---
language:
- fr
license: apache-2.0
base_model: qanastek/whisper-small-french-uncased
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_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_16_0 fr
      type: mozilla-foundation/common_voice_16_0
      config: fr
      split: test
      args: fr
    metrics:
    - name: Wer
      type: wer
      value: 15.184536972434753
---

<!-- 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 [qanastek/whisper-small-french-uncased](https://huggingface.co/qanastek/whisper-small-french-uncased) on the mozilla-foundation/common_voice_16_0 fr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8014
- Wer: 15.1845

## 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: 5e-07
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.9295        | 0.2   | 100  | 0.8014          | 15.1845 |
| 0.2976        | 0.4   | 200  | 0.4207          | 16.0289 |
| 0.2699        | 0.59  | 300  | 0.3999          | 15.8267 |
| 0.2773        | 0.79  | 400  | 0.3910          | 15.7267 |
| 0.2631        | 0.99  | 500  | 0.3863          | 15.5972 |
| 0.2487        | 1.19  | 600  | 0.3834          | 15.5907 |
| 0.2477        | 1.39  | 700  | 0.3814          | 15.6156 |
| 0.2428        | 1.59  | 800  | 0.3801          | 15.4902 |
| 0.2492        | 1.78  | 900  | 0.3794          | 15.4672 |
| 0.2471        | 1.98  | 1000 | 0.3791          | 15.4707 |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0