---
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-amazon-en-es
  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. -->

# mt5-small-finetuned-amazon-en-es

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0882
- Rouge1: 17.4498
- Rouge2: 8.7404
- Rougel: 16.8415
- Rougelsum: 16.9066

## 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 6.4445        | 1.0   | 1209 | 3.3476          | 13.3795 | 5.5143 | 12.8433 | 12.7807   |
| 3.9098        | 2.0   | 2418 | 3.2364          | 15.5805 | 7.6998 | 14.9371 | 14.9673   |
| 3.5854        | 3.0   | 3627 | 3.1560          | 17.0237 | 8.2938 | 16.3307 | 16.3798   |
| 3.4231        | 4.0   | 4836 | 3.1527          | 18.0902 | 9.0059 | 17.1599 | 17.2816   |
| 3.3166        | 5.0   | 6045 | 3.1183          | 17.5474 | 8.6267 | 16.9442 | 17.0014   |
| 3.2545        | 6.0   | 7254 | 3.0967          | 17.6619 | 8.625  | 17.0709 | 17.0763   |
| 3.2021        | 7.0   | 8463 | 3.0897          | 18.1442 | 9.1184 | 17.6043 | 17.5848   |
| 3.1818        | 8.0   | 9672 | 3.0882          | 17.4498 | 8.7404 | 16.8415 | 16.9066   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1