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rinna-arabert22-qa-ar2

This model is a fine-tuned version of aubmindlab/araelectra-base-discriminator on the arcd dataset. It achieves the following results on the evaluation set:

  • Loss: 5.9506

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: 0.001
  • train_batch_size: 2
  • eval_batch_size: 1
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 100

Training results

Training Loss Epoch Step Validation Loss
4.412 6.92 150 5.9506
5.9523 13.83 300 5.9506
5.9551 20.75 450 5.9506
5.952 27.67 600 5.9506
5.9518 34.58 750 5.9506
5.9501 41.5 900 5.9506
5.9526 48.41 1050 5.9506
5.9538 55.33 1200 5.9506
5.9517 62.25 1350 5.9506
5.9529 69.16 1500 5.9506
5.9518 76.08 1650 5.9506
5.9532 83.0 1800 5.9506
5.9518 89.91 1950 5.9506
5.9515 96.83 2100 5.9506

Framework versions

  • Transformers 4.32.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3
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Dataset used to train Echiguerkh/rinna-arabert22-qa-ar2