---
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
datasets:
- xlsum
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-summary
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: xlsum
      type: xlsum
      config: french
      split: validation
      args: french
    metrics:
    - name: Rouge1
      type: rouge
      value: 22.1761
---

<!-- 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-finetuned-summary

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the xlsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2770
- Rouge1: 22.1761
- Rouge2: 8.0115
- Rougel: 18.8245
- Rougelsum: 18.8574

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 4.7862        | 1.0   | 1085 | 2.5085          | 21.2935 | 7.4006 | 18.0791 | 18.0868   |
| 3.2212        | 2.0   | 2170 | 2.4069          | 21.968  | 7.9139 | 18.5785 | 18.6248   |
| 3.0201        | 3.0   | 3255 | 2.3489          | 21.8529 | 7.9865 | 18.6842 | 18.7074   |
| 2.9085        | 4.0   | 4340 | 2.3173          | 22.1605 | 8.2646 | 18.8284 | 18.838    |
| 2.8285        | 5.0   | 5425 | 2.2965          | 22.0612 | 8.0447 | 18.7454 | 18.7784   |
| 2.7727        | 6.0   | 6510 | 2.2899          | 22.1416 | 7.9747 | 18.7622 | 18.8029   |
| 2.7311        | 7.0   | 7595 | 2.2797          | 22.2979 | 8.1382 | 18.9798 | 19.035    |
| 2.7171        | 8.0   | 8680 | 2.2770          | 22.1761 | 8.0115 | 18.8245 | 18.8574   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0