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---
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
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_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
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