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Qarib_arabic_keyword_extraction

This model is a fine-tuned version of qarib/bert-base-qarib60_860k on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4027
  • Precision: 0.5369
  • Recall: 0.5937
  • F1: 0.5638
  • Accuracy: 0.9408

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
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 15
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.2196 1.0 750 0.1674 0.4656 0.4190 0.4411 0.9327
0.1374 2.0 1500 0.1559 0.4741 0.5255 0.4985 0.9366
0.0976 3.0 2250 0.1711 0.4901 0.5650 0.5249 0.9378
0.0676 4.0 3000 0.1928 0.4884 0.5557 0.5199 0.9363
0.0474 5.0 3750 0.2109 0.5313 0.5438 0.5375 0.9402
0.0342 6.0 4500 0.2414 0.5259 0.5754 0.5495 0.9389
0.024 7.0 5250 0.2527 0.5076 0.5881 0.5449 0.9382
0.0186 8.0 6000 0.3029 0.5379 0.5654 0.5513 0.9400
0.0143 9.0 6750 0.3154 0.5307 0.5862 0.5571 0.9398
0.0108 10.0 7500 0.3490 0.5491 0.5810 0.5646 0.9403
0.0078 11.0 8250 0.3550 0.5475 0.5929 0.5693 0.9412
0.0068 12.0 9000 0.3681 0.5360 0.6019 0.5670 0.9406
0.0049 13.0 9750 0.3873 0.5264 0.6048 0.5629 0.9402
0.004 14.0 10500 0.3987 0.5380 0.5937 0.5644 0.9407
0.0034 15.0 11250 0.4027 0.5369 0.5937 0.5638 0.9408

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.0
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