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finetune_v14

This model is a fine-tuned version of openai/whisper-large-v3 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6836
  • Wer: 39.4400

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: 4
  • seed: 42
  • distributed_type: multi-GPU
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 5
  • training_steps: 80
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
No log 7.2727 10 0.6533 30.4626
No log 14.5455 20 0.6367 29.8539
No log 21.8182 30 0.6772 29.5192
No log 29.0909 40 0.6792 34.9057
0.1995 36.3636 50 0.6777 180.6147
0.1995 43.6364 60 0.6782 33.9318
0.1995 50.9091 70 0.6821 37.4924
0.1995 58.1818 80 0.6836 39.4400

Framework versions

  • Transformers 4.42.4
  • Pytorch 2.2.0
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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