---
library_name: transformers
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-amazon-en-fr
  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: 3.0056
- Rouge1: 16.1556
- Rouge2: 8.8085
- Rougel: 15.8019
- Rougelsum: 15.7787

## 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_fused 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 6.9474        | 1.0   | 1399  | 3.3187          | 11.4251 | 4.57   | 10.9308 | 10.7649   |
| 3.892         | 2.0   | 2798  | 3.1469          | 13.4445 | 6.2409 | 13.013  | 12.9006   |
| 3.5863        | 3.0   | 4197  | 3.0734          | 15.1812 | 8.3203 | 14.7922 | 14.7632   |
| 3.4229        | 4.0   | 5596  | 3.0587          | 16.1014 | 8.4524 | 15.8047 | 15.7134   |
| 3.326         | 5.0   | 6995  | 3.0234          | 17.153  | 9.3495 | 16.6487 | 16.564    |
| 3.2622        | 6.0   | 8394  | 3.0144          | 15.5588 | 8.1691 | 15.275  | 15.2065   |
| 3.2163        | 7.0   | 9793  | 3.0139          | 15.8487 | 8.6641 | 15.548  | 15.511    |
| 3.1948        | 8.0   | 11192 | 3.0056          | 16.1556 | 8.8085 | 15.8019 | 15.7787   |


### Framework versions

- Transformers 4.55.4
- Pytorch 2.8.0+cu128
- Datasets 4.0.0
- Tokenizers 0.21.4