---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_7_0
- generated_from_trainer
- robust-speech-event
model-index:
- name: XLS-R-300M - French
  results:
  - task: 
      name: Automatic Speech Recognition 
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 7
      type: mozilla-foundation/common_voice_7_0
      args: fr
    metrics:
       - name: Test WER
         type: wer
         value: 24.56
       - name: Test CER
         type: cer
         value: 7.3
---

<!-- 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. -->

# 

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_7_0 - FR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2619
- Wer: 0.2457

## 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: 7.5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 2.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.495         | 0.16  | 500  | 3.3883          | 1.0    |
| 2.9095        | 0.32  | 1000 | 2.9152          | 1.0000 |
| 1.8434        | 0.49  | 1500 | 1.0473          | 0.7446 |
| 1.4298        | 0.65  | 2000 | 0.5729          | 0.5130 |
| 1.1937        | 0.81  | 2500 | 0.3795          | 0.3450 |
| 1.1248        | 0.97  | 3000 | 0.3321          | 0.3052 |
| 1.0835        | 1.13  | 3500 | 0.3038          | 0.2805 |
| 1.0479        | 1.3   | 4000 | 0.2910          | 0.2689 |
| 1.0413        | 1.46  | 4500 | 0.2798          | 0.2593 |
| 1.014         | 1.62  | 5000 | 0.2727          | 0.2512 |
| 1.004         | 1.78  | 5500 | 0.2646          | 0.2471 |
| 0.9949        | 1.94  | 6000 | 0.2619          | 0.2457 |


### Eval results on Common Voice 7 "test" (WER):

| Without LM | With LM |
|---|---|
| 24.56 | To be computed |

### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0