pytorch wav2vec2 automatic-speech-recognition fr dataset:common_voice transformers common_voice generated_from_trainer license:apache-2.0 model-index
---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- common_voice
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2XLS-R-common_voice_10-fr
  results: []
---

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# wav2vec2XLS-R-common_voice_10-fr

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 - FR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3934
- Wer: 0.2774

## 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: 15.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 2.72  | 400  | 1.3597          | 0.8722 |
| 3.9444        | 5.44  | 800  | 0.5503          | 0.4751 |
| 0.5425        | 8.16  | 1200 | 0.4261          | 0.3445 |
| 0.2356        | 10.88 | 1600 | 0.4007          | 0.3042 |
| 0.1345        | 13.61 | 2000 | 0.4101          | 0.2836 |


### Framework versions

- Transformers 4.21.0.dev0
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
