---
language:
- id
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
- generated_from_trainer
datasets:
- id_liputan6
metrics:
- rouge
model-index:
- name: liputan6-pt-pl5
  results:
  - task:
      name: Summarization
      type: summarization
    dataset:
      name: id_liputan6 canonical
      type: id_liputan6
      config: canonical
      split: validation
      args: canonical
    metrics:
    - name: Rouge1
      type: rouge
      value: 29.4984
---

<!-- 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. -->

# liputan6-pt-pl5

This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co./LazarusNLP/IndoNanoT5-base) on the id_liputan6 canonical dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7526
- Rouge1: 29.4984
- Rouge2: 14.2115
- Rougel: 24.9259
- Rougelsum: 27.5126
- Gen Len: 59.201

## 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: 0.001
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 4.309         | 1.0   | 63   | 3.4072          | 20.861  | 8.8494  | 18.3118 | 19.3333   | 41.853  |
| 3.6184        | 2.0   | 126  | 3.1460          | 25.8149 | 9.9065  | 21.2242 | 23.6534   | 51.44   |
| 3.3773        | 3.0   | 189  | 2.9716          | 27.0263 | 11.563  | 22.6018 | 25.0075   | 55.215  |
| 3.1793        | 4.0   | 252  | 2.8266          | 28.6871 | 12.9802 | 24.038  | 26.6558   | 52.119  |
| 3.0027        | 5.0   | 315  | 2.7526          | 29.5518 | 13.5408 | 24.834  | 27.6096   | 51.956  |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1