|
--- |
|
language: |
|
- fr |
|
license: apache-2.0 |
|
tags: |
|
- whisper-event |
|
- generated_from_trainer |
|
datasets: |
|
- mozilla-foundation/common_voice_11_0 |
|
metrics: |
|
- wer |
|
base_model: openai/whisper-base |
|
model-index: |
|
- name: Whisper Base French |
|
results: |
|
- task: |
|
type: automatic-speech-recognition |
|
name: 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: |
|
- type: wer |
|
value: 24.064827553489256 |
|
name: Wer |
|
- task: |
|
type: automatic-speech-recognition |
|
name: Automatic Speech Recognition |
|
dataset: |
|
name: google/fleurs fr_fr |
|
type: google/fleurs |
|
config: fr_fr |
|
split: test |
|
args: fr_fr |
|
metrics: |
|
- type: wer |
|
value: 24.2 |
|
name: Wer |
|
- task: |
|
type: automatic-speech-recognition |
|
name: Automatic Speech Recognition |
|
dataset: |
|
name: facebook/voxpopuli fr |
|
type: facebook/voxpopuli |
|
config: fr |
|
split: test |
|
args: fr |
|
metrics: |
|
- type: wer |
|
value: 23.66 |
|
name: Wer |
|
--- |
|
|
|
<!-- 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_11_0 fr dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4968 |
|
- Wer on `mozilla-foundation/common_voice_11_0` `fr`: 24.0648 |
|
- Wer on `google/fleurs` `fr_fr`: 24.20 |
|
- Wer on `facebook/voxpopuli` `fr`: 23.66 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:| |
|
| 0.534 | 0.2 | 1000 | 0.5710 | 27.4408 | |
|
| 0.4409 | 1.2 | 2000 | 0.5279 | 25.1981 | |
|
| 0.3095 | 2.2 | 3000 | 0.5117 | 25.0818 | |
|
| 0.3285 | 3.2 | 4000 | 0.4995 | 24.0601 | |
|
| 0.3032 | 4.2 | 5000 | 0.4968 | 24.0648 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.26.0.dev0 |
|
- Pytorch 1.11.0+cu102 |
|
- Datasets 2.7.1.dev0 |
|
- Tokenizers 0.13.2 |
|
|
