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abdulrahman-nuzha/UBC-NLP-MARBERT-arabic-fp16-allagree

sourceHugging Faceupdated 1y agoView on Hugging Face
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UBC-NLP-MARBERT-arabic-fp16-allagree

This model is a fine-tuned version of UBC-NLP/MARBERT on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.1775
  • —Accuracy: 0.9440
  • —Precision: 0.9445
  • —Recall: 0.9440
  • —F1: 0.9440

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: 64
  • —evalbatchsize: 64
  • —seed: 42
  • —gradientaccumulationsteps: 2
  • —totaltrainbatch_size: 128
  • —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: linear
  • —lrschedulerwarmup_ratio: 0.3
  • —num_epochs: 10
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossAccuracyPrecisionRecallF1
0.95930.7463500.61990.81530.83600.81530.7805
0.35111.49251000.22410.93380.93550.93380.9343
0.18482.23881500.20020.93840.93880.93840.9383
0.14492.98512000.17750.94400.94450.94400.9440
0.08413.73132500.22980.93190.93440.93190.9326
0.05044.47763000.24290.94220.94220.94220.9415
0.03985.22393500.26080.93840.93910.93840.9387

Framework versions

  • —Transformers 4.52.4
  • —Pytorch 2.7.0+cu126
  • —Datasets 3.6.0
  • —Tokenizers 0.21.1