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Whisper large LV - Felikss Kleins

This model is a fine-tuned version of AiLab-IMCS-UL/whisper-large-v3-lv-late-cv19 on the Recorded Voice dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1620
  • Wer: 10.8617

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: Use adamw_hf 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: 250
  • training_steps: 2500

Training results

Training Loss Epoch Step Validation Loss Wer
0.0032 36.0360 1000 0.1513 12.6354
0.0007 72.0721 2000 0.1620 10.8617

Framework versions

  • Transformers 4.46.3
  • Pytorch 2.4.1
  • Datasets 3.1.0
  • Tokenizers 0.20.3
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