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metadata
base_model: aubmindlab/bert-base-arabertv02
tags:
  - generated_from_trainer
model-index:
  - name: arabert_baseline_mechanics_task2_fold0
    results: []

arabert_baseline_mechanics_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: 0.9842
  • Qwk: 0.1750
  • Mse: 0.9841

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 4.1574 0.0205 4.1715
No log 0.6667 4 2.0929 0.0123 2.1054
No log 1.0 6 1.3194 -0.1337 1.3202
No log 1.3333 8 0.9360 0.2588 0.9322
No log 1.6667 10 0.9386 0.0907 0.9344
No log 2.0 12 1.1338 -0.0221 1.1277
No log 2.3333 14 1.0683 0.0907 1.0627
No log 2.6667 16 0.8193 0.2808 0.8154
No log 3.0 18 0.7951 0.2441 0.7912
No log 3.3333 20 0.8524 0.2853 0.8486
No log 3.6667 22 1.0382 -0.1210 1.0361
No log 4.0 24 1.2097 -0.1351 1.2090
No log 4.3333 26 1.3025 -0.0355 1.3038
No log 4.6667 28 1.1375 0.2732 1.1373
No log 5.0 30 0.8628 0.2455 0.8539
No log 5.3333 32 0.8145 0.1649 0.8046
No log 5.6667 34 0.8765 0.2222 0.8718
No log 6.0 36 0.9949 0.1892 0.9951
No log 6.3333 38 1.0164 0.1892 1.0171
No log 6.6667 40 0.9913 0.1892 0.9919
No log 7.0 42 0.9485 0.1892 0.9484
No log 7.3333 44 0.9129 0.0667 0.9120
No log 7.6667 46 0.8943 0.0667 0.8925
No log 8.0 48 0.9394 0.0667 0.9387
No log 8.3333 50 0.9883 0.1892 0.9886
No log 8.6667 52 0.9904 0.1892 0.9907
No log 9.0 54 0.9905 0.1892 0.9908
No log 9.3333 56 0.9842 0.1892 0.9843
No log 9.6667 58 0.9876 0.1664 0.9876
No log 10.0 60 0.9842 0.1750 0.9841

Framework versions

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