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---
license: mit
base_model: indobenchmark/indobert-large-p2
tags:
- generated_from_trainer
model-index:
- name: pertama
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. -->
# pertama
This model is a fine-tuned version of [indobenchmark/indobert-large-p2](https://huggingface.co./indobenchmark/indobert-large-p2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4507
- F1 macro: 0.4131
- Weighted: 0.5840
- Balanced accuracy: 0.5423
## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 14
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 macro | Weighted | Balanced accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|
| 1.3416 | 1.0 | 154 | 1.5603 | 0.2942 | 0.3462 | 0.4357 |
| 0.941 | 2.0 | 308 | 1.3408 | 0.3530 | 0.5202 | 0.4807 |
| 0.6965 | 3.0 | 462 | 1.3731 | 0.3747 | 0.5629 | 0.5101 |
| 0.4375 | 4.0 | 616 | 1.3137 | 0.3904 | 0.5961 | 0.5002 |
| 0.2491 | 5.0 | 770 | 1.5577 | 0.3772 | 0.5930 | 0.4978 |
| 0.0793 | 6.0 | 924 | 2.1326 | 0.3923 | 0.5382 | 0.5401 |
| 0.0488 | 7.0 | 1078 | 2.2000 | 0.3861 | 0.5483 | 0.5243 |
| 0.0206 | 8.0 | 1232 | 2.1568 | 0.3914 | 0.5873 | 0.5096 |
| 0.0243 | 9.0 | 1386 | 2.2272 | 0.4118 | 0.5851 | 0.5457 |
| 0.0126 | 10.0 | 1540 | 2.3494 | 0.4029 | 0.5885 | 0.5346 |
| 0.0449 | 11.0 | 1694 | 2.2914 | 0.4115 | 0.6037 | 0.5387 |
| 0.0023 | 12.0 | 1848 | 2.5714 | 0.3962 | 0.5675 | 0.5334 |
| 0.0023 | 13.0 | 2002 | 2.4491 | 0.4155 | 0.5878 | 0.5400 |
| 0.0024 | 14.0 | 2156 | 2.4507 | 0.4131 | 0.5840 | 0.5423 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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