---
language:
- id
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
- generated_from_trainer
datasets:
- id_liputan6
metrics:
- rouge
model-index:
- name: liputan6-seq_bn-rf16
  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: 27.6391
---

<!-- 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-seq_bn-rf16

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: 2.7479
- Rouge1: 27.6391
- Rouge2: 12.5407
- Rougel: 23.5774
- Rougelsum: 25.3376
- Gen Len: 39.933

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.6241        | 1.0   | 63   | 2.7534          | 23.3287 | 9.5988  | 20.1923 | 21.2916   | 33.387  |
| 2.228         | 2.0   | 126  | 2.7025          | 25.8033 | 10.8168 | 21.9451 | 23.4491   | 32.153  |
| 2.0615        | 3.0   | 189  | 2.6749          | 25.8887 | 10.7586 | 22.113  | 23.8997   | 30.873  |
| 1.9099        | 4.0   | 252  | 2.7197          | 26.5565 | 11.2255 | 22.6026 | 24.5495   | 31.524  |
| 1.8007        | 5.0   | 315  | 2.7479          | 26.9743 | 11.4843 | 22.9863 | 24.9284   | 33.854  |


### Framework versions

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