whisper-large-amitabha

This model is a fine-tuned version of openai/whisper-large-v2 on the Amitabha dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0000
  • Cer: 0.4498

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: 16
  • eval_batch_size: 8
  • 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: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Cer
0.0079 12.5 1000 0.0118 1.1245
0.0001 25.0 2000 0.0001 0.3036
0.0 37.5 3000 0.0000 0.2699
0.0 50.0 4000 0.0000 0.4498

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.2
  • Tokenizers 0.19.1
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