---
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-news-summary-model-2
  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-news-summary-model-2

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: 2.5813
- Rouge1: 29.4322
- Rouge2: 11.4361
- Rougel: 26.3875
- Rougelsum: 26.297

## 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: 4e-05
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 9.2632        | 0.9972  | 351  | 3.7059          | 17.3365 | 5.2307  | 15.438  | 15.3776   |
| 4.6719        | 1.9943  | 702  | 3.0896          | 19.5787 | 6.8278  | 18.0637 | 18.0255   |
| 4.1356        | 2.9915  | 1053 | 2.8713          | 22.5668 | 8.2899  | 20.551  | 20.5232   |
| 3.7852        | 3.9886  | 1404 | 2.7729          | 25.7974 | 9.9158  | 23.2398 | 23.2198   |
| 3.6194        | 4.9858  | 1755 | 2.7038          | 26.2572 | 10.0034 | 24.0326 | 23.9956   |
| 3.4864        | 5.9830  | 2106 | 2.6714          | 26.8149 | 9.9056  | 24.2704 | 24.1399   |
| 3.3965        | 6.9801  | 2457 | 2.6361          | 27.5399 | 10.3609 | 24.8286 | 24.7628   |
| 3.3422        | 7.9773  | 2808 | 2.6194          | 28.0298 | 10.6938 | 25.1678 | 25.0924   |
| 3.2879        | 8.9744  | 3159 | 2.5976          | 28.2324 | 10.6412 | 25.2803 | 25.1804   |
| 3.2391        | 9.9716  | 3510 | 2.5894          | 29.0155 | 11.174  | 25.9995 | 25.8843   |
| 3.2128        | 10.9688 | 3861 | 2.5854          | 29.3283 | 11.477  | 26.2235 | 26.1278   |
| 3.2214        | 11.9659 | 4212 | 2.5813          | 29.4322 | 11.4361 | 26.3875 | 26.297    |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1