drepic/whisper-medium-jp

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whisper-medium-jp

This model is a fine-tuned version of openai/whisper-medium on an unknown dataset. It achieves the following results on the evaluation set:

• —Loss: 0.4828
• —Wer: 0.2254
• —Cer: 0.2254

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: 4e-06
• —trainbatchsize: 4
• —evalbatchsize: 2
• —seed: 42
• —distributed_type: multi-GPU
• —num_devices: 2
• —gradientaccumulationsteps: 2
• —totaltrainbatch_size: 16
• —totalevalbatch_size: 4
• —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• —lrschedulertype: linear
• —lrschedulerwarmup_steps: 400
• —num_epochs: 15
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 4.56.1
• —Pytorch 2.8.0+cu128
• —Datasets 4.0.0
• —Tokenizers 0.22.0