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josephhaaga/transcribe-arlco-calls

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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transcribe-arlco-calls

This model is a fine-tuned version of openai/whisper-small.en on the arlco-calls dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.0040
  • —Wer: 1.9950

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: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —gradientaccumulationsteps: 2
  • —totaltrainbatch_size: 16
  • —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 20
  • —training_steps: 400
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossWer
0.8442.0500.782014.4313
0.38684.01000.37697.6453
0.16986.01500.09415.4609
0.02418.02000.02484.9949
0.028510.02500.01025.1551
0.00712.03000.00552.2426
0.002714.03500.00431.9659
0.003116.04000.00401.9950

Framework versions

  • —Transformers 4.48.3
  • —Pytorch 2.5.1+cu124
  • —Datasets 3.2.0
  • —Tokenizers 0.21.0