transformers pytorch mt5 text2text-generation summarization generated_from_trainer dataset:mlsum base_model:google/mt5-small base_model:finetune:google/mt5-small license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: google/mt5-small
datasets:
- mlsum
license: apache-2.0
metrics:
- rouge
tags:
- summarization
- generated_from_trainer
model-index:
- name: mt5-small-finetuned-mlsum
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: mlsum
      type: mlsum
      config: fr
      split: validation
      args: fr
    metrics:
    - type: rouge
      value: 23.8523
      name: Rouge1
---

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# mt5-small-finetuned-mlsum

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the mlsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1938
- Rouge1: 23.8523
- Rouge2: 11.7959
- Rougel: 21.1838
- Rougelsum: 21.2463

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 5.6087        | 1.0   | 1005 | 2.4269          | 29.6042 | 15.5378 | 25.5964 | 25.6503   |
| 3.4099        | 2.0   | 2010 | 2.2734          | 23.8963 | 12.2351 | 21.4806 | 21.4861   |
| 3.169         | 3.0   | 3015 | 2.2310          | 26.7408 | 13.7129 | 23.7543 | 23.8443   |
| 3.0327        | 4.0   | 4020 | 2.2084          | 23.2971 | 11.5675 | 20.911  | 21.0564   |
| 2.9777        | 5.0   | 5025 | 2.1938          | 23.8523 | 11.7959 | 21.1838 | 21.2463   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
