Edit model card

t5-small-finetuned-contradiction

This model is a fine-tuned version of domenicrosati/t5-small-finetuned-contradiction on the snli dataset. It achieves the following results on the evaluation set:

  • Loss: 2.0458
  • Rouge1: 34.4237
  • Rouge2: 14.5442
  • Rougel: 32.5483
  • Rougelsum: 32.5785

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 8
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
1.8605 1.0 2863 2.0813 34.4597 14.5186 32.6909 32.7097
1.9209 2.0 5726 2.0721 34.3859 14.5733 32.5188 32.5524
1.9367 3.0 8589 2.0623 34.4192 14.455 32.581 32.5962
1.9539 4.0 11452 2.0565 34.5148 14.6131 32.6786 32.7174
1.9655 5.0 14315 2.0538 34.4393 14.6439 32.6344 32.6587
1.9683 6.0 17178 2.0493 34.7199 14.7763 32.8625 32.8782
1.9735 7.0 20041 2.0476 34.5366 14.6362 32.6939 32.7177
1.98 8.0 22904 2.0458 34.5 14.5695 32.6219 32.6478

Framework versions

  • Transformers 4.18.0
  • Pytorch 1.11.0+cu102
  • Datasets 2.1.0
  • Tokenizers 0.12.1
Downloads last month
279
Hosted inference API
Summarization
Examples
Examples
This model can be loaded on the Inference API on-demand.

Dataset used to train domenicrosati/t5-small-finetuned-contradiction

Evaluation results