---
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: 19.8017
---

<!-- 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: 3.7533
- Rouge1: 19.8017
- Rouge2: 5.8239
- Rougel: 17.0737
- Rougelsum: 18.0279
- Gen Len: 30.789

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 4.7245        | 1.0   | 63   | 3.9912          | 16.8276 | 3.6927 | 14.367  | 15.3151   | 30.652  |
| 3.9104        | 2.0   | 126  | 3.8609          | 17.712  | 4.2061 | 14.9465 | 15.9818   | 35.104  |
| 3.6651        | 3.0   | 189  | 3.8036          | 18.8508 | 4.6943 | 15.8363 | 17.0134   | 30.749  |
| 3.4442        | 4.0   | 252  | 3.7533          | 19.7665 | 5.1425 | 16.7615 | 18.1456   | 28.31   |
| 3.2664        | 5.0   | 315  | 3.7381          | 19.5385 | 5.1106 | 16.7601 | 17.9271   | 29.142  |


### Framework versions

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