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whisper-small-khmer-aug-v6

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

  • Loss: 0.2209
  • Wer: 60.8400

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: 0.0001
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Wer
0.5473 0.9994 837 0.2368 79.1309
0.2005 2.0 1675 0.1907 69.7422
0.1505 2.9994 2512 0.1775 65.4289
0.1221 4.0 3350 0.1839 65.3802
0.1013 4.9994 4187 0.1888 64.1641
0.0851 6.0 5025 0.1921 62.8507
0.0725 6.9994 5862 0.1960 61.9588
0.0618 8.0 6700 0.2103 62.6074
0.053 8.9994 7537 0.2161 61.3426
0.0474 9.9940 8370 0.2209 60.8400

Framework versions

  • Transformers 4.44.0
  • Pytorch 2.3.1
  • Datasets 2.21.0
  • Tokenizers 0.19.1
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