---
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: 0.0899
---

<!-- 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: 3.6525
- Rouge1: 0.0899
- Rouge2: 0.0226
- Rougel: 0.0821
- Rougelsum: 0.0807

## 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: 2
- eval_batch_size: 2
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 18.5949       | 1.0   | 50   | 8.8110          | 0.0298 | 0.0    | 0.0298 | 0.0298    |
| 10.7742       | 2.0   | 100  | 5.1285          | 0.087  | 0.0087 | 0.0805 | 0.0796    |
| 7.6938        | 3.0   | 150  | 4.3645          | 0.0684 | 0.0    | 0.0579 | 0.0615    |
| 6.3393        | 4.0   | 200  | 4.0164          | 0.035  | 0.0    | 0.0355 | 0.035     |
| 5.9075        | 5.0   | 250  | 3.7881          | 0.0579 | 0.0065 | 0.051  | 0.0528    |
| 5.7394        | 6.0   | 300  | 3.6971          | 0.0749 | 0.0226 | 0.0733 | 0.0733    |
| 5.4246        | 7.0   | 350  | 3.6652          | 0.0749 | 0.0226 | 0.0733 | 0.0733    |
| 5.2963        | 8.0   | 400  | 3.6525          | 0.0899 | 0.0226 | 0.0821 | 0.0807    |


### Framework versions

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