Whisper Small Hi - Sanchit Gandhi

This model is a fine-tuned version of nurzhanit/whisper-enhanced-ml on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0000
  • Wer: 0.0

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: 200
  • training_steps: 4000

Training results

Training Loss Epoch Step Validation Loss Wer
0.0073 50.0 100 0.0008 0.0
0.0003 100.0 200 0.0002 0.0
0.0001 150.0 300 0.0001 0.0
0.0001 200.0 400 0.0001 0.0
0.0001 250.0 500 0.0001 0.0
0.0 300.0 600 0.0000 0.0
0.0 350.0 700 0.0000 0.0
0.0 400.0 800 0.0000 0.0
0.0 450.0 900 0.0000 0.0
0.0 500.0 1000 0.0000 0.0
0.0 550.0 1100 0.0000 0.0
0.0 600.0 1200 0.0000 0.0
0.0 650.0 1300 0.0000 0.0
0.0 700.0 1400 0.0000 0.0
0.0 750.0 1500 0.0000 0.0
0.0 800.0 1600 0.0000 0.0
0.0 850.0 1700 0.0000 0.0
0.0 900.0 1800 0.0000 0.0
0.0 950.0 1900 0.0000 0.0
0.0 1000.0 2000 0.0000 0.0
0.0 1050.0 2100 0.0000 0.0
0.0 1100.0 2200 0.0000 0.0
0.0 1150.0 2300 0.0000 0.0
0.0 1200.0 2400 0.0000 0.0
0.0 1250.0 2500 0.0000 0.0
0.0 1300.0 2600 0.0000 0.0
0.0 1350.0 2700 0.0000 0.0
0.0 1400.0 2800 0.0000 0.0
0.0 1450.0 2900 0.0000 0.0
0.0 1500.0 3000 0.0000 0.0
0.0 1550.0 3100 0.0000 0.0
0.0 1600.0 3200 0.0000 0.0
0.0 1650.0 3300 0.0000 0.0
0.0 1700.0 3400 0.0000 0.0
0.0 1750.0 3500 0.0000 0.0
0.0 1800.0 3600 0.0000 0.0
0.0 1850.0 3700 0.0000 0.0
0.0 1900.0 3800 0.0000 0.0
0.0 1950.0 3900 0.0000 0.0
0.0 2000.0 4000 0.0000 0.0

Framework versions

  • Transformers 4.40.0
  • Pytorch 2.5.0+cu124
  • Datasets 3.0.2
  • Tokenizers 0.19.1
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Dataset used to train nurzhanit/whisper-omg-2

Evaluation results