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t5-small-finetuned-xsum

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

  • Loss: 2.4229
  • Rouge1: 29.1042
  • Rouge2: 8.3068
  • Rougel: 22.9912
  • Rougelsum: 22.9923
  • Gen Len: 18.8182

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: 2
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
2.676 1.0 12753 2.4477 28.6585 8.031 22.5756 22.5754 18.8202
2.6335 2.0 25506 2.4229 29.1042 8.3068 22.9912 22.9923 18.8182

Framework versions

  • Transformers 4.38.1
  • Pytorch 2.1.2
  • Datasets 2.1.0
  • Tokenizers 0.15.2
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Model tree for datht/t5-small-finetuned-xsum

Base model

google-t5/t5-small
Finetuned
this model

Dataset used to train datht/t5-small-finetuned-xsum

Evaluation results