---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- robust-speech-event
model-index:
- name: XLS-R-1B - French
  results:
  - task:
      name: Automatic Speech Recognition 
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: fr
    metrics:
       - name: Test WER
         type: wer
         value: 21.65
       - name: Test CER
         type: cer
         value: 6.52
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Robust Speech Event - Dev Data
      type: speech-recognition-community-v2/dev_data
      args: fr
    metrics:
       - name: Test WER
         type: wer
         value: 61.72
       - name: Test CER
         type: cer
         value: 16.43
---

## Model description

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_8_0 - FR dataset.

## Training and evaluation data

It achieves the following results on the evaluation set (Step 17000):
- Wer: 0.2172

## 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: 5.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 2.9114        | 0.29  | 1000  | inf             | 0.9997 |
| 1.2436        | 0.57  | 2000  | inf             | 0.4310 |
| 1.0552        | 0.86  | 3000  | inf             | 0.3144 |
| 1.0044        | 1.15  | 4000  | inf             | 0.2814 |
| 0.9718        | 1.43  | 5000  | inf             | 0.2658 |
| 0.9502        | 1.72  | 6000  | inf             | 0.2566 |
| 0.9418        | 2.01  | 7000  | inf             | 0.2476 |
| 0.9215        | 2.29  | 8000  | inf             | 0.2420 |
| 0.9236        | 2.58  | 9000  | inf             | 0.2388 |
| 0.9014        | 2.87  | 10000 | inf             | 0.2354 |
| 0.8814        | 3.15  | 11000 | inf             | 0.2312 |
| 0.8809        | 3.44  | 12000 | inf             | 0.2285 |
| 0.8717        | 3.73  | 13000 | inf             | 0.2263 |
| 0.8787        | 4.01  | 14000 | inf             | 0.2218 |
| 0.8567        | 4.3   | 15000 | inf             | 0.2193 |
| 0.8488        | 4.59  | 16000 | inf             | 0.2187 |
| 0.8359        | 4.87  | 17000 | inf             | 0.2172 |

Got some issue with validation loss calculation.

### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.3.dev0
- Tokenizers 0.11.0