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Whisper_large_Khmer

This model is a fine-tuned version of openai/whisper-large-v2 on the google/fleurs km_kh dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5659
  • Wer: 51.1683

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: 8
  • eval_batch_size: 16
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • total_eval_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • training_steps: 1000

Training results

Training Loss Epoch Step Validation Loss Wer
0.0002 50.0 500 0.5488 51.5328
0.0001 100.0 1000 0.5659 51.1683

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1
  • Tokenizers 0.13.2
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Dataset used to train steja/whisper-large-khmer

Evaluation results