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---
license: mit
base_model: indobenchmark/indobert-large-p2
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: wrete-indonlu
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. -->
# wrete-indonlu
This model is a fine-tuned version of [indobenchmark/indobert-large-p2](https://huggingface.co/indobenchmark/indobert-large-p2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0433
- Accuracy: 0.98
- Precision: 0.98
- Recall: 0.98
- F1 Score: 0.9799
## 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-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| 0.1774 | 1.0 | 88 | 0.5232 | 0.92 | 0.92 | 0.92 | 0.9177 |
| 0.0992 | 2.0 | 176 | 0.2976 | 0.94 | 0.94 | 0.94 | 0.9388 |
| 0.0645 | 3.0 | 264 | 0.1118 | 0.98 | 0.98 | 0.98 | 0.9799 |
| 0.029 | 4.0 | 352 | 0.1066 | 0.98 | 0.98 | 0.98 | 0.9799 |
| 0.0333 | 5.0 | 440 | 0.0665 | 0.98 | 0.98 | 0.98 | 0.9799 |
| 0.0153 | 6.0 | 528 | 0.0504 | 0.98 | 0.98 | 0.98 | 0.9799 |
| 0.0092 | 7.0 | 616 | 0.0433 | 0.98 | 0.98 | 0.98 | 0.9799 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2
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