dhaval0108/whisper-large-v3-turbo-finetuned-frozen-encoder

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ap-LracgWanIBIvdjeHeDoO07

This model is a fine-tuned version of openai/whisper-large-v3-turbo on the None dataset. It achieves the following results on the evaluation set:

• —Loss: 0.5750
• —Model Preparation Time: 0.025
• —Wer: 0.1411

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: 0.0003
• —trainbatchsize: 8
• —evalbatchsize: 8
• —seed: 42
• —gradientaccumulationsteps: 8
• —totaltrainbatch_size: 64
• —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: linear
• —lrschedulerwarmup_steps: 400
• —num_epochs: 16
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 4.48.3
• —Pytorch 2.5.1+cu124
• —Datasets 3.2.0
• —Tokenizers 0.21.2