Edit model card

t5-small-finetuned-giga

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

  • Loss: 3.2594
  • Rouge1: 26.6579
  • Rouge2: 9.5505
  • Rougel: 24.4987
  • Rougelsum: 24.5146
  • Gen Len: 13.5436

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 1
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
1.8512 1.0 23775 3.2594 26.6579 9.5505 24.4987 24.5146 13.5436

Framework versions

  • Transformers 4.24.0
  • Pytorch 1.12.1+cu113
  • Datasets 2.7.1
  • Tokenizers 0.13.2
Downloads last month
4
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 MJS2022/t5-small-finetuned-giga

Evaluation results