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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: 2.0552
  • Wer: 1.3802
  • Cer: 0.8297

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
1.3477 33.33 100 1.8981 1.2433 0.8110
0.0238 66.67 200 1.7919 0.9340 0.5818
0.0032 100.0 300 1.8780 0.9756 0.6155
0.0014 133.33 400 1.9332 1.3582 0.8039
0.0008 166.67 500 1.9769 1.6333 0.9329
0.0005 200.0 600 2.0099 1.3790 0.8230
0.0004 233.33 700 2.0307 1.3851 0.8270
0.0004 266.67 800 2.0442 1.3851 0.8286
0.0003 300.0 900 2.0523 1.3814 0.8303
0.0003 333.33 1000 2.0552 1.3802 0.8297

Framework versions

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