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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: 1.9500
  • Wer: 2.1895
  • Cer: 1.3548

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
1.7116 5.53 100 1.9115 1.1785 0.6901
0.6101 11.11 200 1.5123 1.1039 0.6221
0.2376 16.64 300 1.5636 0.9817 0.6448
0.0591 22.21 400 1.7179 2.2005 1.3384
0.0177 27.75 500 1.8454 1.9205 1.2140
0.0096 33.32 600 1.8529 1.2983 0.7777
0.0048 38.85 700 1.9306 2.3411 1.4385
0.0032 44.43 800 1.9388 1.9523 1.2705
0.0028 49.96 900 1.9472 1.8655 1.2023
0.0026 55.53 1000 1.9500 2.1895 1.3548

Framework versions

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