---
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: 18.3412
---

<!-- 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: 3.8205
- Rouge1: 18.3412
- Rouge2: 4.7361
- Rougel: 15.5136
- Rougelsum: 16.6913
- Gen Len: 35.5

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 4.799         | 1.0   | 63   | 4.1142          | 13.0788 | 2.2394 | 10.8409 | 11.8062   | 40.873  |
| 4.179         | 2.0   | 126  | 3.9928          | 16.7604 | 3.2541 | 13.8889 | 15.1654   | 32.962  |
| 3.9656        | 3.0   | 189  | 3.8832          | 18.1366 | 3.9918 | 15.2392 | 16.4266   | 30.549  |
| 3.8038        | 4.0   | 252  | 3.8552          | 18.2504 | 4.0948 | 15.4777 | 16.7374   | 28.411  |
| 3.6617        | 5.0   | 315  | 3.8205          | 18.6328 | 4.2703 | 15.6625 | 16.9103   | 30.177  |


### Framework versions

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