---
language:
- fr
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Base French
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 fr
      type: mozilla-foundation/common_voice_11_0
      config: fr
      split: test
      args: fr
    metrics:
    - name: Wer
      type: wer
      value: 24.064827553489256
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: google/fleurs fr_fr
      type: google/fleurs
      config: fr_fr
      split: test
      args: fr_fr
    metrics:
    - name: Wer
      type: wer
      value: 24.20
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: facebook/voxpopuli fr
      type: facebook/voxpopuli
      config: fr
      split: test
      args: fr
    metrics:
    - name: Wer
      type: wer
      value: 23.66
---

<!-- 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. -->

# Whisper Base French

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_11_0 fr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4968
- Wer on `mozilla-foundation/common_voice_11_0` `fr`: 24.0648
- Wer on `google/fleurs` `fr_fr`: 24.20
- Wer on `facebook/voxpopuli` `fr`: 23.66

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.534         | 0.2   | 1000 | 0.5710          | 27.4408 |
| 0.4409        | 1.2   | 2000 | 0.5279          | 25.1981 |
| 0.3095        | 2.2   | 3000 | 0.5117          | 25.0818 |
| 0.3285        | 3.2   | 4000 | 0.4995          | 24.0601 |
| 0.3032        | 4.2   | 5000 | 0.4968          | 24.0648 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2