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t5-large_readme_summarization

This model is a fine-tuned version of t5-large on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.7393
  • Rouge1: 0.4806
  • Rouge2: 0.3307
  • Rougel: 0.4559
  • Rougelsum: 0.4552
  • Gen Len: 13.8969

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: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 4

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
1.968 1.0 2916 1.8066 0.4624 0.3113 0.4349 0.4342 14.0995
1.8681 2.0 5832 1.7578 0.4791 0.327 0.453 0.4526 13.8046
1.875 3.0 8748 1.7441 0.479 0.3291 0.4536 0.4536 13.8909
1.8169 4.0 11664 1.7393 0.4806 0.3307 0.4559 0.4552 13.8969

Framework versions

  • Transformers 4.35.1
  • Pytorch 2.1.0+cu121
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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