T5_small_eurlexsum

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

  • Loss: 0.9360
  • Rouge1: 0.2288
  • Rouge2: 0.1816
  • Rougel: 0.2157
  • Rougelsum: 0.2158
  • 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: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 8

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 71 1.4482 0.1743 0.0982 0.1509 0.1511 19.0
No log 2.0 142 1.1661 0.193 0.1257 0.1731 0.1734 19.0
No log 3.0 213 1.0651 0.2072 0.1483 0.1892 0.1896 19.0
No log 4.0 284 1.0053 0.2167 0.1638 0.2017 0.2019 19.0
No log 5.0 355 0.9706 0.222 0.1731 0.2082 0.2079 19.0
No log 6.0 426 0.9510 0.2253 0.1771 0.2114 0.2114 19.0
No log 7.0 497 0.9393 0.2263 0.1785 0.2134 0.2133 19.0
1.4549 8.0 568 0.9360 0.2288 0.1816 0.2157 0.2158 19.0

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.13.1
  • Tokenizers 0.13.3
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Evaluation results