Edit model card

t5-base-news_headlines

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

  • Loss: 0.9947
  • Rouge1: 53.8834
  • Rouge2: 35.147
  • Rougel: 50.8217
  • Rougelsum: 50.9105

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: 5.6e-05
  • 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: 7

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
2.0129 1.0 1531 1.5160 44.1037 21.8536 40.2425 40.3433
1.6207 2.0 3062 1.2865 46.6327 25.2538 43.0594 43.1583
1.4243 3.0 4593 1.2410 48.3304 27.729 45.0085 45.0977
1.2828 4.0 6124 1.1008 50.7514 30.7978 47.5413 47.6432
1.1796 5.0 7655 1.0646 52.4672 33.0679 49.2593 49.3381
1.1059 6.0 9186 1.0082 53.4044 34.4035 50.3925 50.4943
1.0596 7.0 10717 0.9947 53.8834 35.147 50.8217 50.9105

Framework versions

  • Transformers 4.28.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.12.0
  • Tokenizers 0.13.3
Downloads last month
7