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aomar85/fine-tuned-arabert-random-negative4-1

sourceHugging Faceupdated 4y agoView on Hugging Face
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fine-tuned-arabert-random-negative4-1

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: 0.0080
  • Accuracy: 0.9990
  • Precision: 0.9995
  • Recall: 0.9993
  • F1: 0.9994

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
0.01821.0374830.01000.99830.99830.99970.9990
0.00982.0749660.00830.99870.99950.99890.9992
0.0083.01124490.00720.99890.99950.99920.9993
0.00774.01499320.00720.99850.99960.99860.9991
0.00625.01874150.00950.99880.99930.99930.9993
0.00456.02248980.00630.99910.99960.99930.9995
0.00297.02623810.00920.99900.99950.99930.9994
0.00418.02998640.00900.99900.99950.99930.9994
0.00229.03373470.00800.99900.99950.99930.9994

Framework versions

  • Transformers 4.19.2
  • Pytorch 1.11.0+cu113
  • Datasets 2.2.2
  • Tokenizers 0.12.1