Whisper Small Khmer

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

  • Loss: 0.0776
  • WER: 78.5976

Model description

Fine-tuned for automatic speech recognition (ASR) in Khmer using a combination of public and custom datasets.

Intended uses & limitations

More information needed

Training and evaluation data

Includes:

  • PhanithLIM/ams-speech-dataset
  • openslr/openslr
  • google/fleurs
  • PhanithLIM/kh-wmc
  • PhanithLIM/wmc-international-news
  • PhanithLIM/rfi-news-dataset
  • PhanithLIM/aakanee-kh
  • rinabuoy/khm-asr-open
  • seanghay/khmer_grkpp_speech
  • seanghay/khmer_mpwt_speech
  • seanghay/km-speech-corpus

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 1e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: AdamW (betas=(0.9, 0.999), eps=1e-08)
  • lr_scheduler_type: constant
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 10
  • max_steps: 56940
  • logging_steps: 500
  • save_steps: 500
  • eval_steps: 500
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss WER
0.235 1.0 5694 0.1025 80.7038
0.0872 2.0 11388 0.0852 80.3682
0.0636 3.0 17082 0.0789 79.8482
0.0494 4.0 22776 0.0776 78.5976

Framework versions

  • Transformers 4.51.3
  • PyTorch 2.5.1+cu121
  • Datasets 3.5.1
  • Tokenizers 0.21.0
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