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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: 1.0576
  • Wer: 1.1825
  • Cer: 1.0651

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
1.6978 3.33 100 1.3610 0.7852 0.4184
0.6547 6.66 200 0.8659 0.7226 0.4379
0.3805 9.99 300 0.8060 0.7256 0.4330
0.1886 13.33 400 0.8382 0.6395 0.4164
0.0745 16.66 500 0.9106 0.8185 0.6747
0.0303 19.99 600 0.9697 0.8509 0.5685
0.0139 23.33 700 1.0096 0.8773 0.6483
0.0069 26.66 800 1.0367 1.2781 1.2923
0.0054 29.99 900 1.0518 1.2363 1.1066
0.0048 33.33 1000 1.0576 1.1825 1.0651

Framework versions

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