---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- multi_news
metrics:
- rouge
model-index:
- name: my_awesome_billsum_model
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: multi_news
      type: multi_news
      config: default
      split: test
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.1003
---

<!-- 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. -->

# my_awesome_billsum_model

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the multi_news dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6768
- Rouge1: 0.1003
- Rouge2: 0.0337
- Rougel: 0.0777
- Rougelsum: 0.0777
- Gen Len: 19.0

## 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: 2e-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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 3.0003        | 1.0   | 22486 | 2.7383          | 0.0993 | 0.0332 | 0.077  | 0.077     | 19.0    |
| 2.9276        | 2.0   | 44972 | 2.6999          | 0.1001 | 0.0332 | 0.0774 | 0.0774    | 19.0    |
| 2.9036        | 3.0   | 67458 | 2.6795          | 0.1004 | 0.0338 | 0.0778 | 0.0778    | 19.0    |
| 2.9043        | 4.0   | 89944 | 2.6768          | 0.1003 | 0.0337 | 0.0777 | 0.0777    | 19.0    |


### Framework versions

- Transformers 4.27.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2