---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- summarization
- generated_from_trainer
datasets:
- govreport-summarization
metrics:
- rouge
model-index:
- name: t5-small-finetuned-govReport-3072
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: govreport-summarization
      type: govreport-summarization
      config: document
      split: validation
      args: document
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.0371
pipeline_tag: summarization
---

<!-- 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. -->

# t5-small-finetuned-govReport-3072

This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the govreport-summarization dataset.
It achieves the following results on the evaluation set:
- Loss: 3.8367
- Rouge1: 0.0371
- Rouge2: 0.0142
- Rougel: 0.0316
- Rougelsum: 0.0352

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 19.9287       | 0.99  | 31   | 11.5775         | 0.0331 | 0.0151 | 0.0293 | 0.0317    |
| 12.489        | 1.98  | 62   | 9.1322          | 0.0373 | 0.0162 | 0.0322 | 0.0351    |
| 10.8693       | 2.98  | 93   | 7.8834          | 0.0367 | 0.0153 | 0.0327 | 0.0348    |
| 9.1603        | 4.0   | 125  | 6.8580          | 0.0374 | 0.0162 | 0.0322 | 0.0355    |
| 8.2587        | 4.99  | 156  | 5.7038          | 0.0382 | 0.0154 | 0.0326 | 0.0366    |
| 6.6869        | 5.98  | 187  | 4.8553          | 0.0388 | 0.0159 | 0.0341 | 0.037     |
| 5.8997        | 6.98  | 218  | 4.3049          | 0.0383 | 0.0145 | 0.0336 | 0.036     |
| 5.0285        | 8.0   | 250  | 3.9143          | 0.0369 | 0.0138 | 0.0311 | 0.035     |
| 4.5944        | 8.99  | 281  | 3.8533          | 0.0376 | 0.0149 | 0.032  | 0.0353    |
| 4.5239        | 9.92  | 310  | 3.8367          | 0.0371 | 0.0142 | 0.0316 | 0.0352    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1