---
license: mit
base_model: cahya/bert-base-indonesian-1.5G
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: belajarner_bert_case
  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. -->

# belajarner_bert_case

This model is a fine-tuned version of [cahya/bert-base-indonesian-1.5G](https://huggingface.co/cahya/bert-base-indonesian-1.5G) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3302
- Precision: 0.8314
- Recall: 0.8484
- F1: 0.8398
- Accuracy: 0.9471

## 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: 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: 8

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1904        | 1.0   | 1567  | 0.2090          | 0.7825    | 0.8298 | 0.8054 | 0.9385   |
| 0.1195        | 2.0   | 3134  | 0.2141          | 0.8312    | 0.8237 | 0.8274 | 0.9446   |
| 0.0772        | 3.0   | 4701  | 0.2200          | 0.8220    | 0.8427 | 0.8322 | 0.9457   |
| 0.0463        | 4.0   | 6268  | 0.2636          | 0.8158    | 0.8498 | 0.8324 | 0.9446   |
| 0.0342        | 5.0   | 7835  | 0.2878          | 0.8351    | 0.8392 | 0.8372 | 0.9456   |
| 0.0223        | 6.0   | 9402  | 0.3066          | 0.8267    | 0.8414 | 0.8340 | 0.9454   |
| 0.0139        | 7.0   | 10969 | 0.3250          | 0.8302    | 0.8476 | 0.8388 | 0.9466   |
| 0.0096        | 8.0   | 12536 | 0.3302          | 0.8314    | 0.8484 | 0.8398 | 0.9471   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2