---
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: mt5-small-finetuned_samsum_summarization_model
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: samsum
      type: samsum
      config: samsum
      split: validation
      args: samsum
    metrics:
    - name: Rouge1
      type: rouge
      value: 39.9323
---

<!-- 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_samsum_summarization_model

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9328
- Rouge1: 39.9323
- Rouge2: 18.0293
- Rougel: 34.3611
- Rougelsum: 37.3087

## 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: 14
- eval_batch_size: 14
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 4.5012        | 1.0   | 1050 | 2.1992          | 34.6608 | 14.0886 | 29.8674 | 32.1737   |
| 2.6852        | 2.0   | 2100 | 2.1014          | 38.1793 | 16.0747 | 32.5426 | 35.4332   |
| 2.4933        | 3.0   | 3150 | 2.0319          | 38.4414 | 16.4993 | 32.6973 | 35.8539   |
| 2.3933        | 4.0   | 4200 | 1.9910          | 39.2966 | 17.1718 | 33.5556 | 36.802    |
| 2.3273        | 5.0   | 5250 | 1.9764          | 39.7619 | 17.7287 | 33.9838 | 37.1345   |
| 2.2783        | 6.0   | 6300 | 1.9503          | 39.9351 | 17.8312 | 34.2641 | 37.2625   |
| 2.2543        | 7.0   | 7350 | 1.9350          | 39.9551 | 17.918  | 34.3361 | 37.2039   |
| 2.2383        | 8.0   | 8400 | 1.9328          | 39.9323 | 18.0293 | 34.3611 | 37.3087   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0