---
language:
- id
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
- generated_from_trainer
datasets:
- id_liputan6
metrics:
- rouge
model-index:
- name: liputan6-base
  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: 18.1827
---

<!-- 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-base

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: 5.4266
- Rouge1: 18.1827
- Rouge2: 5.5014
- Rougel: 15.5147
- Rougelsum: 16.9245
- Gen Len: 35.116

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 3.8271        | 1.0   | 63   | 3.9787          | 14.5233 | 4.127  | 12.7611 | 13.5205   | 47.473  |
| 2.2739        | 2.0   | 126  | 4.1316          | 15.9563 | 4.7752 | 13.8242 | 14.8005   | 44.229  |
| 1.2999        | 3.0   | 189  | 4.4850          | 17.2932 | 4.6352 | 14.8582 | 16.1555   | 33.112  |
| 0.6423        | 4.0   | 252  | 4.9200          | 17.5707 | 4.9772 | 14.949  | 16.1838   | 36.399  |
| 0.2536        | 5.0   | 315  | 5.4266          | 17.698  | 4.7021 | 14.8138 | 16.3595   | 31.108  |


### Framework versions

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