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whisper-large-v2-Ko

This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0617
  • Wer: 2.9

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

***** train metrics *****
epoch = 50.0
train_loss = 0.0234
train_runtime = 16:20:18.00
train_samples = 22262
train_samples_per_second = 19.042
train_steps_per_second = 0.085

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 1e-05
  • train_batch_size: 32
  • eval_batch_size: 16
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 7
  • total_train_batch_size: 224
  • total_eval_batch_size: 112
  • 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
0.0299 10.0 1000 0.0745 0.0447
0.0085 20.0 2000 0.0608 0.0353
0.0036 30.0 3000 0.0593 0.0302
0.0013 40.0 4000 0.0609 0.0282
0.0008 50.0 5000 0.0617 0.0290

Framework versions

  • Transformers 4.27.0.dev0
  • Pytorch 1.12.1+cu113
  • Datasets 2.10.1
  • Tokenizers 0.13.2
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Dataset used to train byoussef/whisper-large-v2-Ko

Space using byoussef/whisper-large-v2-Ko 1

Evaluation results