---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- billsum
metrics:
- rouge
model-index:
- name: 2_smtg
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: billsum
      type: billsum
      config: default
      split: ca_test
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.1982
---

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# 2_smtg

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: 1.9346
- Rouge1: 0.1982
- Rouge2: 0.1052
- Rougel: 0.1709
- Rougelsum: 0.1711
- 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: 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 124  | 2.2154          | 0.1881 | 0.0892 | 0.1571 | 0.157     | 18.996  |
| No log        | 2.0   | 248  | 2.1455          | 0.2003 | 0.1039 | 0.1695 | 0.1696    | 19.0    |
| No log        | 3.0   | 372  | 2.0963          | 0.2011 | 0.1043 | 0.1706 | 0.1706    | 19.0    |
| No log        | 4.0   | 496  | 2.0696          | 0.2014 | 0.105  | 0.1708 | 0.1708    | 19.0    |
| 2.4198        | 5.0   | 620  | 2.0437          | 0.1991 | 0.1016 | 0.1693 | 0.1694    | 19.0    |
| 2.4198        | 6.0   | 744  | 2.0256          | 0.1983 | 0.1016 | 0.1694 | 0.1695    | 19.0    |
| 2.4198        | 7.0   | 868  | 2.0109          | 0.2003 | 0.1044 | 0.1702 | 0.1705    | 19.0    |
| 2.4198        | 8.0   | 992  | 1.9969          | 0.1981 | 0.1025 | 0.1692 | 0.1694    | 19.0    |
| 2.2056        | 9.0   | 1116 | 1.9849          | 0.1984 | 0.103  | 0.1696 | 0.1699    | 19.0    |
| 2.2056        | 10.0  | 1240 | 1.9738          | 0.1985 | 0.1032 | 0.1702 | 0.1704    | 19.0    |
| 2.2056        | 11.0  | 1364 | 1.9661          | 0.1976 | 0.1029 | 0.1694 | 0.1697    | 19.0    |
| 2.2056        | 12.0  | 1488 | 1.9591          | 0.1986 | 0.1038 | 0.1704 | 0.1706    | 19.0    |
| 2.1209        | 13.0  | 1612 | 1.9535          | 0.1994 | 0.1045 | 0.1708 | 0.1709    | 19.0    |
| 2.1209        | 14.0  | 1736 | 1.9486          | 0.1986 | 0.1047 | 0.1706 | 0.1708    | 19.0    |
| 2.1209        | 15.0  | 1860 | 1.9440          | 0.1988 | 0.1053 | 0.1709 | 0.1711    | 19.0    |
| 2.1209        | 16.0  | 1984 | 1.9406          | 0.1983 | 0.1057 | 0.1708 | 0.1709    | 19.0    |
| 2.0754        | 17.0  | 2108 | 1.9378          | 0.199  | 0.1062 | 0.1712 | 0.1712    | 19.0    |
| 2.0754        | 18.0  | 2232 | 1.9361          | 0.1986 | 0.1057 | 0.1713 | 0.1714    | 19.0    |
| 2.0754        | 19.0  | 2356 | 1.9348          | 0.1986 | 0.1056 | 0.1712 | 0.1713    | 19.0    |
| 2.0754        | 20.0  | 2480 | 1.9346          | 0.1982 | 0.1052 | 0.1709 | 0.1711    | 19.0    |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1.post200
- Datasets 2.10.0
- Tokenizers 0.13.2