metadata
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: whisper-sm-arabic-nouraa5
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_17_0
config: ar
split: None
args: 'config: ar, split: test'
metrics:
- name: Wer
type: wer
value: 90.9278350515464
whisper-sm-arabic-nouraa5
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: 0.7124
- Wer: 90.9278
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: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 1.0 | 32 | 3.4835 | 64.3918 |
| 2.7298 | 2.0 | 64 | 2.1102 | 97.8557 |
| 2.7298 | 3.0 | 96 | 1.4302 | 82.5361 |
| 1.2041 | 4.0 | 128 | 1.2875 | 73.7113 |
| 0.7692 | 5.0 | 160 | 1.1756 | 67.5464 |
| 0.7692 | 6.0 | 192 | 1.0568 | 67.5876 |
| 0.5691 | 7.0 | 224 | 0.7701 | 61.3196 |
| 0.2735 | 8.0 | 256 | 0.6364 | 79.8351 |
| 0.2735 | 9.0 | 288 | 0.6546 | 82.8247 |
| 0.0953 | 9.704 | 310 | 0.7124 | 90.9278 |
Framework versions
- Transformers 4.51.1
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1