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AleksanderObuchowski/whisper-large-v3-turbo-med-pl-lora-r64-enc-dec-lr2e-04-ep5-whisper_bigos10k_fair-filtered

sourceHugging Facemitupdated 6mo agoView on Hugging Face
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whisper-large-v3-turbo-med-pl-lora-r64-enc-dec-lr2e-04-ep5-whisperbigos10kfair-filtered

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: 1.6342
  • —Model Preparation Time: 0.0204
  • —Wer: 13.1507
  • —Cer: 4.5137

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: 0.0002
  • —trainbatchsize: 16
  • —evalbatchsize: 8
  • —seed: 42
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: linear
  • —lrschedulerwarmup_ratio: 0.1
  • —num_epochs: 5
  • —mixedprecisiontraining: Native AMP
  • —labelsmoothingfactor: 0.1

Training results

Training LossEpochStepValidation LossModel Preparation TimeWerCer
1.62241.017801.65640.020413.86224.5215
1.59022.035601.64110.020413.30574.2441
1.56543.053401.63200.020412.82794.2279
1.54584.071201.63290.020413.11254.4243
1.53225.089001.63420.020413.15074.5137

Framework versions

  • —PEFT 0.18.1
  • —Transformers 4.57.6
  • —Pytorch 2.8.0+cu128
  • —Datasets 4.5.0
  • —Tokenizers 0.22.2