---
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mT5
  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

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: 2.7797
- Rouge1: 17.5958
- Rouge2: 5.5502
- Rougel: 14.89
- Rougelsum: 15.8861

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 6.7587        | 1.0   | 313  | 3.0537          | 15.5845 | 4.426  | 12.7262 | 13.9385   |
| 3.6224        | 2.0   | 626  | 2.8799          | 16.4339 | 4.8534 | 13.3138 | 14.9449   |
| 3.3322        | 3.0   | 939  | 2.8378          | 18.1043 | 6.2202 | 15.376  | 16.5012   |
| 3.1974        | 4.0   | 1252 | 2.8008          | 17.8905 | 5.7529 | 15.0379 | 16.3205   |
| 3.1183        | 5.0   | 1565 | 2.7936          | 17.7318 | 5.4565 | 14.8508 | 15.9979   |
| 3.0522        | 6.0   | 1878 | 2.7824          | 17.6328 | 5.5352 | 14.7803 | 15.8202   |
| 3.019         | 7.0   | 2191 | 2.7846          | 17.7348 | 5.4391 | 14.7499 | 15.8859   |
| 2.9889        | 8.0   | 2504 | 2.7797          | 17.5958 | 5.5502 | 14.89   | 15.8861   |


### Framework versions

- Transformers 4.32.1
- Pytorch 1.13.0+cpu
- Datasets 2.14.4
- Tokenizers 0.13.3