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arabert_baseline_style_task5_fold1

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metadata
base_model: aubmindlab/bert-base-arabertv02
tags:
  - generated_from_trainer
model-index:
  - name: arabert_baseline_style_task5_fold1
    results: []

arabert_baseline_style_task5_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: 0.4351
  • Qwk: 0.7772
  • Mse: 0.4351

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 3.0281 0.0186 3.0281
No log 0.6667 4 1.1102 0.0 1.1102
No log 1.0 6 0.6207 0.3478 0.6207
No log 1.3333 8 0.5268 0.3462 0.5268
No log 1.6667 10 0.5443 0.2941 0.5443
No log 2.0 12 0.4954 0.2941 0.4954
No log 2.3333 14 0.3975 0.3314 0.3975
No log 2.6667 16 0.3492 0.4828 0.3492
No log 3.0 18 0.3545 0.5238 0.3545
No log 3.3333 20 0.3763 0.6839 0.3763
No log 3.6667 22 0.4022 0.7472 0.4022
No log 4.0 24 0.4557 0.7772 0.4557
No log 4.3333 26 0.4928 0.7549 0.4928
No log 4.6667 28 0.4922 0.7549 0.4922
No log 5.0 30 0.4857 0.6939 0.4857
No log 5.3333 32 0.4759 0.6939 0.4759
No log 5.6667 34 0.4948 0.7549 0.4948
No log 6.0 36 0.4684 0.7772 0.4684
No log 6.3333 38 0.4446 0.7772 0.4446
No log 6.6667 40 0.4305 0.7772 0.4305
No log 7.0 42 0.4345 0.7222 0.4345
No log 7.3333 44 0.4345 0.6324 0.4345
No log 7.6667 46 0.4215 0.75 0.4215
No log 8.0 48 0.4192 0.7772 0.4192
No log 8.3333 50 0.4335 0.7772 0.4335
No log 8.6667 52 0.4440 0.7549 0.4440
No log 9.0 54 0.4449 0.7549 0.4449
No log 9.3333 56 0.4405 0.7549 0.4405
No log 9.6667 58 0.4375 0.7772 0.4375
No log 10.0 60 0.4351 0.7772 0.4351

Framework versions

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