   | 0.9981   | 0.9970          | 0.9992       |
| 0.0056        | 4.0   | 36752 | 0.0037          | 0.9995   | 0.9986   | 0.9980          | 0.9993       |
| 0.0           | 5.0   | 45940 | 0.0019          | 0.9998   | 0.9994   | 0.9994          | 0.9994       |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1