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---
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 Tiny French Cased
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: 33.06549172161867
- 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: 36.69
- 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: 32.71
---
<!-- 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 Tiny French Cased
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the mozilla-foundation/common_voice_11_0 fr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6509
- Wer on `mozilla-foundation/common_voice_11_0` `fr`: 33.0655
- Wer on `google/fleurs` `fr_fr`: 36.69
- Wer on `facebook/voxpopuli` `fr`: 32.71
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.7185 | 0.2 | 1000 | 0.7608 | 38.1636 |
| 0.6052 | 1.2 | 2000 | 0.6949 | 34.9513 |
| 0.4467 | 2.2 | 3000 | 0.6708 | 34.3393 |
| 0.4773 | 3.2 | 4000 | 0.6536 | 33.2102 |
| 0.4479 | 4.2 | 5000 | 0.6509 | 33.0655 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|