---
license: mit
base_model: indobenchmark/indobart-v2
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: indobart-indonlg-nusax-500-jv-id
  results: []
---

<!-- 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. -->

# indobart-indonlg-nusax-500-jv-id

This model is a fine-tuned version of [indobenchmark/indobart-v2](https://huggingface.co/indobenchmark/indobart-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6148
- Bleu: 20.3132
- Gen Len: 19.3294

## 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: 2e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| No log        | 1.0   | 114  | 0.8182          | 12.2063 | 19.4575 |
| No log        | 2.0   | 228  | 0.7390          | 14.2482 | 19.3932 |
| No log        | 3.0   | 342  | 0.6975          | 15.9974 | 19.4014 |
| No log        | 4.0   | 456  | 0.6706          | 16.578  | 19.3601 |
| 0.849         | 5.0   | 570  | 0.6527          | 17.2313 | 19.3713 |
| 0.849         | 6.0   | 684  | 0.6392          | 17.9    | 19.3477 |
| 0.849         | 7.0   | 798  | 0.6285          | 18.0166 | 19.3495 |
| 0.849         | 8.0   | 912  | 0.6242          | 18.2424 | 19.3347 |
| 0.4461        | 9.0   | 1026 | 0.6170          | 18.6378 | 19.3648 |
| 0.4461        | 10.0  | 1140 | 0.6148          | 19.0513 | 19.3365 |
| 0.4461        | 11.0  | 1254 | 0.6106          | 19.5335 | 19.3383 |
| 0.4461        | 12.0  | 1368 | 0.6097          | 19.2886 | 19.3353 |
| 0.4461        | 13.0  | 1482 | 0.6079          | 19.5712 | 19.3347 |
| 0.3344        | 14.0  | 1596 | 0.6067          | 19.4256 | 19.3684 |
| 0.3344        | 15.0  | 1710 | 0.6078          | 19.7062 | 19.3483 |
| 0.3344        | 16.0  | 1824 | 0.6052          | 19.6353 | 19.3506 |
| 0.3344        | 17.0  | 1938 | 0.6072          | 19.8745 | 19.3318 |
| 0.2674        | 18.0  | 2052 | 0.6076          | 20.0834 | 19.3318 |
| 0.2674        | 19.0  | 2166 | 0.6078          | 20.082  | 19.3506 |
| 0.2674        | 20.0  | 2280 | 0.6098          | 20.1934 | 19.3117 |
| 0.2674        | 21.0  | 2394 | 0.6094          | 20.1326 | 19.3453 |
| 0.225         | 22.0  | 2508 | 0.6109          | 20.2045 | 19.3329 |
| 0.225         | 23.0  | 2622 | 0.6133          | 20.0595 | 19.3495 |
| 0.225         | 24.0  | 2736 | 0.6117          | 20.2089 | 19.3442 |
| 0.225         | 25.0  | 2850 | 0.6141          | 20.2566 | 19.3264 |
| 0.225         | 26.0  | 2964 | 0.6143          | 20.3092 | 19.3329 |
| 0.199         | 27.0  | 3078 | 0.6134          | 20.3808 | 19.33   |
| 0.199         | 28.0  | 3192 | 0.6141          | 20.412  | 19.34   |
| 0.199         | 29.0  | 3306 | 0.6148          | 20.2613 | 19.3359 |
| 0.199         | 30.0  | 3420 | 0.6148          | 20.3132 | 19.3294 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.13.3