leenag/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: 0.6211
  • Wer: 60.1371

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
0.1612 11.3636 250 0.3185 64.0206
0.0114 22.7273 500 0.4682 65.7339
0.0016 34.0909 750 0.5380 59.9657
0.0004 45.4545 1000 0.5761 59.8515
0.0003 56.8182 1250 0.5969 59.6802
0.0002 68.1818 1500 0.6104 60.3655
0.0002 79.5455 1750 0.6181 60.1942
0.0002 90.9091 2000 0.6211 60.1371

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.1.2+cu121
  • Datasets 2.16.0
  • Tokenizers 0.19.1
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