PhanithLIM / whisper-tiny-aug-26dec

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Model's Last Updated: 2024年12月29日
automatic-speech-recognition

Introduction of whisper-tiny-aug-26dec

Model Details of whisper-tiny-aug-26dec

small-tindy-aug-26dec

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

  • Loss: 0.2720
  • Wer: 82.4497
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: 16
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 15
Training results
Training Loss Epoch Step Validation Loss Wer
1.4654 1.0 272 1.2543 113.9215
1.0788 2.0 544 0.8559 105.8815
0.7043 3.0 816 0.5695 97.9140
0.5241 4.0 1088 0.4696 94.4734
0.4376 5.0 1360 0.4099 90.9894
0.3814 6.0 1632 0.3720 90.8953
0.3414 7.0 1904 0.3490 87.5489
0.3127 8.0 2176 0.3282 85.8395
0.29 9.0 2448 0.3132 85.5425
0.2691 10.0 2720 0.3018 84.6516
0.2525 11.0 2992 0.2949 84.6733
0.2365 12.0 3264 0.2878 85.1586
0.2235 13.0 3536 0.2787 82.1744
0.2117 14.0 3808 0.2770 81.7181
0.2004 15.0 4080 0.2720 82.4497
Framework versions
  • Transformers 4.45.2
  • Pytorch 2.4.0
  • Datasets 3.2.0
  • Tokenizers 0.20.3

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