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metadata
base_model: aubmindlab/bert-base-arabertv02
tags:
  - generated_from_trainer
model-index:
  - name: arabert_baseline_organization_task7_fold1
    results: []

arabert_baseline_organization_task7_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: 0.6217
  • Qwk: 0.4969
  • Mse: 0.6213

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 1.0245 0.3758 1.0297
No log 0.6667 4 0.7919 0.5312 0.8059
No log 1.0 6 0.8469 0.6400 0.8626
No log 1.3333 8 0.7621 0.3793 0.7785
No log 1.6667 10 0.8831 0.2326 0.8970
No log 2.0 12 0.7493 0.4 0.7628
No log 2.3333 14 0.4924 0.6165 0.5052
No log 2.6667 16 0.4499 0.6571 0.4612
No log 3.0 18 0.4936 0.6203 0.5029
No log 3.3333 20 0.7252 0.4224 0.7311
No log 3.6667 22 0.9227 0.3657 0.9263
No log 4.0 24 0.8957 0.3657 0.8980
No log 4.3333 26 0.7242 0.4211 0.7260
No log 4.6667 28 0.5595 0.6203 0.5620
No log 5.0 30 0.4521 0.6024 0.4559
No log 5.3333 32 0.4402 0.6786 0.4437
No log 5.6667 34 0.4703 0.6909 0.4728
No log 6.0 36 0.6144 0.5 0.6153
No log 6.3333 38 0.7150 0.4969 0.7150
No log 6.6667 40 0.7022 0.4969 0.7024
No log 7.0 42 0.6409 0.5 0.6418
No log 7.3333 44 0.5912 0.5 0.5923
No log 7.6667 46 0.5457 0.6341 0.5469
No log 8.0 48 0.5073 0.6909 0.5089
No log 8.3333 50 0.5143 0.6909 0.5157
No log 8.6667 52 0.5540 0.6341 0.5549
No log 9.0 54 0.5883 0.6272 0.5886
No log 9.3333 56 0.6103 0.4969 0.6102
No log 9.6667 58 0.6204 0.4969 0.6200
No log 10.0 60 0.6217 0.4969 0.6213

Framework versions

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