Tirendaz/whisper-large-v3-turbo

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Whisper Large V3 Pro on the Turkish Dataset - Evren Ozkip

This model is a fine-tuned version of openai/whisper-small on the Turkish Common Voice 13 dataset. It achieves the following results on the evaluation set:

• —Loss: 0.4715
• —Wer Ortho: 35.2262
• —Wer: 31.3503

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
• —trainbatchsize: 4
• —evalbatchsize: 4
• —seed: 42
• —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: constantwithwarmup
• —lrschedulerwarmup_steps: 50
• —training_steps: 100
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 4.51.3
• —Pytorch 2.1.1+cu121
• —Datasets 3.6.0
• —Tokenizers 0.21.1