---
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: 3.0295
- Rouge1: 17.3239
- Rouge2: 8.3252
- Rougel: 16.9877
- Rougelsum: 16.9491

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 6.5794        | 1.0   | 1209 | 3.2991          | 14.2697 | 5.8959 | 13.9629 | 14.019    |
| 3.8873        | 2.0   | 2418 | 3.1327          | 16.4495 | 8.0475 | 16.0014 | 15.8747   |
| 3.5776        | 3.0   | 3627 | 3.0835          | 17.5812 | 8.9516 | 17.0727 | 17.0682   |
| 3.4167        | 4.0   | 4836 | 3.0604          | 16.8649 | 8.0349 | 16.3734 | 16.4011   |
| 3.3178        | 5.0   | 6045 | 3.0599          | 17.4474 | 8.2552 | 17.1422 | 17.1661   |
| 3.242         | 6.0   | 7254 | 3.0396          | 17.8629 | 8.9654 | 17.5915 | 17.5903   |
| 3.2067        | 7.0   | 8463 | 3.0341          | 17.6749 | 8.8579 | 17.3253 | 17.3087   |
| 3.179         | 8.0   | 9672 | 3.0295          | 17.3239 | 8.3252 | 16.9877 | 16.9491   |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1