Whisper Medium Arabic
This model is a fine-tuned version of openai/whisper-medium on the Arabic Speech Corpus dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.0794
- eval_wer: 5.4226
- eval_runtime: 200.1714
- eval_samples_per_second: 0.5
- eval_steps_per_second: 0.5
- epoch: 5.7143
- step: 250
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 400
Framework versions
- Transformers 4.41.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Base model
openai/whisper-medium