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vowelizer_1203_v8

This model is a fine-tuned version of Buseak/vowelizer_1203_v6 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0001
  • Precision: 1.0000
  • Recall: 1.0000
  • F1: 1.0000
  • Accuracy: 1.0000

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: 2e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.0731 1.0 967 0.0292 0.9860 0.9750 0.9805 0.9908
0.0462 2.0 1934 0.0171 0.9916 0.9850 0.9883 0.9945
0.0327 3.0 2901 0.0104 0.9950 0.9907 0.9929 0.9967
0.0243 4.0 3868 0.0063 0.9968 0.9953 0.9960 0.9981
0.0197 5.0 4835 0.0042 0.9979 0.9968 0.9973 0.9987
0.0159 6.0 5802 0.0031 0.9981 0.9979 0.9980 0.9991
0.0132 7.0 6769 0.0018 0.9990 0.9985 0.9988 0.9995
0.0115 8.0 7736 0.0014 0.9991 0.9991 0.9991 0.9996
0.0097 9.0 8703 0.0010 0.9994 0.9994 0.9994 0.9997
0.0082 10.0 9670 0.0007 0.9996 0.9995 0.9996 0.9998
0.0066 11.0 10637 0.0005 0.9998 0.9997 0.9998 0.9999
0.006 12.0 11604 0.0004 0.9998 0.9998 0.9998 0.9999
0.0055 13.0 12571 0.0003 0.9997 0.9997 0.9997 0.9999
0.0047 14.0 13538 0.0002 0.9999 0.9999 0.9999 1.0000
0.004 15.0 14505 0.0002 0.9999 0.9999 0.9999 1.0000
0.0034 16.0 15472 0.0001 0.9999 0.9999 0.9999 1.0000
0.0032 17.0 16439 0.0001 1.0000 1.0000 1.0000 1.0000
0.003 18.0 17406 0.0001 1.0000 1.0000 1.0000 1.0000
0.0027 19.0 18373 0.0001 1.0000 1.0000 1.0000 1.0000
0.0024 20.0 19340 0.0001 1.0000 1.0000 1.0000 1.0000

Framework versions

  • Transformers 4.28.0
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.13.3
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