---
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: 3.0193
- Rouge1: 17.2135
- Rouge2: 8.3357
- Rougel: 16.8793
- Rougelsum: 16.9394

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 3.6768        | 1.0   | 1209 | 3.2182          | 17.7584 | 9.2535 | 17.2471 | 17.2362   |
| 3.6447        | 2.0   | 2418 | 3.1029          | 17.5874 | 8.7799 | 16.9421 | 16.8519   |
| 3.4304        | 3.0   | 3627 | 3.0759          | 15.9059 | 7.5876 | 15.2891 | 15.3577   |
| 3.3128        | 4.0   | 4836 | 3.0706          | 17.1344 | 8.7748 | 16.6593 | 16.5961   |
| 3.2203        | 5.0   | 6045 | 3.0339          | 16.5542 | 7.7302 | 16.0354 | 16.081    |
| 3.1651        | 6.0   | 7254 | 3.0283          | 16.5324 | 8.0126 | 16.1407 | 16.1522   |
| 3.1387        | 7.0   | 8463 | 3.0188          | 16.7522 | 8.2367 | 16.4669 | 16.5025   |
| 3.1139        | 8.0   | 9672 | 3.0193          | 17.2135 | 8.3357 | 16.8793 | 16.9394   |


### Framework versions

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