---
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: 17.0896
- Rouge2: 8.362
- Rougel: 16.735
- Rougelsum: 16.8131

## 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          | 17.7059 | 9.3629 | 17.1633 | 17.2774   |
| 3.6447        | 2.0   | 2418 | 3.1029          | 17.4241 | 8.8479 | 16.9706 | 16.9578   |
| 3.4304        | 3.0   | 3627 | 3.0759          | 15.8371 | 7.5702 | 15.2312 | 15.3302   |
| 3.3128        | 4.0   | 4836 | 3.0706          | 16.9745 | 8.7666 | 16.559  | 16.6638   |
| 3.2203        | 5.0   | 6045 | 3.0339          | 16.3788 | 7.769  | 15.9624 | 16.027    |
| 3.1651        | 6.0   | 7254 | 3.0283          | 16.4083 | 8.0507 | 15.9778 | 16.1114   |
| 3.1387        | 7.0   | 8463 | 3.0188          | 16.6289 | 8.2229 | 16.3528 | 16.3952   |
| 3.1139        | 8.0   | 9672 | 3.0193          | 17.0896 | 8.362  | 16.735  | 16.8131   |


### Framework versions

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