---
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: 3.0341
- Rouge1: 16.9947
- Rouge2: 8.1917
- Rougel: 16.5751
- Rougelsum: 16.6864

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 7.0901        | 1.0   | 1209 | 3.2969          | 13.9062 | 5.7456 | 13.4148 | 13.409    |
| 3.9124        | 2.0   | 2418 | 3.1529          | 16.6418 | 8.4375 | 15.85   | 15.9119   |
| 3.5991        | 3.0   | 3627 | 3.1181          | 18.7571 | 9.9189 | 18.0758 | 18.1545   |
| 3.4197        | 4.0   | 4836 | 3.0619          | 17.8796 | 8.8002 | 17.2547 | 17.3509   |
| 3.3215        | 5.0   | 6045 | 3.0706          | 16.9356 | 7.5098 | 16.2641 | 16.468    |
| 3.2448        | 6.0   | 7254 | 3.0455          | 16.7471 | 7.7886 | 16.345  | 16.4044   |
| 3.2033        | 7.0   | 8463 | 3.0349          | 17.0401 | 8.3424 | 16.6741 | 16.7633   |
| 3.177         | 8.0   | 9672 | 3.0341          | 16.9947 | 8.1917 | 16.5751 | 16.6864   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2