Whisper Small - Levantine Arabic (Roma F1 Assistant)
This model is a fine-tuned version of openai/whisper-small on the NADI 2025 Subtask 2 (Jordan & Palestine) dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.5629
- eval_wer: 37.5784
- eval_runtime: 320.5385
- eval_samples_per_second: 1.997
- eval_steps_per_second: 0.25
- epoch: 6.9444
- step: 1250
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: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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
- mixed_precision_training: Native AMP
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2
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openai/whisper-small