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whisper-tiny-akan

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

  • Loss: 1.0747
  • Wer: 43.6101

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: 0.0001
  • 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: 500
  • training_steps: 3000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.4857 10.0 250 0.7120 57.1555
0.0806 20.0 500 0.8478 49.9411
0.0347 30.0 750 0.9223 48.1743
0.0168 40.0 1000 1.0079 55.1826
0.0085 50.0 1250 1.0402 47.3498
0.0051 60.0 1500 1.0890 46.7314
0.0029 70.0 1750 1.0639 44.9352
0.002 80.0 2000 1.0707 44.6702
0.0005 90.0 2250 1.0705 43.7574
0.0005 100.0 2500 1.0721 44.4052
0.0002 110.0 2750 1.0730 43.3451
0.0003 120.0 3000 1.0747 43.6101

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1
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