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whisper-baset

This model is a fine-tuned version of openai/whisper-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0001
  • Wer: 1.9802

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: 1
  • seed: 42
  • 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
No log 100.0 100 0.0009 1.9802
No log 200.0 200 0.0003 1.9802
No log 300.0 300 0.0002 1.9802
No log 400.0 400 0.0001 1.9802
0.0555 500.0 500 0.0001 1.9802
0.0555 600.0 600 0.0001 1.9802
0.0555 700.0 700 0.0001 1.9802
0.0555 800.0 800 0.0001 1.9802
0.0555 900.0 900 0.0001 1.9802
0.0001 1000.0 1000 0.0001 1.9802

Framework versions

  • Transformers 4.40.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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