transformers pytorch tensorboard bart text2text-generation summarization generated_from_trainer dataset:multi_news license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- multi_news
license: apache-2.0
metrics:
- rouge
tags:
- summarization
- generated_from_trainer
model-index:
- name: CS685-text-summarizer
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: multi_news
      type: multi_news
      config: default
      split: train[:20%]
      args: default
    metrics:
    - type: rouge
      value: 9.8777
      name: Rouge1
---

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# CS685-text-summarizer

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the multi_news dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4960
- Rouge1: 9.8777
- Rouge2: 3.6509
- Rougel: 7.597
- Rougelsum: 9.0495

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.8402        | 1.0   | 1349 | 2.5256          | 9.7548 | 3.5429 | 7.5078 | 8.9174    |
| 2.5581        | 2.0   | 2698 | 2.5011          | 9.7256 | 3.6262 | 7.5644 | 8.8904    |
| 2.3908        | 3.0   | 4047 | 2.4948          | 9.7569 | 3.5976 | 7.5209 | 8.8919    |
| 2.2744        | 4.0   | 5396 | 2.4875          | 9.9116 | 3.7758 | 7.6823 | 9.0881    |
| 2.1908        | 5.0   | 6745 | 2.4960          | 9.8777 | 3.6509 | 7.597  | 9.0495    |


### Framework versions

- Transformers 4.29.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
