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t5-small-mlsum

This model is a fine-tuned version of t5-small on the mlsum dataset. It achieves the following results on the evaluation set:

  • Loss: 2.6372
  • Rouge1: 14.4732
  • Rouge2: 6.6752
  • Rougel: 13.4183
  • Rougelsum: 13.8427
  • Gen Len: 19.0

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
  • 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 Gen Len
No log 1.0 13 2.7607 14.4395 6.4679 13.2562 13.6373 19.0
No log 2.0 26 2.7068 14.4214 6.4106 13.4536 13.7502 19.0
No log 3.0 39 2.6689 14.7941 6.5511 13.6862 14.1839 19.0
No log 4.0 52 2.6450 14.3539 6.6061 13.281 13.7636 19.0
No log 5.0 65 2.6372 14.4732 6.6752 13.4183 13.8427 19.0

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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Finetuned from

Dataset used to train kamranshah/t5-small-mlsum

Evaluation results