---
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
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# billsum-full-data

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/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