---
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: 0.508994708994709
---

<!-- 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: 1.2344
- Wer: 0.5090

## 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: 35

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 2.8178        | 3.36  | 1000  | 1.0244          | 0.7207 |
| 0.5674        | 6.72  | 2000  | 0.9848          | 0.6341 |
| 0.33          | 10.08 | 3000  | 1.0254          | 0.6014 |
| 0.2362        | 13.45 | 4000  | 1.1387          | 0.5848 |
| 0.1777        | 16.81 | 5000  | 1.2125          | 0.5783 |
| 0.1429        | 20.17 | 6000  | 1.1952          | 0.5572 |
| 0.1076        | 23.53 | 7000  | 1.2492          | 0.5628 |
| 0.0842        | 26.89 | 8000  | 1.2103          | 0.5410 |
| 0.0666        | 30.25 | 9000  | 1.2032          | 0.5128 |
| 0.051         | 33.61 | 10000 | 1.2344          | 0.5090 |


### Framework versions

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