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wav2vec2-base-intent-classification-ori

This model is a fine-tuned version of facebook/wav2vec2-base on the intent-dataset dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4928
  • Accuracy: 0.9167

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: 3e-05
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 4
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 45

Training results

Training Loss Epoch Step Validation Loss Accuracy
2.1867 1.0 28 2.1745 0.2708
2.1177 2.0 56 2.1165 0.2708
2.1012 3.0 84 2.0553 0.2708
1.9851 4.0 112 1.9551 0.375
1.9092 5.0 140 1.9765 0.2917
1.6848 6.0 168 1.8461 0.2917
1.6576 7.0 196 1.5223 0.5
1.4492 8.0 224 1.4500 0.4792
1.2193 9.0 252 1.5349 0.4792
1.1149 10.0 280 1.2159 0.5833
1.0615 11.0 308 1.1469 0.6875
1.0584 12.0 336 1.2778 0.6042
0.8237 13.0 364 1.1774 0.5625
0.6699 14.0 392 0.9661 0.6875
0.7414 15.0 420 1.2787 0.5208
0.5324 16.0 448 0.8592 0.7292
0.3753 17.0 476 0.6860 0.7917
0.3274 18.0 504 0.6210 0.8333
0.3667 19.0 532 0.7310 0.75
0.2347 20.0 560 0.6801 0.7292
0.2036 21.0 588 0.9876 0.6875
0.1711 22.0 616 0.6323 0.7917
0.205 23.0 644 0.4414 0.8958
0.0892 24.0 672 0.4253 0.8958
0.0777 25.0 700 0.4703 0.8958
0.0717 26.0 728 0.4883 0.8958
0.041 27.0 756 0.6224 0.8542
0.0493 28.0 784 0.5839 0.875
0.0405 29.0 812 0.6454 0.8542
0.04 30.0 840 0.6102 0.875
0.0333 31.0 868 0.6080 0.875
0.0303 32.0 896 0.5539 0.875
0.025 33.0 924 0.5799 0.8958
0.0246 34.0 952 0.5766 0.8958
0.0209 35.0 980 0.5700 0.8958
0.0225 36.0 1008 0.5709 0.8958
0.0225 37.0 1036 0.5582 0.8958
0.0217 38.0 1064 0.5258 0.875
0.0207 39.0 1092 0.5058 0.8958
0.0234 40.0 1120 0.4981 0.8958
0.021 41.0 1148 0.4928 0.9167
0.0224 42.0 1176 0.4962 0.9167
0.0212 43.0 1204 0.5329 0.8958
0.0208 44.0 1232 0.5727 0.8958
0.0206 45.0 1260 0.5733 0.8958

Framework versions

  • Transformers 4.20.1
  • Pytorch 1.11.0
  • Datasets 2.1.0
  • Tokenizers 0.12.1
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