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C-L-V/PsyDefDetect_roberta-base_merged_lr-4

sourceHugging Facemitupdated 6mo agoView on Hugging Face
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Model Card

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PsyDefDetectroberta-basemerged_lr-4

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

  • —Loss: 0.6981
  • —Accuracy: 0.8311
  • —Macro F1: 0.4539
  • —Weighted F1: 0.7544
  • —Macro Precision: 0.4155
  • —Macro Recall: 0.5

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: 0.0002
  • —trainbatchsize: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: linear
  • —num_epochs: 4

Training results

Training LossEpochStepValidation LossAccuracyMacro F1Weighted F1Macro PrecisionMacro Recall
0.74311.01870.69990.83110.45390.75440.41550.5
0.72202.03740.69490.16890.14450.04880.08450.5
0.69193.05610.77160.16890.14450.04880.08450.5

Framework versions

  • —Transformers 5.0.0
  • —Pytorch 2.10.0+cu128
  • —Datasets 4.0.0
  • —Tokenizers 0.22.2