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Whisper Base Turkish

This model is a fine-tuned version of arun100/whisper-base-tr-1 on the google/fleurs tr_tr dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5195
  • Wer: 28.3845

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-06
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 2
  • 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: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.3503 45.0 500 0.4874 29.1817
0.0695 90.0 1000 0.4960 28.4597
0.0243 136.0 1500 0.5195 28.3845
0.0145 181.0 2000 0.5334 28.6477
0.0101 227.0 2500 0.5454 28.6778
0.0077 272.0 3000 0.5548 28.6928
0.0063 318.0 3500 0.5625 28.7079
0.0054 363.0 4000 0.5684 29.0238
0.0048 409.0 4500 0.5727 28.9260
0.0046 454.0 5000 0.5743 28.9260

Framework versions

  • Transformers 4.38.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.16.2.dev0
  • Tokenizers 0.15.0
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Safetensors
Model size
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Finetuned from

Dataset used to train arun100/whisper-base-tr-2

Evaluation results