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HCKLab/BiBert-MultiTask-1

sourceHugging Facemitupdated 4y agoView on Hugging Face
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BiBert-MultiTask-1

This model is a fine-tuned version of nlptown/bert-base-multilingual-uncased-sentiment on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.2281
  • Accuracy: 0.7247

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: 16
  • seed: 42
  • gradientaccumulationsteps: 4
  • totaltrainbatch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 5

Training results

Training LossEpochStepValidation LossAccuracy
No log1.03451.20600.7063
0.77392.06901.18870.7103
0.61833.010351.22810.7247
0.61834.013801.26350.7103
0.51035.017251.29710.7090

Framework versions

  • Transformers 4.22.2
  • Pytorch 1.12.1+cu113
  • Datasets 2.6.1
  • Tokenizers 0.12.1