leenag/Malasar_Dict

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: 0.0139
  • Wer: 7.6014

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
0.042 0.6410 250 0.0392 18.1869
0.023 1.2821 500 0.0318 14.5833
0.0158 1.9231 750 0.0215 10.5293
0.0106 2.5641 1000 0.0175 11.5428
0.0035 3.2051 1250 0.0145 7.5450
0.0027 3.8462 1500 0.0139 9.1779
0.0018 4.4872 1750 0.0144 7.5450
0.0016 5.1282 2000 0.0139 7.6014

Framework versions

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