Edit model card

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
Downloads last month
13
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Dataset used to train nikhedward/t5-small-finetuned-multi-news

Evaluation results