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EshAhm/q2v2-fake-citation-detector-scibert

sourceHugging Faceupdated 5d agoView on Hugging Face
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q2v2-fake-citation-detector-scibert

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

  • —Loss: 0.7148
  • —Accuracy: 0.5938
  • —Macro F1: 0.5883

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: 32
  • —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
  • —lrschedulerwarmup_steps: 28
  • —num_epochs: 6
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossAccuracyMacro F1
0.73291.0470.70260.51040.3725
0.68062.0940.67520.59380.5883
0.66303.01410.67150.56250.5333
0.58094.01880.68500.59380.5806
0.46185.02350.71480.59380.5883

Framework versions

  • —Transformers 5.17.0
  • —Pytorch 2.11.0+cu130
  • —Datasets 4.8.5
  • —Tokenizers 0.23.2