whisper-small-arabic-finetuned-on-halabi_daataset
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.2854
- Wer: 1.2203
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: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use 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: 2000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0195 | 8.7788 | 500 | 3.6442 | 1.2196 |
| 0.0044 | 17.5487 | 1000 | 4.2713 | 1.2203 |
| 0.0002 | 26.3186 | 1500 | 4.2612 | 1.2203 |
| 0.0001 | 35.0885 | 2000 | 4.2533 | 1.2203 |
Framework versions
- Transformers 4.47.0.dev0
- Pytorch 2.5.1
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
openai/whisper-small