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---
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
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