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mbert2mbert-finetuned-ar-wikilingua

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

  • Loss: 3.6753
  • Rouge-1: 15.19
  • Rouge-2: 5.45
  • Rouge-l: 14.64
  • Gen Len: 20.0
  • Bertscore: 67.86

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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 128
  • 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

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/mbert2mbert-finetuned-ar-wikilingua