---
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: 18.33
       - name: Test CER
         type: cer
         value: 5.60
  - 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: 60.25
       - name: Test CER
         type: cer
         value: 15.68
---

## Model description

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - FR dataset.

## 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: 4.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.9827        | 0.29  | 1000  | inf             | 0.2937 |
| 1.0203        | 0.57  | 2000  | inf             | 0.2711 |
| 1.0048        | 0.86  | 3000  | inf             | 0.2620 |
| 0.9858        | 1.15  | 4000  | inf             | 0.2522 |
| 0.9709        | 1.43  | 5000  | inf             | 0.2365 |
| 0.9347        | 1.72  | 6000  | inf             | 0.2332 |
| 0.9256        | 2.01  | 7000  | inf             | 0.2261 |
| 0.8936        | 2.29  | 8000  | inf             | 0.2203 |
| 0.877         | 2.58  | 9000  | inf             | 0.2096 |
| 0.8393        | 2.87  | 10000 | inf             | 0.2017 |
| 0.8156        | 3.15  | 11000 | inf             | 0.1936 |
| 0.8015        | 3.44  | 12000 | inf             | 0.1880 |
| 0.774         | 3.73  | 13000 | inf             | 0.1834 |

It achieves the best result for STEP 13000 on the validation set:
- Wer: 0.1834

Some problems occur when calculating the validation loss.

### Framework versions

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

### Evaluation Commands
1. To evaluate on `mozilla-foundation/common_voice_8` with split `test`

```bash
python eval.py --model_id Plim/xls-r-1b-cv_8-fr --dataset mozilla-foundation/common_voice_8_0 --config fr --split test
```

2. To evaluate on `speech-recognition-community-v2/dev_data`

```bash
python eval.py --model_id Plim/xls-r-1b-cv_8-fr --dataset speech-recognition-community-v2/dev_data --config fr --split validation --chunk_length_s 5.0 --stride_length_s 1.0