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

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: 2.5691
- Rouge1: 29.8831
- Rouge2: 11.6462
- Rougel: 26.8481
- Rougelsum: 26.8856

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 8.1234        | 1.0   | 440  | 3.3123          | 18.1687 | 5.9565  | 16.7581 | 16.7495   |
| 4.2107        | 2.0   | 880  | 2.8404          | 23.0004 | 8.3723  | 20.8424 | 20.9312   |
| 3.738         | 3.0   | 1320 | 2.7354          | 26.5882 | 10.1061 | 23.9299 | 24.0001   |
| 3.4864        | 4.0   | 1760 | 2.6756          | 27.2242 | 10.1775 | 24.4504 | 24.5062   |
| 3.3642        | 5.0   | 2200 | 2.6224          | 28.7857 | 11.5222 | 26.2568 | 26.3167   |
| 3.269         | 6.0   | 2640 | 2.5883          | 29.6623 | 11.7765 | 26.8117 | 26.906    |
| 3.212         | 7.0   | 3080 | 2.5677          | 29.7811 | 11.635  | 26.5844 | 26.6327   |
| 3.186         | 8.0   | 3520 | 2.5691          | 29.8831 | 11.6462 | 26.8481 | 26.8856   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1