This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 Arabic dataset. It achieves the following results on the evaluation set:

Loss: 0.3424
Wer: 46.3869

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: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
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: 200
training_steps: 2000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2895	0.4156	1000	0.3992	48.7118
0.2411	0.8313	2000	0.3424	46.3869

Framework versions

Transformers 4.48.0
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.2

ziadtarek12/whisper-small-msa-arabic

Whisper Small One-Stage: MSA Arabic

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

ziadtarek12/
whisper-small-msa-arabic