---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-machine-articles-tag-generation
  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-machine-articles-tag-generation

This model is a fine-tuned version of [t5-small](https://huggingface.co./t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9833
- Rouge1: 35.3543
- Rouge2: 18.1226
- Rougel: 31.3958
- Rougelsum: 31.414
- Gen Len: 17.6596

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 3.7917        | 1.0   | 47   | 3.0002          | 19.9138 | 6.9215  | 17.6969 | 17.7888   | 18.9787 |
| 3.0113        | 2.0   | 94   | 2.5823          | 22.9993 | 9.0341  | 20.8118 | 20.7657   | 18.7021 |
| 2.7086        | 3.0   | 141  | 2.3643          | 26.7716 | 12.2207 | 24.1983 | 24.2611   | 18.3298 |
| 2.5192        | 4.0   | 188  | 2.2361          | 28.5866 | 13.6305 | 26.1201 | 26.1367   | 17.9894 |
| 2.4089        | 5.0   | 235  | 2.1661          | 30.1919 | 13.8779 | 27.1523 | 27.1256   | 18.0638 |
| 2.3293        | 6.0   | 282  | 2.1185          | 31.1222 | 15.6736 | 27.3953 | 27.4457   | 17.8404 |
| 2.2635        | 7.0   | 329  | 2.0875          | 32.3166 | 16.3032 | 28.7062 | 28.732    | 17.9149 |
| 2.2349        | 8.0   | 376  | 2.0653          | 31.8387 | 15.616  | 28.3254 | 28.4288   | 17.7979 |
| 2.1945        | 9.0   | 423  | 2.0473          | 32.388  | 16.4027 | 28.5642 | 28.6096   | 17.6809 |
| 2.1658        | 10.0  | 470  | 2.0352          | 33.9489 | 16.999  | 29.8446 | 29.8251   | 17.5426 |
| 2.1414        | 11.0  | 517  | 2.0252          | 34.0804 | 17.6999 | 30.1921 | 30.2739   | 17.5106 |
| 2.1103        | 12.0  | 564  | 2.0155          | 34.3488 | 17.8273 | 30.2613 | 30.3358   | 17.5957 |
| 2.1052        | 13.0  | 611  | 2.0053          | 35.1038 | 18.3494 | 30.6999 | 30.7655   | 17.6064 |
| 2.0795        | 14.0  | 658  | 2.0004          | 35.366  | 18.8791 | 31.4931 | 31.5691   | 17.7872 |
| 2.0612        | 15.0  | 705  | 1.9951          | 36.1778 | 18.7911 | 31.5974 | 31.6309   | 17.6064 |
| 2.0792        | 16.0  | 752  | 1.9886          | 35.0387 | 18.2363 | 31.5279 | 31.5694   | 17.6702 |
| 2.0695        | 17.0  | 799  | 1.9868          | 36.1432 | 18.4902 | 31.8314 | 31.7955   | 17.617  |
| 2.0593        | 18.0  | 846  | 1.9844          | 35.7847 | 18.3497 | 31.745  | 31.7007   | 17.6809 |
| 2.0395        | 19.0  | 893  | 1.9842          | 36.0629 | 18.9649 | 32.098  | 32.0453   | 17.5745 |
| 2.0623        | 20.0  | 940  | 1.9833          | 35.3543 | 18.1226 | 31.3958 | 31.414    | 17.6596 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2