This model is a fine-tuned version of openai/whisper-large-v3-turbo on the Common Voice 13.0 dataset. It achieves the following results on the evaluation set:

Loss: 0.2687
Wer: 27.9267

Model description

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
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: 500
training_steps: 5000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2167	0.4160	1000	0.4101	39.1360
0.1643	0.8319	2000	0.3560	34.6257
0.0874	1.2479	3000	0.3249	32.9962
0.0873	1.6639	4000	0.2836	29.3890
0.0421	2.0799	5000	0.2687	27.9267

Framework versions

Transformers 4.52.1
Pytorch 2.7.0+cu126
Datasets 3.6.0
Tokenizers 0.21.1

Notes

Amir Nezami safa
Vahid Mahmodiyan
Shahab Salehi

nezamisafa/whisper-large-v3-turbo-fa-c13-avs

whisper-large-v3-turbo-fa-c13-avs