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salohnana2018/OTE-domianAdaption-ABSA-Qarib-HARD-SemEval-run1

sourceHugging Faceupdated 3y agoView on Hugging Face
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OTE-domianAdaption-ABSA-Qarib-HARD-SemEval-run1

This model is a fine-tuned version of salohnana2018/Qarib-domianAdaption-OTE-ABSA-HARD-SemEvlLast on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.1350
  • —Precision: 0.7502
  • —Recall: 0.7872
  • —F1: 0.7683
  • —Accuracy: 0.9550

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: 5e-05
  • —trainbatchsize: 32
  • —evalbatchsize: 8
  • —seed: 25
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 3

Training results

Training LossEpochStepValidation LossPrecisionRecallF1Accuracy
0.1491.01210.11400.78000.74890.76410.9560
0.0812.02420.11740.77590.75730.76650.9563
0.0513.03630.13500.75020.78720.76830.9550

Framework versions

  • —Transformers 4.30.1
  • —Pytorch 2.0.1+cu118
  • —Datasets 2.12.0
  • —Tokenizers 0.13.3