Whisper ka

This model is a fine-tuned version of openai/whisper-small on the Subtitri voice 0.1v dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1584
  • Wer: 42.4434

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: 8
  • seed: 42
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • 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
0.0471 2.9070 1000 0.0875 46.0260
0.0058 5.8140 2000 0.1194 44.0363
0.0004 8.7209 3000 0.1400 42.8457
0.0001 11.6279 4000 0.1529 42.5829
0.0 14.5349 5000 0.1584 42.4434

Framework versions

  • Transformers 4.47.0
  • Pytorch 2.5.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.21.0
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Dataset used to train nik-o/subtitri-whisper-ka

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