---
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: 44.408
---

<!-- 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: 0.2554
- Rouge1: 44.408
- Rouge2: 35.788
- Rougel: 40.8449
- Rougelsum: 43.0054
- Gen Len: 62.247

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 0.9013        | 1.0   | 63   | 0.3600          | 40.5674 | 32.5892 | 37.7471 | 39.1368   | 46.887  |
| 0.4754        | 2.0   | 126  | 0.2958          | 43.3031 | 34.5149 | 39.7514 | 41.863    | 56.767  |
| 0.3811        | 3.0   | 189  | 0.2629          | 43.4511 | 34.6775 | 39.9831 | 42.0606   | 57.898  |
| 0.3317        | 4.0   | 252  | 0.2610          | 43.9259 | 35.2198 | 40.3143 | 42.5364   | 57.815  |
| 0.299         | 5.0   | 315  | 0.2554          | 44.3826 | 35.7034 | 40.7597 | 42.9985   | 58.818  |


### Framework versions

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