---
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: 3.0303
- Rouge1: 16.5951
- Rouge2: 7.6416
- Rougel: 16.0871
- Rougelsum: 16.0029

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 6.9675        | 1.0   | 1209 | 3.2986          | 15.3916 | 6.8734 | 14.8161 | 14.7319   |
| 3.8997        | 2.0   | 2418 | 3.1665          | 16.2801 | 7.7394 | 15.7055 | 15.7013   |
| 3.5826        | 3.0   | 3627 | 3.1106          | 17.0462 | 8.4851 | 16.5069 | 16.4118   |
| 3.421         | 4.0   | 4836 | 3.0963          | 17.235  | 8.8167 | 16.7472 | 16.7047   |
| 3.3089        | 5.0   | 6045 | 3.0490          | 16.6744 | 7.6767 | 16.1951 | 16.098    |
| 3.2437        | 6.0   | 7254 | 3.0401          | 16.6011 | 7.9461 | 16.0163 | 15.9111   |
| 3.2133        | 7.0   | 8463 | 3.0292          | 16.2951 | 7.6564 | 15.9059 | 15.857    |
| 3.1851        | 8.0   | 9672 | 3.0303          | 16.5951 | 7.6416 | 16.0871 | 16.0029   |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3