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vowelizer_1203_v12

This model is a fine-tuned version of Buseak/vowelizer_1203_v11 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0000
  • 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
0.0493 1.0 967 0.0219 0.9936 0.9889 0.9913 0.9943
0.0299 2.0 1934 0.0112 0.9964 0.9952 0.9958 0.9971
0.0197 3.0 2901 0.0064 0.9980 0.9972 0.9976 0.9984
0.0143 4.0 3868 0.0039 0.9988 0.9984 0.9986 0.9990
0.0113 5.0 4835 0.0025 0.9990 0.9990 0.9990 0.9994
0.0094 6.0 5802 0.0017 0.9993 0.9993 0.9993 0.9996
0.0074 7.0 6769 0.0013 0.9993 0.9994 0.9994 0.9997
0.0063 8.0 7736 0.0007 0.9997 0.9996 0.9997 0.9998
0.0055 9.0 8703 0.0006 0.9997 0.9998 0.9997 0.9999
0.0045 10.0 9670 0.0004 0.9997 0.9998 0.9998 0.9999
0.0039 11.0 10637 0.0003 0.9998 0.9999 0.9999 0.9999
0.0031 12.0 11604 0.0002 0.9999 0.9999 0.9999 1.0000
0.0028 13.0 12571 0.0002 0.9999 0.9999 0.9999 1.0000
0.0023 14.0 13538 0.0001 1.0000 1.0000 1.0000 1.0000
0.002 15.0 14505 0.0001 1.0000 1.0000 1.0000 1.0000
0.0019 16.0 15472 0.0001 1.0000 1.0000 1.0000 1.0000
0.0017 17.0 16439 0.0001 1.0000 1.0000 1.0000 1.0000
0.0014 18.0 17406 0.0000 1.0000 1.0000 1.0000 1.0000
0.0013 19.0 18373 0.0000 1.0000 1.0000 1.0000 1.0000
0.0011 20.0 19340 0.0000 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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