---
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: 7.3770
- Rouge1: 7.972
- Rouge2: 1.6667
- Rougel: 7.972
- Rougelsum: 6.4336

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 22.553        | 1.0   | 7    | 12.1593         | 7.972  | 1.6667 | 7.972  | 6.4336    |
| 20.0448       | 2.0   | 14   | 8.1176          | 7.972  | 1.6667 | 7.972  | 6.4336    |
| 17.5194       | 3.0   | 21   | 7.7753          | 7.972  | 1.6667 | 7.972  | 6.4336    |
| 18.608        | 4.0   | 28   | 7.6868          | 7.972  | 1.6667 | 7.972  | 6.4336    |
| 15.8009       | 5.0   | 35   | 7.4422          | 7.972  | 1.6667 | 7.972  | 6.4336    |
| 16.2277       | 6.0   | 42   | 7.8053          | 7.972  | 1.6667 | 7.972  | 6.4336    |
| 16.2949       | 7.0   | 49   | 7.8086          | 7.972  | 1.6667 | 7.972  | 6.4336    |
| 15.1347       | 8.0   | 56   | 7.3770          | 7.972  | 1.6667 | 7.972  | 6.4336    |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3