leenag/Norm_Malasar_Luke

This model is a fine-tuned version of openai/whisper-small on the Spoken Bible Corpus: Malasar dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5217
  • Wer: 52.4656

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
  • train_batch_size: 32
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 2000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1406 11.3636 250 0.2856 55.7339
0.0084 22.7273 500 0.4196 53.8417
0.0022 34.0909 750 0.4641 53.3257
0.0005 45.4545 1000 0.4835 51.6628
0.0002 56.8182 1250 0.5049 52.0642
0.0002 68.1818 1500 0.5149 52.4656
0.0002 79.5455 1750 0.5200 52.2936
0.0002 90.9091 2000 0.5217 52.4656

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.0.1+cu117
  • Datasets 2.16.0
  • Tokenizers 0.19.1
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