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fs-w-he-base

This model is a fine-tuned version of openai/whisper-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1453
  • Wer: 110.8262
  • Cer: 93.0350

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: 16
  • 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: 500
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
7.2383 4.5872 500 7.6104 178.9174 140.9825
1.348 9.1743 1000 2.0785 113.0579 96.7795
0.4859 13.7615 1500 1.1437 132.2412 113.7066
0.2809 18.3486 2000 0.9320 156.9801 142.7087
0.1568 22.9358 2500 0.9841 124.2640 115.1666
0.041 27.5229 3000 1.0475 130.6743 110.1941
0.0091 32.1101 3500 1.0947 124.5014 103.2205
0.0016 36.6972 4000 1.1475 137.9392 119.5981
0.0001 41.2844 4500 1.1431 124.0741 103.3494
0.0001 45.8716 5000 1.1453 110.8262 93.0350

Framework versions

  • Transformers 4.45.1
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.20.0
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