---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- govreport-summarization
metrics:
- rouge
model-index:
- name: flan-t5-gov-report-sum
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: govreport-summarization
      type: govreport-summarization
      config: document
      split: test
      args: document
    metrics:
    - name: Rouge1
      type: rouge
      value: 5.8729
---

<!-- 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-gov-report-sum

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the govreport-summarization dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2385
- Rouge1: 5.8729
- Rouge2: 3.0763
- Rougel: 5.1016
- Rougelsum: 5.646
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.5801        | 1.0   | 2190  | 2.3211          | 5.6226 | 2.9142 | 4.9535 | 5.417     | 19.0    |
| 2.5125        | 2.0   | 4380  | 2.2748          | 5.7982 | 3.0365 | 5.0726 | 5.5837    | 19.0    |
| 2.453         | 3.0   | 6570  | 2.2545          | 5.8744 | 3.0997 | 5.1196 | 5.6524    | 19.0    |
| 2.436         | 4.0   | 8760  | 2.2430          | 5.8669 | 3.0525 | 5.0849 | 5.631     | 19.0    |
| 2.4144        | 5.0   | 10950 | 2.2385          | 5.8729 | 3.0763 | 5.1016 | 5.646     | 19.0    |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.11.0+cu102
- Datasets 2.9.0
- Tokenizers 0.13.2