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AraT5-base-finetune-ar-wikilingua

This model is a fine-tuned version of UBC-NLP/AraT5-base on the wiki_lingua dataset. It achieves the following results on the evaluation set:

  • Loss: 4.6110
  • Rouge-1: 19.97
  • Rouge-2: 6.9
  • Rouge-l: 18.25
  • Gen Len: 18.45
  • Bertscore: 69.44

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: 0.0005
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 250
  • num_epochs: 10
  • label_smoothing_factor: 0.1

Training results

Training Loss Epoch Step Validation Loss Rouge-1 Rouge-2 Rouge-l Gen Len Bertscore
11.5412 1.0 312 6.8825 5.2 0.69 5.04 19.0 63.2
6.5212 2.0 624 5.8992 8.89 1.4 8.36 17.92 63.9
5.8302 3.0 936 5.3712 9.99 2.21 9.54 15.87 65.08
5.406 4.0 1248 5.0632 13.94 3.5 13.0 15.95 66.83
5.1109 5.0 1560 4.8718 15.28 4.34 14.27 18.26 66.83
4.9004 6.0 1872 4.7631 16.65 4.92 15.46 17.73 67.75
4.754 7.0 2184 4.6920 18.31 5.79 16.9 18.17 68.55
4.6369 8.0 2496 4.6459 18.6 6.12 17.16 18.16 68.66
4.5595 9.0 2808 4.6153 18.94 6.1 17.39 17.82 68.99
4.4967 10.0 3120 4.6110 19.15 6.25 17.55 17.91 69.09

Framework versions

  • Transformers 4.19.4
  • Pytorch 1.11.0+cu113
  • Datasets 2.2.2
  • Tokenizers 0.12.1
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Dataset used to train eslamxm/AraT5-base-finetune-ar-wikilingua