---
license: apache-2.0
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 the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0255
- Rouge1: 17.469
- Rouge2: 8.5134
- Rougel: 17.1167
- Rougelsum: 17.2481

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 8.094         | 1.0   | 1209 | 3.2933          | 12.7976 | 5.1617 | 12.4199 | 12.5113   |
| 3.9263        | 2.0   | 2418 | 3.1487          | 16.2082 | 8.3215 | 15.744  | 15.807    |
| 3.599         | 3.0   | 3627 | 3.0789          | 16.9706 | 8.2425 | 16.3972 | 16.4067   |
| 3.429         | 4.0   | 4836 | 3.0492          | 17.2122 | 8.7398 | 16.7892 | 16.795    |
| 3.3279        | 5.0   | 6045 | 3.0384          | 17.5381 | 8.7438 | 17.0764 | 17.1831   |
| 3.2518        | 6.0   | 7254 | 3.0343          | 17.0966 | 8.5622 | 16.7016 | 16.8022   |
| 3.2084        | 7.0   | 8463 | 3.0255          | 16.7713 | 8.0472 | 16.3159 | 16.4091   |
| 3.1839        | 8.0   | 9672 | 3.0255          | 17.469  | 8.5134 | 17.1167 | 17.2481   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1