---
license: apache-2.0
tags:
- translation
- 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: 17.5202
- Rouge2: 8.4634
- Rougel: 17.0175
- Rougelsum: 17.0528

## 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          | 12.7563 | 5.2606 | 12.4786 | 12.4961   |
| 3.9263        | 2.0   | 2418 | 3.1487          | 16.2314 | 8.4716 | 15.6854 | 15.7506   |
| 3.599         | 3.0   | 3627 | 3.0789          | 16.9233 | 8.1928 | 16.2596 | 16.2522   |
| 3.429         | 4.0   | 4836 | 3.0492          | 17.2679 | 8.7561 | 16.6685 | 16.7399   |
| 3.3279        | 5.0   | 6045 | 3.0384          | 17.6081 | 8.6721 | 17.0546 | 17.0368   |
| 3.2518        | 6.0   | 7254 | 3.0343          | 17.2271 | 8.504  | 16.6285 | 16.6209   |
| 3.2084        | 7.0   | 8463 | 3.0255          | 16.7859 | 8.054  | 16.2574 | 16.2853   |
| 3.1839        | 8.0   | 9672 | 3.0255          | 17.5202 | 8.4634 | 17.0175 | 17.0528   |


### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.6