---
license: apache-2.0
base_model: google/flan-t5-small
tags:
- generated_from_trainer
datasets:
- billsum
metrics:
- rouge
model-index:
- name: flan-t5-small-billsum
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: billsum
      type: billsum
      config: default
      split: train[17000:]
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 24.0011
---

<!-- 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. -->

# flan-t5-small-billsum

This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the billsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5675
- Rouge1: 24.0011
- Rouge2: 18.8602
- Rougel: 22.9037
- Rougelsum: 23.1161
- 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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 | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 195  | 1.6773          | 22.8625 | 17.311  | 21.829  | 22.0089   | 19.0    |
| No log        | 2.0   | 390  | 1.6134          | 23.6942 | 18.553  | 22.561  | 22.8895   | 19.0    |
| 1.9532        | 3.0   | 585  | 1.5882          | 23.8253 | 18.7086 | 22.6519 | 22.9745   | 19.0    |
| 1.9532        | 4.0   | 780  | 1.5739          | 24.0178 | 18.8429 | 22.9119 | 23.1471   | 19.0    |
| 1.9532        | 5.0   | 975  | 1.5675          | 24.0011 | 18.8602 | 22.9037 | 23.1161   | 19.0    |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3