CoolFace
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GwadaDLT/whisper-base-gcf

sourceHugging Faceapache-2.0updated 6mo agoView on Hugging Face
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whisper-base-gcf

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

  • —Loss: 2.4385
  • —Wer: 100.1274

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: 16
  • —evalbatchsize: 8
  • —seed: 42
  • —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 100
  • —training_steps: 1500
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossWer
0.99631.40852003.4896101.2739
0.60152.81694003.08771097.9618
0.32164.22546002.861899.7452
0.23685.63388002.6891100.1274
0.17397.042310002.5483421.6561
0.18928.450712002.4829104.5860
0.12739.859214002.43581683.6943
0.125610.563415002.4385100.1274

Framework versions

  • —Transformers 5.5.0
  • —Pytorch 2.4.1+cu124
  • —Datasets 3.6.0
  • —Tokenizers 0.22.2