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t5-small-finetuned-multi-news

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

  • Loss: 2.7775
  • Rouge1: 14.5549
  • Rouge2: 4.5934
  • Rougel: 11.1178
  • Rougelsum: 12.8964
  • Gen Len: 19.0

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
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • 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
3.0211 1.0 1405 2.7775 14.5549 4.5934 11.1178 12.8964 19.0

Framework versions

  • Transformers 4.17.0
  • Pytorch 1.10.0+cu111
  • Datasets 2.0.0
  • Tokenizers 0.11.6
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Dataset used to train nikhedward/t5-small-finetuned-multi-news

Evaluation results