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metadata
base_model: aubmindlab/bert-base-arabertv02
tags:
  - generated_from_trainer
model-index:
  - name: arabert_baseline_vocabulary_task2_fold0
    results: []

arabert_baseline_vocabulary_task2_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: 0.5710
  • Qwk: 0.0911
  • Mse: 0.5727

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 5.7084 -0.0071 5.7092
No log 0.6667 4 2.7119 0.0524 2.7198
No log 1.0 6 1.4034 -0.0198 1.4046
No log 1.3333 8 0.6439 0.0396 0.6441
No log 1.6667 10 0.6138 0.0 0.6150
No log 2.0 12 0.6664 0.0 0.6682
No log 2.3333 14 0.6604 -0.0925 0.6596
No log 2.6667 16 0.5976 0.0526 0.5979
No log 3.0 18 0.6250 0.1747 0.6254
No log 3.3333 20 0.6646 0.1021 0.6644
No log 3.6667 22 0.5974 0.2396 0.5967
No log 4.0 24 0.5442 0.0911 0.5440
No log 4.3333 26 0.5490 0.0289 0.5512
No log 4.6667 28 0.5728 0.0 0.5758
No log 5.0 30 0.5435 0.0 0.5463
No log 5.3333 32 0.4958 0.2794 0.4980
No log 5.6667 34 0.4795 0.2105 0.4813
No log 6.0 36 0.4887 0.2167 0.4894
No log 6.3333 38 0.4972 0.2222 0.4980
No log 6.6667 40 0.5094 0.2222 0.5094
No log 7.0 42 0.5328 0.1198 0.5321
No log 7.3333 44 0.5401 0.1064 0.5397
No log 7.6667 46 0.5403 0.1064 0.5409
No log 8.0 48 0.5495 0.0911 0.5517
No log 8.3333 50 0.5683 0.0735 0.5711
No log 8.6667 52 0.5763 0.0735 0.5791
No log 9.0 54 0.5754 0.0911 0.5779
No log 9.3333 56 0.5725 0.0911 0.5748
No log 9.6667 58 0.5717 0.0911 0.5736
No log 10.0 60 0.5710 0.0911 0.5727

Framework versions

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