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C-L-V/PsyDefDetect_roberta-base_merged_lr-5

sourceHugging Facemitupdated 6mo agoView on Hugging Face
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PsyDefDetectroberta-basemerged_lr-5

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

  • —Loss: 0.5063
  • —Accuracy: 0.9491
  • —Macro F1: 0.9023
  • —Weighted F1: 0.9471
  • —Macro Precision: 0.9382
  • —Macro Recall: 0.8745

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: 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
0.63241.01870.63310.87940.70130.85400.89330.6555
0.55632.03740.69530.92490.84100.91750.93540.7904
0.41713.05610.50720.94910.90230.94710.93820.8745
0.28024.07480.46980.94370.89780.94310.90580.8902

Framework versions

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