---
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: 0.5302549302549302
---

<!-- 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: 1.0737
- Wer: 0.5303

## 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: 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_steps: 500
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.8658        | 2.68  | 400  | 1.2395          | 0.8972 |
| 0.8219        | 5.37  | 800  | 0.9454          | 0.6731 |
| 0.4743        | 8.05  | 1200 | 0.8880          | 0.6181 |
| 0.3224        | 10.74 | 1600 | 0.9330          | 0.6148 |
| 0.2415        | 13.42 | 2000 | 1.0494          | 0.5889 |
| 0.1904        | 16.11 | 2400 | 1.0328          | 0.5469 |
| 0.152         | 18.79 | 2800 | 1.0771          | 0.5625 |
| 0.1231        | 21.48 | 3200 | 0.9980          | 0.5598 |
| 0.0993        | 24.16 | 3600 | 1.0351          | 0.5317 |
| 0.0788        | 26.85 | 4000 | 1.0560          | 0.5381 |
| 0.0653        | 29.53 | 4400 | 1.0737          | 0.5303 |


### Framework versions

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