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Whisper Small FT Malay - CLT013

This model is a fine-tuned version of openai/whisper-small on the Malay Speech 3k dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6336

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: 0.001
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
2.1001 0.3731 100 0.8407
0.7305 0.7463 200 0.7879
0.615 1.1194 300 0.7401
0.4364 1.4925 400 0.7126
0.3951 1.8657 500 0.6772
0.2428 2.2388 600 0.6649
0.185 2.6119 700 0.6426
0.1781 2.9851 800 0.6336

Framework versions

  • PEFT 0.13.1.dev0
  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.19.1
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