whisper-small-fr / README.md
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---
language:
- hi
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Fr - Joss
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0 FR
type: mozilla-foundation/common_voice_11_0
args: 'config: fr, split: test'
metrics:
- name: Wer
type: wer
value: 24.03653329331678
---
<!-- 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 Small Fr - Joss
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 FR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4212
- Wer: 24.0365
## 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: 16
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3803 | 0.99 | 1000 | 0.3992 | 23.9465 |
| 0.2214 | 1.99 | 2000 | 0.3902 | 22.8108 |
| 0.0986 | 2.98 | 3000 | 0.4028 | 22.4459 |
| 0.0478 | 3.98 | 4000 | 0.4212 | 24.0365 |
### Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.2