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test-summarization

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

  • Loss: 2.4496
  • Rouge1: 28.7363
  • Rouge2: 8.023
  • Rougel: 22.6496
  • Rougelsum: 22.644
  • Gen Len: 18.8226

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: 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: 1

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
2.6873 1.0 25506 2.4496 28.7363 8.023 22.6496 22.644 18.8226

Framework versions

  • Transformers 4.34.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.14.1
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Base model

google-t5/t5-small
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Dataset used to train yulittlemoon/test-summarization

Evaluation results