---
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-amazon-en-es
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: xsum
      type: xsum
      config: default
      split: validation
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.0524
---

<!-- 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 xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 8.0085
- Rouge1: 0.0524
- Rouge2: 0.0083
- Rougel: 0.0416
- Rougelsum: 0.0416

## 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   | 4    | 12.7017         | 0.0208 | 0.0    | 0.0148 | 0.0148    |
| No log        | 2.0   | 8    | 10.3879         | 0.0208 | 0.0    | 0.0148 | 0.0148    |
| 18.6837       | 3.0   | 12   | 9.1367          | 0.0208 | 0.0    | 0.0148 | 0.0148    |
| 18.6837       | 4.0   | 16   | 8.6067          | 0.0269 | 0.0    | 0.0209 | 0.0209    |
| 18.6837       | 5.0   | 20   | 8.2033          | 0.0377 | 0.0    | 0.026  | 0.0256    |
| 15.292        | 6.0   | 24   | 8.1000          | 0.0524 | 0.0083 | 0.0416 | 0.0416    |
| 15.292        | 7.0   | 28   | 8.0750          | 0.0524 | 0.0083 | 0.0416 | 0.0416    |
| 15.292        | 8.0   | 32   | 8.0085          | 0.0524 | 0.0083 | 0.0416 | 0.0416    |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu118
- Datasets 2.17.1
- Tokenizers 0.15.2