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aomar85/M1-arabert-similiraty-without_unique-values

sourceHugging Faceupdated 4y agoView on Hugging Face
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M1-arabert-similiraty-without_unique-values

This model is a fine-tuned version of aubmindlab/bert-base-arabertv2 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1695
  • Accuracy: 0.9628
  • Precision: 0.9129
  • Recall: 0.9437
  • F1: 0.9280

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
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 10
  • mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossAccuracyPrecisionRecallF1
0.17791.0182980.13940.95500.88490.94600.9144
0.1362.0365960.15320.95560.90660.92000.9133
0.11963.0548940.13710.96050.88930.96450.9253
0.10264.0731920.15200.96070.90710.94190.9242
0.09185.0914900.16620.96220.90920.94540.9270
0.08076.01097880.16950.96280.91290.94370.9280

Framework versions

  • Transformers 4.21.3
  • Pytorch 1.12.1+cu113
  • Datasets 2.4.0
  • Tokenizers 0.12.1