---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-article
  results: []
---

<!-- 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-article

This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1645
- Rouge1: 33.3436
- Rouge2: 16.5897
- Rougel: 28.335
- Rougelsum: 31.1228

## 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: 5.6e-08
- 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: 8

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 2.5953        | 1.0   | 1880  | 2.3487          | 31.0337 | 15.0267 | 26.0027 | 28.8777   |
| 2.5437        | 2.0   | 3760  | 2.2894          | 31.838  | 15.394  | 26.7426 | 29.625    |
| 2.5054        | 3.0   | 5640  | 2.2434          | 32.034  | 15.5701 | 26.913  | 29.8383   |
| 2.474         | 4.0   | 7520  | 2.2104          | 32.0455 | 15.5593 | 27.0056 | 29.8549   |
| 2.4456        | 5.0   | 9400  | 2.1876          | 32.7165 | 16.1007 | 27.6665 | 30.5147   |
| 2.4295        | 6.0   | 11280 | 2.1734          | 33.0987 | 16.3509 | 28.011  | 30.8393   |
| 2.4205        | 7.0   | 13160 | 2.1662          | 33.2262 | 16.4986 | 28.1781 | 30.9915   |
| 2.4165        | 8.0   | 15040 | 2.1645          | 33.3436 | 16.5897 | 28.335  | 31.1228   |


### Framework versions

- Transformers 4.28.0
- Pytorch 1.13.1+cu117
- Datasets 2.18.0
- Tokenizers 0.13.3