---
language:
- id
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
- generated_from_trainer
datasets:
- id_liputan6
metrics:
- rouge
model-index:
- name: liputan6-lora-8
  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: 44.041
---

<!-- 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-lora-8

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: 0.2482
- Rouge1: 44.041
- Rouge2: 35.4021
- Rougel: 40.435
- Rougelsum: 42.6248
- Gen Len: 60.602

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.4611        | 1.0   | 63   | 0.4168          | 20.2294 | 15.1672 | 18.3462 | 19.5551   | 26.342  |
| 0.6123        | 2.0   | 126  | 0.3030          | 42.4943 | 33.9837 | 39.042  | 40.9843   | 54.709  |
| 0.4836        | 3.0   | 189  | 0.2516          | 39.2983 | 30.3972 | 36.1696 | 37.7681   | 48.258  |
| 0.4256        | 4.0   | 252  | 0.2482          | 42.8202 | 33.9496 | 39.2137 | 41.343    | 54.56   |
| 0.4014        | 5.0   | 315  | 0.2389          | 42.5107 | 33.6017 | 39.0118 | 41.0601   | 55.005  |


### Framework versions

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