---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- billsum
metrics:
- rouge
model-index:
- name: CS685-text-summarizer-2
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: billsum
      type: billsum
      config: default
      split: train[:37%]
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 17.4066
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# CS685-text-summarizer-2

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: 1.7516
- Rouge1: 17.4066
- Rouge2: 14.022
- Rougel: 16.9378
- Rougelsum: 17.0519

## 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: 5.6e-05
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 2.3529        | 1.0   | 1052 | 1.9277          | 17.1288 | 13.5932 | 16.6346 | 16.7728   |
| 1.9686        | 2.0   | 2104 | 1.8297          | 17.2756 | 13.7685 | 16.7924 | 16.9242   |
| 1.789         | 3.0   | 3156 | 1.7903          | 17.4219 | 14.0205 | 16.9082 | 17.0564   |
| 1.6619        | 4.0   | 4208 | 1.7632          | 17.5055 | 14.1186 | 16.996  | 17.1265   |
| 1.5819        | 5.0   | 5260 | 1.7516          | 17.4066 | 14.022  | 16.9378 | 17.0519   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3