slplab / 5sents_QoLT_largev2_FT

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Model's Last Updated: November 03 2023
automatic-speech-recognition

Introduction of 5sents_QoLT_largev2_FT

Model Details of 5sents_QoLT_largev2_FT

5sents_QoLT_largev2_FT

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: 0.0110
  • Wer: 33.3333
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: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • training_steps: 600
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Wer
0.0001 49.89 100 0.0112 28.5714
0.0001 99.89 200 0.0112 28.5714
0.0001 149.89 300 0.0130 84.1270
0.0001 199.89 400 0.0153 86.7725
0.0 249.89 500 0.0166 37.5661
0.0 299.89 600 0.0171 38.0952
Framework versions
  • Transformers 4.26.1
  • Pytorch 1.13.1+cu116
  • Datasets 2.11.0
  • Tokenizers 0.13.3

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Updated:September 07 2023