---
license: apache-2.0
base_model: google/mt5-small
tags:
- 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: 2.5259
- Rouge1: 36.6783
- Rouge2: 8.5304
- Rougel: 26.4419
- Rougelsum: 26.6455

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 3.833         | 1.0   | 250  | 2.6792          | 31.8471 | 7.6517 | 22.5413 | 22.6222   |
| 3.5861        | 2.0   | 500  | 2.6408          | 36.8204 | 8.641  | 26.7687 | 26.9114   |
| 3.411         | 3.0   | 750  | 2.6037          | 36.2502 | 7.9975 | 26.3962 | 26.502    |
| 3.29          | 4.0   | 1000 | 2.5673          | 36.7784 | 8.4415 | 26.7726 | 26.9248   |
| 3.2199        | 5.0   | 1250 | 2.5568          | 36.8812 | 8.7419 | 26.7704 | 26.8682   |
| 3.1628        | 6.0   | 1500 | 2.5280          | 37.1871 | 8.8604 | 26.9372 | 27.0992   |
| 3.1292        | 7.0   | 1750 | 2.5265          | 36.6801 | 8.5876 | 26.4392 | 26.5908   |
| 3.1129        | 8.0   | 2000 | 2.5259          | 36.6783 | 8.5304 | 26.4419 | 26.6455   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1