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whisper-LARGE-AR

This model is a fine-tuned version of openai/whisper-large on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6586
  • Wer Ortho: 52.7723
  • Wer: 56.2992

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: 0.0002
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 10
  • training_steps: 50

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
0.349 0.8 50 0.6586 52.7723 56.2992

Framework versions

  • PEFT 0.11.2.dev0
  • Transformers 4.42.0.dev0
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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