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alpcansoydas/whisper-large-v2-tr-ft-15-03-26-partial-encoder-only

sourceHugging Faceapache-2.0updated 7mo agoView on Hugging Face
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Model Card

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Whisper for Turkish Call Centers

This model is a fine-tuned version of openai/whisper-large-v2 on the Custom turkish call center simulated data dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.2925

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: 5e-06
  • —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_steps: 500
  • —training_steps: 4500
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation Loss
0.30920.22222500.3472
0.30420.44445000.3181
0.26410.66677500.3088
0.26710.888910000.3017
0.22981.111112500.2988
0.21181.333315000.2972
0.20901.555617500.2944
0.23411.777820000.2919
0.22382.022500.2896
0.23182.222225000.2921
0.19182.444427500.2918
0.22732.666730000.2914
0.20582.888932500.2906
0.22493.111135000.2921
0.16453.333337500.2931
0.18973.555640000.2924
0.21283.777842500.2925
0.23734.045000.2925

Framework versions

  • —Transformers 5.3.0
  • —Pytorch 2.10.0+cu128
  • —Datasets 4.7.0
  • —Tokenizers 0.22.2