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t5-small-finetuned-giga

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

  • Loss: 3.2594
  • Rouge1: 26.6579
  • Rouge2: 9.5505
  • Rougel: 24.4987
  • Rougelsum: 24.5146
  • Gen Len: 13.5436

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: 1
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
1.8512 1.0 23775 3.2594 26.6579 9.5505 24.4987 24.5146 13.5436

Framework versions

  • Transformers 4.24.0
  • Pytorch 1.12.1+cu113
  • Datasets 2.7.1
  • Tokenizers 0.13.2
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Dataset used to train MJS2022/t5-small-finetuned-giga

Evaluation results