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---
library_name: transformers
license: mit
base_model: indobenchmark/indobert-base-p1
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: results
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. -->
# results
This model is a fine-tuned version of [indobenchmark/indobert-base-p1](https://huggingface.co/indobenchmark/indobert-base-p1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0457
- Accuracy: 0.9875
- F1: 0.9868
- Precision: 0.9865
- Recall: 0.9872
## 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: 32
- 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
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.0879 | 1.0 | 739 | 0.0471 | 0.9871 | 0.9865 | 0.9837 | 0.9893 |
| 0.0443 | 2.0 | 1478 | 0.0391 | 0.9895 | 0.9890 | 0.9872 | 0.9908 |
| 0.0241 | 3.0 | 2217 | 0.0615 | 0.9871 | 0.9866 | 0.9803 | 0.9929 |
| 0.0103 | 4.0 | 2956 | 0.0792 | 0.9868 | 0.9861 | 0.9893 | 0.9829 |
| 0.0029 | 5.0 | 3695 | 0.0767 | 0.9885 | 0.9879 | 0.9886 | 0.9872 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1
- Datasets 2.19.2
- Tokenizers 0.20.1
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