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lct-rug-2022/edos-2023-baseline-bert-base-multilingual-uncased-label_sexist

sourceHugging Faceapache-2.0updated 4y agoView on Hugging Face
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Model Card

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edos-2023-baseline-bert-base-multilingual-uncased-label_sexist

This model is a fine-tuned version of bert-base-multilingual-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.4966
  • —F1: 0.7819

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: 1e-05
  • —trainbatchsize: 32
  • —evalbatchsize: 32
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 5
  • —num_epochs: 8
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossF1
0.40911.144000.37940.7781
0.28922.298000.41850.7787
0.21593.4312000.46110.7906
0.16354.5716000.49660.7819

Framework versions

  • —Transformers 4.24.0
  • —Pytorch 1.12.1+cu113
  • —Datasets 2.7.1
  • —Tokenizers 0.13.2