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salmon-whisper-large-smj-lr5e-5

This model is a fine-tuned version of openai/whisper-large-v2 on the NbAiLab/salmon-asr-smj dataset.

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: 5e-05
  • lr_scheduler_type: linear
  • per_device_train_batch_size: 6
  • total_train_batch_size_per_node: 48
  • total_train_batch_size: 48
  • total_optimization_steps: 60,000
  • starting_optimization_step: 40,000
  • finishing_optimization_step: 100,000
  • num_train_dataset_workers: 32
  • num_hosts: 1
  • total_num_training_examples: 4,800,000
  • steps_per_epoch: 1169
  • num_beams: None
  • weight_decay: 0.01
  • adam_beta1: 0.9
  • adam_beta2: 0.98
  • adam_epsilon: 1e-06
  • dropout: True
  • bpe_dropout_probability: 0.2
  • activation_dropout_probability: 0.1

Training results

step validation_loss train_loss validation_wer validation_cer validation_exact_wer validation_exact_cer
0 4.2254 4.6413 112.7660 59.8700 108.1117 62.0594
10000 0.8720 0.3747 18.2181 5.2803 21.4096 5.6762
20000 1.1365 0.2741 15.2926 4.6304 18.0851 5.0588
30000 1.2561 0.2111 14.6277 4.0617 17.9521 4.5011
40000 33.1032 10.4733 100.0 100.0 100.0 98.0681
50000 3.0192 2.5972 100.7979 80.9301 101.3298 79.8447
60000 2.7909 2.0728 99.6011 79.8944 100.5319 78.8688

Framework versions

  • Transformers 4.35.0
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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