---
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: 3.1185
- Rouge1: 17.2081
- Rouge2: 8.8374
- Rougel: 16.8033
- Rougelsum: 16.663

## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| No log        | 1.0   | 303  | 3.9821          | 8.3993  | 2.0894 | 8.1427  | 8.135     |
| No log        | 2.0   | 606  | 3.3511          | 13.1381 | 5.7193 | 12.8494 | 12.8375   |
| No log        | 3.0   | 909  | 3.2235          | 15.2502 | 6.5903 | 14.728  | 14.612    |
| 5.8943        | 4.0   | 1212 | 3.1695          | 16.1725 | 8.1638 | 15.7655 | 15.6068   |
| 5.8943        | 5.0   | 1515 | 3.1579          | 16.3126 | 7.9727 | 15.8308 | 15.7236   |
| 5.8943        | 6.0   | 1818 | 3.1346          | 16.8323 | 8.088  | 16.3863 | 16.3343   |
| 5.8943        | 7.0   | 2121 | 3.1181          | 16.965  | 8.5799 | 16.6418 | 16.5064   |
| 3.7097        | 8.0   | 2424 | 3.1185          | 17.2081 | 8.8374 | 16.8033 | 16.663    |


### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.1
- Datasets 1.17.0
- Tokenizers 0.10.3