---
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[:20%]
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 17.1607
---

<!-- 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: 1.7651
- Rouge1: 17.1607
- Rouge2: 13.943
- Rougel: 16.6793
- Rougelsum: 16.8422

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 2.4547        | 1.0   | 569  | 1.9895          | 16.6343 | 13.0432 | 16.1262 | 16.2449   |
| 2.0246        | 2.0   | 1138 | 1.8688          | 16.939  | 13.4711 | 16.4359 | 16.5797   |
| 1.818         | 3.0   | 1707 | 1.8075          | 17.1388 | 13.827  | 16.6136 | 16.7574   |
| 1.6831        | 4.0   | 2276 | 1.7744          | 17.2292 | 13.9353 | 16.6961 | 16.8786   |
| 1.5956        | 5.0   | 2845 | 1.7651          | 17.1607 | 13.943  | 16.6793 | 16.8422   |


### Framework versions

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