metadata
language:
- ar
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 ar - Mohammed Nasri
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: ar
split: test
args: 'config: ar, split: test'
metrics:
- name: Wer
type: wer
value: 39.30217610871362
Whisper Small ar - Mohammed Nasri
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2667
- Wer: 39.3022
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: 8
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2262 | 0.05 | 1000 | 0.3206 | 42.6903 |
| 0.2 | 0.1 | 2000 | 0.3067 | 42.8354 |
| 0.1944 | 0.16 | 3000 | 0.2863 | 40.6648 |
| 0.1785 | 0.21 | 4000 | 0.2736 | 39.4675 |
| 0.1641 | 0.26 | 5000 | 0.2667 | 39.3022 |
Framework versions
- Transformers 4.28.0.dev0
- Pytorch 1.12.1
- Datasets 2.10.1
- Tokenizers 0.13.2