---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- amazon_reviews_multi
metrics:
- rouge
model-index:
- name: t5-small-finetuned-amazon-en-es
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: amazon_reviews_multi
      type: amazon_reviews_multi
      config: en
      split: validation
      args: en
    metrics:
    - name: Rouge1
      type: rouge
      value: 18.3942
---

<!-- 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-amazon-en-es

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the amazon_reviews_multi dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2051
- Rouge1: 18.3942
- Rouge2: 10.0117
- Rougel: 17.8072
- Rougelsum: 17.6892

## 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-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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 3.3683        | 1.0   | 771  | 3.2776          | 17.0544 | 8.6801  | 16.2879 | 16.2216   |
| 3.1169        | 2.0   | 1542 | 3.2130          | 17.9604 | 9.6818  | 17.0806 | 16.9609   |
| 3.0393        | 3.0   | 2313 | 3.2003          | 18.123  | 9.554   | 17.2701 | 17.127    |
| 3.0017        | 4.0   | 3084 | 3.2051          | 18.3942 | 10.0117 | 17.8072 | 17.6892   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3