---
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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7922
- Rouge1: 18.97
- Rouge2: 7.0348
- Rougel: 17.6971
- Rougelsum: 17.882

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 11.9457       | 1.0   | 151  | 4.4346          | 5.986   | 1.1429 | 5.9458  | 5.7994    |
| 5.4958        | 2.0   | 302  | 3.4869          | 7.1658  | 1.8822 | 7.2823  | 7.1334    |
| 4.4559        | 3.0   | 453  | 3.1252          | 8.5582  | 1.605  | 8.3697  | 8.302     |
| 4.0657        | 4.0   | 604  | 2.9205          | 10.6565 | 3.4667 | 10.4793 | 10.3928   |
| 3.828         | 5.0   | 755  | 2.8419          | 18.3545 | 6.8241 | 17.013  | 17.3331   |
| 3.6794        | 6.0   | 906  | 2.8178          | 18.6777 | 7.0318 | 17.2025 | 17.3807   |
| 3.6205        | 7.0   | 1057 | 2.7984          | 18.8984 | 7.0004 | 17.4826 | 17.7813   |
| 3.5711        | 8.0   | 1208 | 2.7922          | 18.97   | 7.0348 | 17.6971 | 17.882    |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3