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

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: 1.7125
- Rouge1: 0.5005
- Rouge2: 0.1542
- Rougel: 0.4577
- Rougelsum: 0.4587

## 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: 5.5e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.7151        | 1.0   | 250  | 2.2431          | 0.3662 | 0.0891 | 0.3557 | 0.3556    |
| 2.4198        | 2.0   | 500  | 2.0873          | 0.3997 | 0.1027 | 0.3884 | 0.3883    |
| 2.2232        | 3.0   | 750  | 2.0082          | 0.4453 | 0.1309 | 0.4201 | 0.4203    |
| 2.0842        | 4.0   | 1000 | 1.9100          | 0.4663 | 0.1467 | 0.4275 | 0.4274    |
| 1.9825        | 5.0   | 1250 | 1.8493          | 0.4671 | 0.1457 | 0.4228 | 0.4228    |
| 1.9048        | 6.0   | 1500 | 1.7759          | 0.49   | 0.1545 | 0.4503 | 0.4508    |
| 1.8606        | 7.0   | 1750 | 1.7438          | 0.4996 | 0.1577 | 0.4575 | 0.4585    |
| 1.8208        | 8.0   | 2000 | 1.7236          | 0.4975 | 0.1533 | 0.4555 | 0.4556    |
| 1.788         | 9.0   | 2250 | 1.7200          | 0.4983 | 0.156  | 0.4566 | 0.4572    |
| 1.7799        | 10.0  | 2500 | 1.7125          | 0.5005 | 0.1542 | 0.4577 | 0.4587    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0