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AraT5v2-base-1024-finetuned-ar-wikilingua

This model is a fine-tuned version of UBC-NLP/AraT5v2-base-1024 on the wiki_lingua dataset. It achieves the following results on the evaluation set:

  • Loss: 4.1591
  • Rouge-1: 26.54
  • Rouge-2: 10.4
  • Rouge-l: 23.72
  • Gen Len: 18.19
  • Bertscore: 72.52

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: 5e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 250
  • num_epochs: 8
  • label_smoothing_factor: 0.1

Training results

Training Loss Epoch Step Validation Loss Rouge-1 Rouge-2 Rouge-l Gen Len Bertscore
5.2884 1.0 4998 4.4307 23.0 8.16 20.56 17.66 70.77
4.6798 2.0 9996 4.2972 24.48 8.95 21.86 17.57 71.56
4.4355 3.0 14994 4.2313 24.85 9.17 22.23 17.68 71.7
4.2772 4.0 19992 4.1972 25.41 9.5 22.65 17.63 72.08
4.1551 5.0 24990 4.1724 25.43 9.44 22.58 17.68 72.08
4.0604 6.0 29988 4.1626 25.44 9.56 22.67 17.52 72.19
3.989 7.0 34986 4.1616 25.71 9.68 22.91 17.71 72.29
3.9467 8.0 39984 4.1591 25.81 9.81 23.03 17.67 72.33

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3
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Finetuned from

Dataset used to train eslamxm/AraT5v2-base-1024-finetuned-ar-wikilingua