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openai/whisper-large-v2

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: 0.8022
  • Wer: 20.0210

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
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 128
  • total_eval_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 200
  • training_steps: 500

Training results

Training Loss Epoch Step Validation Loss Wer
0.0029 8.33 100 0.6650 19.2872
0.0005 16.67 200 0.7456 18.4486
0.0003 25.0 300 0.7798 19.4969
0.0002 33.33 400 0.7964 19.7065
0.0002 41.67 500 0.8022 20.0210

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.1
  • Datasets 2.8.1.dev0
  • Tokenizers 0.13.2
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