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T5-XSum-base

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

  • Loss: 2.5491
  • Rouge1: 0.273
  • Rouge2: 0.0711
  • Rougel: 0.2134
  • Rougelsum: 0.2134
  • Gen Len: 18.8194

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: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
2.8234 1.0 2041 2.5916 0.2623 0.0647 0.2043 0.2044 18.8152
2.7742 2.0 4082 2.5577 0.2707 0.0702 0.2118 0.2117 18.8212
2.7482 3.0 6123 2.5491 0.273 0.0711 0.2134 0.2134 18.8194

Framework versions

  • Transformers 4.35.0
  • Pytorch 1.12.0+cu116
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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Base model

google-t5/t5-small
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Dataset used to train alexrodpas/T5-XSum-base

Space using alexrodpas/T5-XSum-base 1

Evaluation results