leenag/Malasar_Luke

This model is a fine-tuned version of vasista22/whisper-tamil-medium on the Spoken Bible Corpus: Malasar dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5075
  • Wer: 48.2010

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
0.018 11.3636 250 0.3526 50.2570
0.0059 22.7273 500 0.4000 49.5146
0.0002 34.0909 750 0.4418 48.3152
0.0001 45.4545 1000 0.4785 48.0868
0.0 56.8182 1250 0.4923 47.8013
0.0 68.1818 1500 0.5008 47.8013
0.0 79.5455 1750 0.5059 48.2010
0.0 90.9091 2000 0.5075 48.2010

Framework versions

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