---
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: 3.0132
- Rouge1: 16.4719
- Rouge2: 7.9366
- Rougel: 16.2123
- Rougelsum: 16.2853

## 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
- distributed_type: multi-GPU
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 3.9249        | 1.0   | 1209 | 3.1904          | 15.8207 | 8.0555 | 15.4584 | 15.648    |
| 3.5688        | 2.0   | 2418 | 3.0812          | 16.3271 | 8.1479 | 15.9001 | 16.0134   |
| 3.3905        | 3.0   | 3627 | 3.0442          | 15.9864 | 7.295  | 15.4247 | 15.5848   |
| 3.2728        | 4.0   | 4836 | 3.0304          | 16.2893 | 7.5851 | 15.9494 | 16.0117   |
| 3.1958        | 5.0   | 6045 | 3.0169          | 15.4888 | 7.4495 | 15.2244 | 15.2326   |
| 3.1359        | 6.0   | 7254 | 3.0158          | 16.3866 | 8.2218 | 16.0625 | 16.0953   |
| 3.1059        | 7.0   | 8463 | 3.0075          | 15.9134 | 7.8387 | 15.626  | 15.6499   |
| 3.0852        | 8.0   | 9672 | 3.0132          | 16.4719 | 7.9366 | 16.2123 | 16.2853   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.2