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Improved-Arabic-bert-nodropout

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

  • Loss: 0.8352
  • Accuracy: 0.83

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: 1e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.5185 0.55 50 0.3813 0.81
0.3312 1.1 100 0.3438 0.86
0.288 1.65 150 0.3476 0.84
0.2155 2.2 200 0.4957 0.81
0.1593 2.75 250 0.4748 0.81
0.1352 3.3 300 0.5133 0.8
0.0887 3.85 350 0.4520 0.86
0.0497 4.4 400 0.7308 0.82
0.0802 4.95 450 0.6633 0.84
0.0188 5.49 500 0.6727 0.85
0.0384 6.04 550 0.8719 0.85
0.0251 6.59 600 0.7503 0.86
0.0193 7.14 650 0.8141 0.84
0.0196 7.69 700 0.7246 0.86
0.014 8.24 750 0.8134 0.83
0.0155 8.79 800 0.7549 0.88
0.0104 9.34 850 0.7811 0.83
0.01 9.89 900 0.8459 0.83
0.004 10.44 950 0.7777 0.88
0.0007 10.99 1000 0.8015 0.87
0.0021 11.54 1050 0.7967 0.87
0.0009 12.09 1100 0.8019 0.88
0.0111 12.64 1150 0.8450 0.87
0.0003 13.19 1200 0.8463 0.84
0.0022 13.74 1250 0.8715 0.85
0.0039 14.29 1300 0.8378 0.83
0.0023 14.84 1350 0.8352 0.83

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.7
  • Tokenizers 0.14.1
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