---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- polinaeterna/voxpopuli
- generated_from_trainer
- hf-asr-leaderboard
- robust-speech-event
datasets:
- polinaeterna/voxpopuli
model-index:
- name: Fine-tuned Wav2Vec2 XLS-R 1B model for ASR in French
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Voxpopuli
      type: polinaeterna/voxpopuli
      args: fr
    metrics:
    - name: Test WER
      type: wer
      value: 11.70
    - name: Test CER
      type: cer
      value: 5.80
    - name: Test WER (+LM)
      type: wer
      value: 10.01
    - name: Test CER (+LM)
      type: cer
      value: 5.63
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 9
      type: mozilla-foundation/common_voice_9_0
      args: fr
    metrics:
    - name: Test WER
      type: wer
      value: 45.74
    - name: Test CER
      type: cer
      value: 22.99
    - name: Test WER (+LM)
      type: wer
      value: 38.81
    - name: Test CER (+LM)
      type: cer
      value: 23.25
  - 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: 27.86
    - name: Test CER
      type: cer
      value: 13.20
    - name: Test WER (+LM)
      type: wer
      value: 22.53
    - name: Test CER (+LM)
      type: cer
      value: 12.82
---


# Fine-tuned Wav2Vec2 XLS-R 1B model for ASR in French

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the POLINAETERNA/VOXPOPULI - FR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2906
- Wer: 0.1093

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- 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_ratio: 0.1
- num_epochs: 12.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.4628        | 0.93  | 500  | 0.3834          | 0.1625 |
| 0.3577        | 1.85  | 1000 | 0.3231          | 0.1367 |
| 0.3103        | 2.78  | 1500 | 0.2918          | 0.1287 |
| 0.2884        | 3.7   | 2000 | 0.2845          | 0.1227 |
| 0.2615        | 4.63  | 2500 | 0.2819          | 0.1189 |
| 0.242         | 5.56  | 3000 | 0.2915          | 0.1165 |
| 0.2268        | 6.48  | 3500 | 0.2768          | 0.1187 |
| 0.2188        | 7.41  | 4000 | 0.2719          | 0.1128 |
| 0.1979        | 8.33  | 4500 | 0.2741          | 0.1134 |
| 0.1834        | 9.26  | 5000 | 0.2827          | 0.1096 |
| 0.1719        | 10.19 | 5500 | 0.2906          | 0.1093 |
| 0.1723        | 11.11 | 6000 | 0.2868          | 0.1104 |

### Framework versions

- Transformers 4.23.0.dev0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1


## Evaluation

1. To evaluate on `mozilla-foundation/common_voice_9_0`

```bash
python eval.py \
  --model_id "bhuang/wav2vec2-xls-r-1b-voxpopuli-fr" \
  --dataset "polinaeterna/voxpopuli" \
  --config "fr" \
  --split "test" \
  --log_outputs \
  --outdir "outputs/results_polinaeterna_voxpopuli_with_lm"
```

2. To evaluate on `mozilla-foundation/common_voice_9_0`

```bash
python eval.py \
  --model_id "bhuang/wav2vec2-xls-r-1b-voxpopuli-fr" \
  --dataset "mozilla-foundation/common_voice_9_0" \
  --config "fr" \
  --split "test" \
  --log_outputs \
  --outdir "outputs/results_mozilla-foundatio_common_voice_9_0_with_lm"
```

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

```bash
python eval.py \
  --model_id "bhuang/wav2vec2-xls-r-1b-voxpopuli-fr" \
  --dataset "speech-recognition-community-v2/dev_data" \
  --config "fr" \
  --split "validation" \
  --chunk_length_s 5.0 \
  --stride_length_s 1.0 \
  --log_outputs \
  --outdir "outputs/results_speech-recognition-community-v2_dev_data_with_lm"
```