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mt5-small-finetuned-mlsum

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

  • Loss: 2.1938
  • Rouge1: 23.8523
  • Rouge2: 11.7959
  • Rougel: 21.1838
  • Rougelsum: 21.2463

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: 5.6e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
5.6087 1.0 1005 2.4269 29.6042 15.5378 25.5964 25.6503
3.4099 2.0 2010 2.2734 23.8963 12.2351 21.4806 21.4861
3.169 3.0 3015 2.2310 26.7408 13.7129 23.7543 23.8443
3.0327 4.0 4020 2.2084 23.2971 11.5675 20.911 21.0564
2.9777 5.0 5025 2.1938 23.8523 11.7959 21.1838 21.2463

Framework versions

  • Transformers 4.34.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.14.1
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Finetuned from

Dataset used to train cleblainclb/mt5-small-finetuned-mlsum

Evaluation results