---
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-pl50
  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: 35.5686
---

<!-- 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-pl50

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: 2.6722
- Rouge1: 35.5686
- Rouge2: 23.5102
- Rougel: 31.8451
- Rougelsum: 33.6584
- Gen Len: 49.748

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 4.2782        | 1.0   | 63   | 3.2600          | 25.0139 | 13.1669 | 22.4852 | 23.5026   | 38.037  |
| 3.3831        | 2.0   | 126  | 3.0118          | 28.0005 | 15.5199 | 25.1006 | 26.3175   | 51.621  |
| 3.0732        | 3.0   | 189  | 2.8226          | 31.6641 | 18.1569 | 27.8004 | 29.8463   | 51.938  |
| 2.83          | 4.0   | 252  | 2.7181          | 34.3328 | 21.5065 | 30.323  | 32.3623   | 51.327  |
| 2.6441        | 5.0   | 315  | 2.6722          | 34.8229 | 22.044  | 30.8324 | 33.0138   | 52.623  |


### Framework versions

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