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Whisper Small Tr - CV 43h - Linear Decay

This model is a fine-tuned version of openai/whisper-small on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2554
  • Wer: 21.6318

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
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 4000
  • training_steps: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.2413 0.37 500 0.2845 23.9500
0.2005 0.73 1000 0.2615 22.3219
0.1583 1.1 1500 0.2493 21.5365
0.1513 1.46 2000 0.2485 21.5455
0.1502 1.83 2500 0.2407 21.0639
0.0959 2.19 3000 0.2485 21.1987
0.1074 2.56 3500 0.2539 21.8762
0.105 2.92 4000 0.2554 21.6318

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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Safetensors
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F32
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Finetuned from

Dataset used to train alikanakar/whisper-small-CV-43-linear-decay

Evaluation results