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

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: 2.5337
- Rouge1: 21.2625
- Rouge2: 9.0676
- Rougel: 18.6959
- Rougelsum: 19.0326

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 4.4067        | 1.0   | 1875  | 2.7776          | 20.7695 | 8.5464 | 18.4037 | 18.6862   |
| 3.0128        | 2.0   | 3750  | 2.6822          | 21.0579 | 8.7229 | 18.5264 | 18.832    |
| 2.7999        | 3.0   | 5625  | 2.5896          | 21.1361 | 8.7677 | 18.5391 | 18.8411   |
| 2.6794        | 4.0   | 7500  | 2.5429          | 21.2314 | 8.9749 | 18.7468 | 19.036    |
| 2.5963        | 5.0   | 9375  | 2.5555          | 21.2005 | 8.8569 | 18.7536 | 19.0381   |
| 2.5401        | 6.0   | 11250 | 2.5464          | 21.1559 | 8.9794 | 18.572  | 18.9026   |
| 2.5099        | 7.0   | 13125 | 2.5313          | 21.0841 | 9.0057 | 18.526  | 18.8667   |
| 2.488         | 8.0   | 15000 | 2.5337          | 21.2625 | 9.0676 | 18.6959 | 19.0326   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.1+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0