---
license: apache-2.0
base_model: google/mt5-small
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: 3.0279
- Rouge1: 16.4284
- Rouge2: 7.8601
- Rougel: 16.0029
- Rougelsum: 16.0246

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 4.4194        | 1.0   | 1209 | 3.3097          | 14.9867 | 6.4886 | 14.4174 | 14.4646   |
| 3.8132        | 2.0   | 2418 | 3.1602          | 16.1474 | 7.9815 | 15.5342 | 15.6445   |
| 3.5412        | 3.0   | 3627 | 3.0789          | 17.4468 | 8.8014 | 16.9142 | 17.002    |
| 3.3861        | 4.0   | 4836 | 3.0775          | 15.903  | 7.4423 | 15.4008 | 15.3871   |
| 3.2952        | 5.0   | 6045 | 3.0480          | 15.8646 | 7.3936 | 15.3989 | 15.4395   |
| 3.2155        | 6.0   | 7254 | 3.0354          | 16.5887 | 8.0624 | 16.2377 | 16.2562   |
| 3.1896        | 7.0   | 8463 | 3.0273          | 17.1092 | 8.5391 | 16.6507 | 16.7272   |
| 3.1594        | 8.0   | 9672 | 3.0279          | 16.4284 | 7.8601 | 16.0029 | 16.0246   |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3