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Whisper Small Ru ORD 0.7 PEFT LoRA - Mizoru

This model is a fine-tuned version of openai/whisper-small on the ORD_0.7 dataset. It achieves the following results on the evaluation set:

  • Loss: 1.4241
  • Wer: 74.5818
  • Cer: 38.6379
  • Clean Wer: 60.9733
  • Clean Cer: 30.4133

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • training_steps: 2000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer Clean Wer Clean Cer
1.3116 1.0 196 1.2595 75.2427 37.5133 59.8253 30.3495
1.1944 2.0 392 1.2362 75.3239 38.0798 61.7830 31.1456
1.137 3.0 588 1.2391 76.7957 39.3375 62.8324 31.6562
1.0293 4.0 784 1.2472 74.9783 38.2671 58.8861 30.9703
0.9835 5.0 980 1.2720 72.7755 37.0461 58.5421 28.9427
0.92 6.0 1176 1.2871 72.1532 37.6018 62.6024 30.6224
0.849 7.0 1372 1.3214 72.6281 37.3213 58.2328 29.4501
0.7708 8.0 1568 1.3527 72.0761 37.4703 60.3471 29.9594
0.7397 9.0 1764 1.3923 74.3780 38.5124 60.8670 30.1533
0.6614 10.0 1960 1.4241 74.5818 38.6379 60.9733 30.4133

Framework versions

  • PEFT 0.10.1.dev0
  • Transformers 4.41.0.dev0
  • Pytorch 2.1.2
  • Datasets 2.18.0
  • Tokenizers 0.19.1
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