CoolFace
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J1mb0o/semantic-bert-imbalanced-dataset

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
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semantic-bert-imbalanced-dataset

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 3.3940
  • —Accuracy: 0.5926

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
  • —trainbatchsize: 16
  • —evalbatchsize: 16
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 20

Training results

Training LossEpochStepValidation LossAccuracy
No log1.03670.82370.6017
0.76082.07340.87500.5834
0.51393.011010.98290.5946
0.51394.014681.24060.5870
0.31195.018351.51680.5865
0.15016.022022.04610.5814
0.09817.025692.25750.5860
0.09818.029362.62890.5804
0.06479.033032.80790.5844
0.043610.036702.98110.5824
0.027111.040373.06690.5875
0.027112.044043.12010.5834
0.015313.047713.19800.5910
0.018914.051383.23170.5931
0.015815.055053.26590.5885
0.015816.058723.38600.5875
0.012217.062393.33020.5956
0.010718.066063.33410.5946
0.010719.069733.40420.5931
0.007820.073403.39400.5926

Framework versions

  • —Transformers 4.36.2
  • —Pytorch 2.3.0.dev20231224
  • —Datasets 2.16.0
  • —Tokenizers 0.15.0