---
library_name: transformers
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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0317
- Rouge1: 16.7841
- Rouge2: 7.5923
- Rougel: 16.3966
- Rougelsum: 16.4835

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 6.5836        | 1.0   | 1209 | 3.3101          | 15.1215 | 5.97   | 14.6831 | 14.7033   |
| 3.9149        | 2.0   | 2418 | 3.1711          | 17.272  | 8.5255 | 16.8357 | 16.9754   |
| 3.5897        | 3.0   | 3627 | 3.1031          | 17.2062 | 8.8101 | 16.704  | 16.7685   |
| 3.4085        | 4.0   | 4836 | 3.0744          | 17.5033 | 8.5182 | 16.977  | 17.1305   |
| 3.3123        | 5.0   | 6045 | 3.0542          | 17.5048 | 8.1755 | 16.9628 | 17.0698   |
| 3.2467        | 6.0   | 7254 | 3.0375          | 17.1634 | 7.9483 | 16.6977 | 16.8717   |
| 3.2043        | 7.0   | 8463 | 3.0282          | 17.1609 | 8.0724 | 16.7818 | 16.9188   |
| 3.1836        | 8.0   | 9672 | 3.0317          | 16.7841 | 7.5923 | 16.3966 | 16.4835   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.1.0+cu118
- Datasets 3.1.0
- Tokenizers 0.20.3