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t5-small-finetuned-cnn-news

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

  • Loss: 1.8412
  • Rouge1: 24.7231
  • Rouge2: 12.292
  • Rougel: 20.5347
  • Rougelsum: 23.4668

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: 0.00056
  • 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: 5

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
2.0318 1.0 718 1.8028 24.5415 12.0907 20.5343 23.3386
1.8307 2.0 1436 1.8028 24.0965 11.6367 20.2078 22.8138
1.6881 3.0 2154 1.8136 25.0822 12.6509 20.9523 23.8303
1.5778 4.0 2872 1.8269 24.4271 11.8443 20.2281 23.0941
1.501 5.0 3590 1.8412 24.7231 12.292 20.5347 23.4668

Framework versions

  • Transformers 4.20.1
  • Pytorch 1.12.0+cu113
  • Datasets 2.3.2
  • Tokenizers 0.12.1
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Dataset used to train shivaniNK8/t5-small-finetuned-cnn-news

Evaluation results