generated_from_trainer id dataset:id_liputan6 base_model:LazarusNLP/IndoNanoT5-base base_model:finetune:LazarusNLP/IndoNanoT5-base license:apache-2.0 model-index region:us
---
base_model: LazarusNLP/IndoNanoT5-base
datasets:
- id_liputan6
language:
- id
license: apache-2.0
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: liputan6-seq_bn-rf64
  results:
  - task:
      type: summarization
      name: Summarization
    dataset:
      name: id_liputan6 canonical
      type: id_liputan6
      config: canonical
      split: validation
      args: canonical
    metrics:
    - type: rouge
      value: 43.4905
      name: Rouge1
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# liputan6-seq_bn-rf64

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: 0.2748
- Rouge1: 43.4905
- Rouge2: 34.6942
- Rougel: 39.8342
- Rougelsum: 42.0699
- Gen Len: 62.292

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.1116        | 1.0   | 63   | 0.3953          | 39.3374 | 31.1269 | 36.447  | 37.9075   | 49.406  |
| 0.5774        | 2.0   | 126  | 0.3309          | 43.6615 | 34.9524 | 40.0101 | 42.2478   | 55.7    |
| 0.4729        | 3.0   | 189  | 0.2864          | 41.4092 | 32.5453 | 37.9684 | 39.9099   | 52.999  |
| 0.4209        | 4.0   | 252  | 0.2845          | 43.3834 | 34.6436 | 39.8104 | 41.9569   | 56.612  |
| 0.3931        | 5.0   | 315  | 0.2748          | 43.7351 | 34.936  | 40.0408 | 42.3437   | 58.611  |


### Framework versions

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