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metadata
language:
  - tr
license: apache-2.0
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: base Turkish Whisper (bTW)
    results: []

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: 1.0034
  • Wer: 0.9507
  • Cer: 0.9543

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
1.6746 2.63 100 1.4311 0.8342 0.5210
0.7117 5.26 200 0.8645 0.9008 0.5476
0.4373 7.89 300 0.7748 0.7412 0.5489
0.2419 10.53 400 0.7788 0.6967 0.4042
0.1359 13.16 500 0.8320 0.6912 0.5735
0.055 15.79 600 0.8891 0.7571 0.7292
0.0268 18.42 700 0.9250 0.7480 0.6051
0.0133 21.05 800 0.9747 0.6906 0.7730
0.0088 23.68 900 0.9968 0.8349 0.8106
0.0077 26.32 1000 1.0034 0.9507 0.9543

Framework versions

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