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Whisper tiny Ta example - Bharat Ramanathan

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

  • Loss: 0.4016
  • Wer: 36.5217

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
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 25
  • training_steps: 100
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.304 12.01 25 0.3614 31.7391
0.1826 24.02 50 0.3851 35.2174
0.1346 37.01 75 0.3999 37.8261
0.1096 49.02 100 0.4016 36.5217

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2
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