Edit model card

t5_billsum

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

  • Loss: 2.4902
  • Rouge1: 0.1399
  • Rouge2: 0.0492
  • Rougel: 0.1163
  • Rougelsum: 0.1161
  • 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: 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: 4

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 62 2.7895 0.13 0.0368 0.1083 0.1082 19.0
No log 2.0 124 2.5723 0.134 0.0448 0.1117 0.1114 19.0
No log 3.0 186 2.5074 0.1418 0.0505 0.1171 0.1171 19.0
No log 4.0 248 2.4902 0.1399 0.0492 0.1163 0.1161 19.0

Framework versions

  • Transformers 4.30.1
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.13.3
Downloads last month
2
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 ddiddu/t5_billsum

Evaluation results