metadata
language:
- ar
license: apache-2.0
base_model: openai/whisper-small
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Whisper Small Arabic
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_16_0 ar
type: mozilla-foundation/common_voice_16_0
config: ar
split: test
args: ar
metrics:
- name: Wer
type: wer
value: 58.90729282066525
Whisper Small Arabic
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_16_0 ar dataset. It achieves the following results on the evaluation set:
- Loss: 0.4005
- Wer: 58.9073
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-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3404 | 1.53 | 500 | 0.4606 | 66.6216 |
| 0.2707 | 3.07 | 1000 | 0.4295 | 66.8500 |
| 0.2427 | 4.6 | 1500 | 0.4124 | 61.1662 |
| 0.2131 | 6.13 | 2000 | 0.4056 | 62.3038 |
| 0.2085 | 7.67 | 2500 | 0.4012 | 62.2754 |
| 0.1904 | 9.2 | 3000 | 0.3976 | 59.7341 |
| 0.1836 | 10.74 | 3500 | 0.4005 | 58.9073 |
| 0.1653 | 12.27 | 4000 | 0.3989 | 59.7774 |
| 0.1693 | 13.8 | 4500 | 0.3983 | 59.9462 |
| 0.1616 | 15.34 | 5000 | 0.3984 | 59.8300 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0