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metadata
license: apache-2.0
tags:
  - summarization
  - mT5_multilingual_XLSum
  - mt5
  - abstractive summarization
  - ar
  - xlsum
  - generated_from_trainer
datasets:
  - xlsum
model-index:
  - name: mt5-base-finetune-ar-xlsum
    results: []

mt5-base-finetune-ar-xlsum

This model is a fine-tuned version of google/mt5-base on the xlsum dataset. It achieves the following results on the evaluation set:

  • Loss: 3.2546
  • Rouge-1: 22.2
  • Rouge-2: 9.57
  • Rouge-l: 20.26
  • Gen Len: 19.0
  • Bertscore: 71.43

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
4.9261 1.0 585 3.6314 18.19 6.49 16.37 19.0 70.17
3.8429 2.0 1170 3.4253 19.45 7.58 17.73 19.0 70.35
3.6311 3.0 1755 3.3569 20.83 8.54 18.9 19.0 70.89
3.4917 4.0 2340 3.3101 20.77 8.53 18.89 19.0 70.98
3.3873 5.0 2925 3.2867 21.47 9.0 19.54 19.0 71.23
3.3037 6.0 3510 3.2693 21.41 9.0 19.5 19.0 71.21
3.2357 7.0 4095 3.2581 22.05 9.36 20.04 19.0 71.43
3.1798 8.0 4680 3.2522 22.21 9.56 20.23 19.0 71.41
3.1359 9.0 5265 3.2546 22.27 9.58 20.23 19.0 71.46
3.0997 10.0 5850 3.2546 22.2 9.57 20.26 19.0 71.43

Framework versions

  • Transformers 4.19.4
  • Pytorch 1.11.0+cu113
  • Datasets 2.2.2
  • Tokenizers 0.12.1