transformers tensorboard safetensors whisper automatic-speech-recognition whisper-event generated_from_trainer fr dataset:mozilla-foundation/common_voice_16_0 base_model:openai/whisper-base license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- fr
license: apache-2.0
base_model: openai/whisper-base
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: 27.650982108014144
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 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_16_0 fr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5654
- Wer: 27.6510

## 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-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- 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: 500
- training_steps: 7000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.739         | 0.07  | 500  | 0.7506          | 35.0088 |
| 0.6131        | 1.07  | 1000 | 0.6595          | 31.4298 |
| 0.5311        | 2.07  | 1500 | 0.6301          | 30.6233 |
| 0.551         | 3.07  | 2000 | 0.6141          | 29.7819 |
| 0.4588        | 4.07  | 2500 | 0.6003          | 29.2527 |
| 0.4163        | 5.07  | 3000 | 0.5936          | 29.0292 |
| 0.4553        | 6.07  | 3500 | 0.5838          | 28.4799 |
| 0.4395        | 7.07  | 4000 | 0.5783          | 28.2488 |
| 0.4233        | 8.07  | 4500 | 0.5747          | 28.0779 |
| 0.4204        | 9.07  | 5000 | 0.5712          | 28.1122 |
| 0.4378        | 10.06 | 5500 | 0.5695          | 28.0578 |
| 0.4337        | 11.06 | 6000 | 0.5673          | 27.7817 |
| 0.4277        | 12.06 | 6500 | 0.5658          | 27.6634 |
| 0.419         | 13.06 | 7000 | 0.5654          | 27.6510 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
