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arabert_cross_vocabulary_task7_fold3

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metadata
base_model: aubmindlab/bert-base-arabertv02
tags:
  - generated_from_trainer
model-index:
  - name: arabert_cross_vocabulary_task7_fold3
    results: []

arabert_cross_vocabulary_task7_fold3

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: 0.7581
  • Qwk: 0.0
  • Mse: 0.7581

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: 1

Training results

Training Loss Epoch Step Validation Loss Qwk Mse
No log 0.0308 2 7.8306 -0.0005 7.8306
No log 0.0615 4 4.1936 0.0 4.1936
No log 0.0923 6 2.0851 0.0593 2.0851
No log 0.1231 8 1.2404 0.0 1.2404
No log 0.1538 10 0.8586 0.0093 0.8586
No log 0.1846 12 0.7508 0.0707 0.7508
No log 0.2154 14 0.7356 0.0372 0.7356
No log 0.2462 16 0.8138 0.1082 0.8138
No log 0.2769 18 0.9262 -0.0080 0.9262
No log 0.3077 20 0.8710 -0.0045 0.8710
No log 0.3385 22 0.7502 -0.0408 0.7502
No log 0.3692 24 0.7389 0.0 0.7389
No log 0.4 26 0.7855 0.0 0.7855
No log 0.4308 28 0.7754 0.0 0.7754
No log 0.4615 30 0.7485 0.0 0.7485
No log 0.4923 32 0.7451 0.0 0.7451
No log 0.5231 34 0.7615 0.0 0.7615
No log 0.5538 36 0.7804 0.0 0.7804
No log 0.5846 38 0.7731 0.0 0.7731
No log 0.6154 40 0.7812 0.0 0.7812
No log 0.6462 42 0.8026 0.0 0.8026
No log 0.6769 44 0.8454 0.0 0.8454
No log 0.7077 46 0.8541 0.0 0.8541
No log 0.7385 48 0.8250 0.0 0.8250
No log 0.7692 50 0.8021 0.0 0.8021
No log 0.8 52 0.7828 0.0 0.7828
No log 0.8308 54 0.7701 0.0 0.7701
No log 0.8615 56 0.7633 0.0 0.7633
No log 0.8923 58 0.7561 0.0 0.7561
No log 0.9231 60 0.7554 0.0 0.7554
No log 0.9538 62 0.7563 0.0 0.7563
No log 0.9846 64 0.7581 0.0 0.7581

Framework versions

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