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fs-w-he-base-en

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

  • Loss: 1.0616
  • Wer: 134.8528
  • Cer: 128.2635

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
5.5657 4.5872 500 5.7291 440.3609 462.4528
1.368 9.1743 1000 1.8578 127.8727 122.6554
0.5271 13.7615 1500 1.0031 101.1871 87.2552
0.3551 18.3486 2000 0.7689 107.6448 90.9653
0.2646 22.9358 2500 0.7395 197.5309 237.3841
0.1357 27.5229 3000 0.7802 124.2165 120.3023
0.0493 32.1101 3500 0.8682 150.9497 148.3167
0.0112 36.6972 4000 0.9626 140.2659 152.1384
0.001 41.2844 4500 1.0325 135.9924 125.2662
0.0004 45.8716 5000 1.0616 134.8528 128.2635

Framework versions

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