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Whisper_small_Khmer

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

  • Loss: 1.9221
  • Wer: 84.9417

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: 500
  • training_steps: 2000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.5571 40.0 400 1.2022 89.9564
0.0088 80.0 800 1.7980 86.6669
0.0023 120.0 1200 1.9221 84.9417
0.0002 160.0 1600 2.0559 85.4326
0.0002 200.0 2000 2.0787 85.6536

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-small-khmer

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Evaluation results