BisiX: Sundanese Whisper

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

  • Loss: 1.0180
  • Wer: 33.8787
  • Cer: 11.6897

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: 32
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 30
  • training_steps: 150
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
4.3455 0.1765 30 2.4772 85.1326 33.9863
1.7093 0.3529 60 1.3486 41.4562 15.2167
1.2183 0.5294 90 1.1469 36.2247 12.5208
1.0676 0.7059 120 1.0517 34.6427 11.9084
0.9974 0.8824 150 1.0180 33.8787 11.6897

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.19.1
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