---
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: Mymt5-small-test
  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. -->

# Mymt5-small-test

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: 16.9555
- Rouge1: 5.3063
- Rouge2: 0.3834
- Rougel: 4.7129
- Rougelsum: 4.769

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 32.0529       | 1.0   | 10   | 22.9068         | 4.148  | 0.2063 | 4.0534 | 4.0281    |
| 26.8483       | 2.0   | 20   | 20.5579         | 4.2091 | 0.2815 | 4.2287 | 4.2414    |
| 26.3936       | 3.0   | 30   | 19.4139         | 4.199  | 0.2051 | 4.1823 | 4.1637    |
| 24.8239       | 4.0   | 40   | 18.3165         | 4.2308 | 0.2812 | 4.2404 | 4.2749    |
| 24.0505       | 5.0   | 50   | 17.3909         | 4.9556 | 0.486  | 4.6229 | 4.6138    |
| 23.8294       | 6.0   | 60   | 17.0988         | 5.4206 | 0.5003 | 4.7981 | 4.7944    |
| 22.7513       | 7.0   | 70   | 16.9862         | 5.3119 | 0.3966 | 4.814  | 4.7785    |
| 22.836        | 8.0   | 80   | 16.9555         | 5.393  | 0.3829 | 4.7334 | 4.8031    |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1