Whisper whisper-large-v3 ar1 - Mohamed Shaaban
This model is a fine-tuned version of openai/whisper-large-v3 on the Common standard ar Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4220
- Wer: 0.0
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.5721 | 1.0 | 1 | 2.1602 | 100.0 |
| 0.5723 | 2.0 | 2 | 1.0610 | 33.3333 |
| 0.1861 | 3.0 | 3 | 0.6003 | 33.3333 |
| 0.0478 | 4.0 | 4 | 0.4661 | 0.0 |
| 0.0262 | 5.0 | 5 | 0.4220 | 0.0 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for Mohamedshaaban2001/MSDC-whisper-large-v3-56
Base model
openai/whisper-large-v3Dataset used to train Mohamedshaaban2001/MSDC-whisper-large-v3-56
Evaluation results
- Wer on Common standard ar Voice 11.0self-reported0.000