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BisiX: Sundanese Whisper (Reset Params)

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: 10.7367
  • Wer: 100.0
  • Cer: 100.0

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: 64
  • eval_batch_size: 64
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • training_steps: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
10.8526 1.1765 100 10.8491 100.9708 81.1835
10.8392 2.3529 200 10.8336 1808.6292 800.3308
10.8194 3.5294 300 10.8165 2677.0607 1196.5347
10.8034 4.7059 400 10.7992 207.8742 83.6906
10.7876 5.8824 500 10.7815 148.4494 78.2801
10.7684 7.0588 600 10.7662 110.9303 77.7046
10.7567 8.2353 700 10.7537 93.9326 75.0677
10.7473 9.4118 800 10.7442 100.0 100.0
10.7389 10.5882 900 10.7386 100.0 100.0
10.7366 11.7647 1000 10.7367 100.0 100.0

Framework versions

  • Transformers 4.45.1
  • Pytorch 2.4.1+cu124
  • Datasets 3.0.1
  • Tokenizers 0.20.0
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