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arabert_baseline_mechanics_task2_fold1

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: 0.8879
  • Qwk: 0.5758
  • Mse: 0.8784

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 3.5975 -0.0382 3.6807
No log 0.6667 4 1.4679 0.1796 1.5092
No log 1.0 6 1.0780 0.0 1.0882
No log 1.3333 8 1.2308 0.1695 1.2193
No log 1.6667 10 1.2253 0.1695 1.2102
No log 2.0 12 0.8911 0.2451 0.8886
No log 2.3333 14 0.8137 0.3099 0.8139
No log 2.6667 16 0.8083 0.3099 0.8044
No log 3.0 18 0.9159 0.5185 0.9080
No log 3.3333 20 1.0465 0.4556 1.0353
No log 3.6667 22 0.9742 0.4731 0.9635
No log 4.0 24 0.7724 0.3897 0.7631
No log 4.3333 26 0.7534 0.3636 0.7425
No log 4.6667 28 0.7201 0.3636 0.7079
No log 5.0 30 0.8574 0.5586 0.8468
No log 5.3333 32 0.9644 0.5130 0.9546
No log 5.6667 34 0.8585 0.608 0.8487
No log 6.0 36 0.7248 0.5405 0.7112
No log 6.3333 38 0.7385 0.5405 0.7257
No log 6.6667 40 0.8072 0.5758 0.7967
No log 7.0 42 0.9702 0.6513 0.9631
No log 7.3333 44 0.9882 0.6513 0.9815
No log 7.6667 46 0.9719 0.6513 0.9651
No log 8.0 48 0.9498 0.6513 0.9425
No log 8.3333 50 0.9073 0.6513 0.8988
No log 8.6667 52 0.8907 0.5758 0.8816
No log 9.0 54 0.8763 0.5758 0.8665
No log 9.3333 56 0.8701 0.5758 0.8602
No log 9.6667 58 0.8850 0.5758 0.8754
No log 10.0 60 0.8879 0.5758 0.8784

Framework versions

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