---
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: 3.0283
- Rouge1: 17.0616
- Rouge2: 8.1283
- Rougel: 16.6434
- Rougelsum: 16.5615

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 6.7874        | 1.0   | 1209 | 3.3081          | 13.8568 | 5.3053 | 13.2999 | 13.2358   |
| 3.9088        | 2.0   | 2418 | 3.1782          | 16.3678 | 8.6126 | 15.9378 | 15.9707   |
| 3.5883        | 3.0   | 3627 | 3.1074          | 17.862  | 8.7925 | 17.2359 | 17.1558   |
| 3.4174        | 4.0   | 4836 | 3.0686          | 17.2836 | 8.8083 | 16.6237 | 16.6587   |
| 3.3103        | 5.0   | 6045 | 3.0487          | 16.4615 | 7.9347 | 15.9351 | 15.9312   |
| 3.251         | 6.0   | 7254 | 3.0379          | 16.9982 | 8.1573 | 16.5562 | 16.5036   |
| 3.2022        | 7.0   | 8463 | 3.0252          | 17.4796 | 8.4263 | 17.0159 | 16.9812   |
| 3.1725        | 8.0   | 9672 | 3.0283          | 17.0616 | 8.1283 | 16.6434 | 16.5615   |


### Framework versions

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