---
language:
- br
license: apache-2.0
tags:
- generated_from_trainer
base_model: facebook/wav2vec2-xls-r-300m
datasets:
- mozilla-foundation/common_voice_15_0
metrics:
- wer
model-index:
- name: wav2vec2-xls-r-300m-breton
  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. -->

# wav2vec2-xls-r-300m-breton

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co./facebook/wav2vec2-xls-r-300m) on the [mozilla-foundation/common_voice_15_0]() dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9939
- Wer: 0.4680
- Cer: 0.1711

## 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: 6e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.08
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 10.4347       | 2.56  | 250  | 3.7906          | 1.0    | 1.0    |
| 3.2144        | 5.13  | 500  | 3.0622          | 1.0    | 1.0    |
| 2.6193        | 7.69  | 750  | 1.6063          | 0.9122 | 0.4042 |
| 1.3658        | 10.26 | 1000 | 1.0917          | 0.7061 | 0.2474 |
| 0.9614        | 12.82 | 1250 | 0.9805          | 0.6384 | 0.2245 |
| 0.7915        | 15.38 | 1500 | 0.9340          | 0.5989 | 0.2124 |
| 0.6728        | 17.95 | 1750 | 0.9135          | 0.5735 | 0.2016 |
| 0.5889        | 20.51 | 2000 | 0.9381          | 0.5443 | 0.1944 |
| 0.5374        | 23.08 | 2250 | 0.9517          | 0.5372 | 0.1918 |
| 0.4972        | 25.64 | 2500 | 0.9171          | 0.5134 | 0.1828 |
| 0.4537        | 28.21 | 2750 | 0.9457          | 0.5043 | 0.1804 |
| 0.4217        | 30.77 | 3000 | 0.9479          | 0.4957 | 0.1789 |
| 0.4082        | 33.33 | 3250 | 0.9400          | 0.4906 | 0.1762 |
| 0.4005        | 35.9  | 3500 | 0.9710          | 0.4881 | 0.1770 |
| 0.3702        | 38.46 | 3750 | 0.9922          | 0.4792 | 0.1757 |
| 0.3473        | 41.03 | 4000 | 0.9724          | 0.4760 | 0.1734 |
| 0.3405        | 43.59 | 4250 | 0.9860          | 0.4726 | 0.1722 |
| 0.325         | 46.15 | 4500 | 0.9888          | 0.4679 | 0.1705 |
| 0.3193        | 48.72 | 4750 | 0.9939          | 0.4680 | 0.1711 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0