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Whisper Small NSC part 1,2,3 (500 steps) - Jarrett Er

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: 0.3612
  • Wer: 12.4283

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: 0.00025
  • train_batch_size: 16
  • 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: 50
  • training_steps: 500
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.806 0.3802 100 0.7674 22.7887
0.6965 0.7605 200 0.6955 20.0655
0.42 1.1407 300 0.5785 17.7723
0.402 1.5209 400 0.4303 14.3939
0.3231 1.9011 500 0.3612 12.4283

Framework versions

  • PEFT 0.14.0
  • Transformers 4.45.2
  • Pytorch 2.5.1+cu124
  • Datasets 3.2.1.dev0
  • Tokenizers 0.20.3
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