metadata

license: apache-2.0
tags:
  - summarization
  - generated_from_trainer
datasets:
  - billsum
metrics:
  - rouge
model-index:
  - name: billsum-full-data
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: billsum
          type: billsum
          config: default
          split: train[:95%]
          args: default
        metrics:
          - name: Rouge1
            type: rouge
            value: 18.0383

billsum-full-data

This model is a fine-tuned version of facebook/bart-base on the billsum dataset. It achieves the following results on the evaluation set:

Loss: 1.6583
Rouge1: 18.0383
Rouge2: 14.8462
Rougel: 17.6086
Rougelsum: 17.6843

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: 5e-05
train_batch_size: 2
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
2.1401	1.0	8101	1.8087	17.8461	14.6015	17.3956	17.4842
1.7596	2.0	16202	1.6980	18.0568	14.7833	17.6068	17.6999
1.5789	3.0	24303	1.6583	18.0383	14.8462	17.6086	17.6843

Framework versions

Transformers 4.29.1
Pytorch 2.0.0
Datasets 2.12.0
Tokenizers 0.13.3