---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-breton-colab
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: br
      split: test
      args: br
    metrics:
    - name: Wer
      type: wer
      value: 0.4936988936988937
---

<!-- 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-large-xls-r-300m-breton-colab

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2211
- Wer: 0.4937

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.3288        | 1.34  | 400  | 1.7076          | 0.9809 |
| 1.2014        | 2.69  | 800  | 1.0803          | 0.7733 |
| 0.7687        | 4.03  | 1200 | 0.9806          | 0.6642 |
| 0.5539        | 5.38  | 1600 | 0.9914          | 0.6301 |
| 0.4456        | 6.72  | 2000 | 0.9797          | 0.6265 |
| 0.3586        | 8.07  | 2400 | 1.0354          | 0.5803 |
| 0.2922        | 9.41  | 2800 | 0.9996          | 0.5821 |
| 0.2628        | 10.76 | 3200 | 1.0250          | 0.5708 |
| 0.2284        | 12.1  | 3600 | 1.0865          | 0.5722 |
| 0.1908        | 13.45 | 4000 | 1.0674          | 0.5450 |
| 0.1732        | 14.79 | 4400 | 1.1775          | 0.5614 |
| 0.153         | 16.13 | 4800 | 1.1542          | 0.5435 |
| 0.14          | 17.48 | 5200 | 1.1807          | 0.5449 |
| 0.1302        | 18.82 | 5600 | 1.1679          | 0.5376 |
| 0.1142        | 20.17 | 6000 | 1.1441          | 0.5276 |
| 0.104         | 21.51 | 6400 | 1.2243          | 0.5355 |
| 0.0882        | 22.86 | 6800 | 1.1837          | 0.5316 |
| 0.0807        | 24.2  | 7200 | 1.1986          | 0.5132 |
| 0.0744        | 25.55 | 7600 | 1.2182          | 0.5108 |
| 0.0646        | 26.89 | 8000 | 1.2116          | 0.5047 |
| 0.0551        | 28.24 | 8400 | 1.2009          | 0.4948 |
| 0.0503        | 29.58 | 8800 | 1.2211          | 0.4937 |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3