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dstefa/mental-roberta_stress_classification

sourceHugging Facecc-by-nc-4.0updated 3y agoView on Hugging Face
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Model Card

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mental-robertastressclassification

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

  • Loss: 0.0096
  • Accuracy: 0.9984
  • F1: 0.9984
  • Precision: 0.9984
  • Recall: 0.9984

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: 5e-05
  • trainbatchsize: 8
  • evalbatchsize: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • lrschedulerwarmup_steps: 500
  • num_epochs: 2

Training results

Training LossEpochStepValidation LossAccuracyF1PrecisionRecall
0.00061.080000.02390.99660.99660.99660.9966
0.00022.0160000.00960.99840.99840.99840.9984

Framework versions

  • Transformers 4.38.0
  • Pytorch 2.2.1+cu121
  • Datasets 2.14.7
  • Tokenizers 0.15.2