transformers tensorboard safetensors mt5 text2text-generation summarization generated_from_trainer dataset:xlsum 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:
- xlsum
license: apache-2.0
metrics:
- rouge
tags:
- summarization
- generated_from_trainer
model-index:
- name: mt5-small-finetuned-summary
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: xlsum
      type: xlsum
      config: french
      split: validation
      args: french
    metrics:
    - type: rouge
      value: 21.6196
      name: Rouge1
---

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# 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: 2.1466
- Rouge1: 21.6196
- Rouge2: 7.7979
- Rougel: 17.5683
- Rougelsum: 17.6757

## 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: 4
- eval_batch_size: 4
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 3.9629        | 1.0   | 2170  | 2.3132          | 20.7316 | 7.3431 | 16.9157 | 17.0149   |
| 2.9704        | 2.0   | 4340  | 2.2299          | 21.3148 | 7.8529 | 17.2968 | 17.3873   |
| 2.8026        | 3.0   | 6510  | 2.2092          | 21.3313 | 7.8526 | 17.3679 | 17.4773   |
| 2.7054        | 4.0   | 8680  | 2.1876          | 21.6909 | 7.9841 | 17.6881 | 17.7839   |
| 2.6453        | 5.0   | 10850 | 2.1743          | 21.7372 | 7.7546 | 17.6551 | 17.7575   |
| 2.5925        | 6.0   | 13020 | 2.1602          | 21.5715 | 7.7879 | 17.5943 | 17.6994   |
| 2.5619        | 7.0   | 15190 | 2.1482          | 21.5888 | 7.8789 | 17.6519 | 17.752    |
| 2.5415        | 8.0   | 17360 | 2.1466          | 21.6196 | 7.7979 | 17.5683 | 17.6757   |


### Framework versions

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