Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Arabic
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use mohammed/whisper-small-arabic-202505 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mohammed/whisper-small-arabic-202505 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mohammed/whisper-small-arabic-202505")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("mohammed/whisper-small-arabic-202505") model = AutoModelForSpeechSeq2Seq.from_pretrained("mohammed/whisper-small-arabic-202505", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Whisper Small AR - Mohammed Bakheet
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: 0.2732
- Wer: 21.5262
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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- 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
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 0.2079 | 250 | 0.3651 | 29.8066 |
| 0.5126 | 0.4158 | 500 | 0.3310 | 27.5784 |
| 0.5126 | 0.6237 | 750 | 0.3087 | 25.3032 |
| 0.2513 | 0.8316 | 1000 | 0.2865 | 24.4490 |
| 0.2513 | 1.0399 | 1250 | 0.2761 | 23.2251 |
| 0.1679 | 1.2478 | 1500 | 0.2755 | 22.9491 |
| 0.1679 | 1.4557 | 1750 | 0.2692 | 22.4329 |
| 0.1343 | 1.6636 | 2000 | 0.2682 | 22.0086 |
| 0.1343 | 1.8715 | 2250 | 0.2629 | 21.6670 |
| 0.1159 | 2.0798 | 2500 | 0.2669 | 21.5600 |
| 0.1159 | 2.2877 | 2750 | 0.2732 | 21.5262 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.5.1+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
- Downloads last month
- 7
Model tree for mohammed/whisper-small-arabic-202505
Base model
openai/whisper-smallEvaluation results
- Wer on Common Voice 11.0test set self-reported21.526