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arabert_baseline_organization_task7_fold0

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metadata
base_model: aubmindlab/bert-base-arabertv02
tags:
  - generated_from_trainer
model-index:
  - name: arabert_baseline_organization_task7_fold0
    results: []

arabert_baseline_organization_task7_fold0

This model is a fine-tuned version of aubmindlab/bert-base-arabertv02 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4509
  • Qwk: 0.6
  • Mse: 0.4509

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: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Qwk Mse
No log 0.3333 2 1.2538 0.1333 1.2538
No log 0.6667 4 0.6732 0.5116 0.6732
No log 1.0 6 1.0128 0.3810 1.0128
No log 1.3333 8 0.6424 0.5455 0.6424
No log 1.6667 10 0.6331 0.5455 0.6331
No log 2.0 12 0.6841 0.5455 0.6841
No log 2.3333 14 0.6488 0.5306 0.6488
No log 2.6667 16 0.7438 0.5185 0.7438
No log 3.0 18 1.0106 0.3636 1.0106
No log 3.3333 20 1.0009 0.3810 1.0009
No log 3.6667 22 0.6870 0.5098 0.6870
No log 4.0 24 0.5375 0.5106 0.5375
No log 4.3333 26 0.5197 0.55 0.5197
No log 4.6667 28 0.5082 0.5366 0.5082
No log 5.0 30 0.5130 0.5652 0.5130
No log 5.3333 32 0.5730 0.56 0.5730
No log 5.6667 34 0.5916 0.56 0.5916
No log 6.0 36 0.5065 0.5306 0.5065
No log 6.3333 38 0.4667 0.6 0.4667
No log 6.6667 40 0.4403 0.6 0.4403
No log 7.0 42 0.4374 0.6 0.4374
No log 7.3333 44 0.4427 0.6 0.4427
No log 7.6667 46 0.4590 0.6 0.4590
No log 8.0 48 0.4783 0.6275 0.4783
No log 8.3333 50 0.4751 0.6275 0.4751
No log 8.6667 52 0.4701 0.6275 0.4701
No log 9.0 54 0.4678 0.6275 0.4678
No log 9.3333 56 0.4574 0.6275 0.4574
No log 9.6667 58 0.4535 0.6 0.4535
No log 10.0 60 0.4509 0.6 0.4509

Framework versions

  • Transformers 4.44.0
  • Pytorch 2.4.0
  • Datasets 2.21.0
  • Tokenizers 0.19.1