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Whisper Small Te - Bharat Ramanathan

This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1863
  • Wer: 31.6456

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: 64
  • eval_batch_size: 32
  • 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: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1637 0.1 500 0.2092 42.9406
0.1459 0.2 1000 0.2025 35.9299
0.1348 0.3 1500 0.1990 35.4917
0.1309 0.4 2000 0.1974 33.7390
0.1253 0.5 2500 0.1974 34.0312
0.1209 0.6 3000 0.1909 32.4732
0.1139 1.05 3500 0.1899 31.7916
0.1043 1.15 4000 0.1868 31.6456
0.0996 1.25 4500 0.1874 31.6943
0.1002 1.35 5000 0.1863 31.6456

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2
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Evaluation results