metadata
language:
- fr
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: deepdml/whisper-medium-mix-fr
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: 11.227820307400155
deepdml/whisper-medium-mix-fr
This model is a fine-tuned version of deepdml/whisper-medium-mix-fr on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2599
- Wer: 11.2278
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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0855 | 0.25 | 1000 | 0.2826 | 12.4230 |
| 0.0569 | 0.5 | 2000 | 0.2768 | 11.9577 |
| 0.0724 | 0.75 | 3000 | 0.2670 | 11.6106 |
| 0.069 | 1.0 | 4000 | 0.2599 | 11.2278 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2