CoolFace
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s3h/ar-poem-classification

sourceHugging Faceupdated 3y agoView on Hugging Face
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ar-poem-classification

This model is a fine-tuned version of aubmindlab/bert-base-arabertv02 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1427
  • Macro F1: 0.6954
  • Accuracy: 0.6944

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: 128
  • seed: 25
  • gradientaccumulationsteps: 5
  • totaltrainbatch_size: 80
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 12

Training results

Training LossEpochStepValidation LossMacro F1Accuracy
No log1.02501.08960.53190.5334
1.1142.05000.99890.58640.5826
1.1143.07500.99930.59420.5976
0.82194.010000.99490.60420.609
0.82195.012500.98130.63370.6366
0.5636.015000.96660.66570.6654
0.5637.017501.02530.66860.6668
0.37638.020001.01500.69510.6936
0.37639.022501.06190.68720.6872
0.252510.025001.10350.69290.6922
0.252511.027501.13520.69520.6944
0.18412.030001.14270.69540.6944

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.1.0+cu121
  • Tokenizers 0.15.2