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---
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
|