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MM2157/bert-finetuned-propaganda-18

sourceHugging Faceapache-2.0updated 4y agoView on Hugging Face
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bert-finetuned-propaganda-18

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

  • —Loss: 0.6542
  • —Precision: 0.0924
  • —Recall: 0.0470
  • —F1: 0.0623
  • —Accuracy: 0.8836

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 3

Training results

Training LossEpochStepValidation LossPrecisionRecallF1Accuracy
0.66791.06700.73790.1250.00350.00690.8868
0.5482.013400.59160.08450.04350.05740.8831
0.37813.020100.65420.09240.04700.06230.8836

Framework versions

  • —Transformers 4.21.3
  • —Pytorch 1.12.1
  • —Datasets 2.4.0
  • —Tokenizers 0.12.1