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base Turkish Whisper (bTW)

This model is a fine-tuned version of openai/whisper-base on the Ermetal Meetings dataset. It achieves the following results on the evaluation set:

  • Loss: 2.1975
  • Wer: 1.6817
  • Cer: 1.2800

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: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • 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: 500
  • training_steps: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
1.5514 33.31 100 1.6389 0.8196 0.8754
0.1703 66.62 200 1.6896 1.0058 0.6987
0.0039 99.92 300 1.9380 1.7011 1.1631
0.0015 133.31 400 2.0324 1.6950 1.2498
0.0008 166.62 500 2.0957 1.4898 1.0992
0.0005 199.92 600 2.1417 1.7320 1.2528
0.0004 233.31 700 2.1681 1.6077 1.1845
0.0003 266.62 800 2.1847 1.625 1.2008
0.0003 299.92 900 2.1944 1.6515 1.2196
0.0003 333.31 1000 2.1975 1.6817 1.2800

Framework versions

  • Transformers 4.26.0
  • Pytorch 1.12.0+cu102
  • Datasets 2.9.0
  • Tokenizers 0.13.2
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