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DoryDing/Depression_Detection_Model_v2

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
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DepressionDetectionModel_v2

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: 0.0711
  • Accuracy: 0.9825

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

https://github.com/DoryDing/DepressionDetectionDataset.git

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: 6

Training results

Training LossEpochStepValidation LossAccuracy
No log1.03760.09540.9683
0.10282.07520.14320.9683
0.03643.011280.07110.9825
0.01394.015040.17010.97
0.01395.018800.10930.9808
0.00596.022560.12720.9775

Framework versions

  • Transformers 4.31.0
  • Pytorch 1.13.1
  • Datasets 2.14.0
  • Tokenizers 0.13.3