---
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-xlsum-pt
  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-xlsum-pt

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: 0.0986
- Rouge1: 16.5756
- Rouge2: 13.7639
- Rougel: 15.7445
- Rougelsum: 16.5112

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 0.7681        | 1.0   | 125  | 0.1393          | 12.9432 | 9.5039  | 12.2871 | 12.7291   |
| 0.5282        | 2.0   | 250  | 0.1231          | 13.4575 | 10.0697 | 12.6449 | 13.2      |
| 0.4132        | 3.0   | 375  | 0.1134          | 16.6964 | 14.0187 | 15.7338 | 16.6025   |
| 0.3534        | 4.0   | 500  | 0.1077          | 16.8961 | 14.2203 | 15.9187 | 16.7712   |
| 0.3126        | 5.0   | 625  | 0.1039          | 16.993  | 14.0876 | 15.8914 | 16.9277   |
| 0.283         | 6.0   | 750  | 0.1023          | 16.7431 | 13.9453 | 15.8758 | 16.6413   |
| 0.2675        | 7.0   | 875  | 0.1008          | 16.6566 | 13.8639 | 15.775  | 16.5481   |
| 0.2509        | 8.0   | 1000 | 0.0987          | 16.6829 | 13.935  | 15.872  | 16.6222   |
| 0.2441        | 9.0   | 1125 | 0.0987          | 16.6085 | 13.7884 | 15.7896 | 16.5412   |
| 0.2401        | 10.0  | 1250 | 0.0986          | 16.5756 | 13.7639 | 15.7445 | 16.5112   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2