---
license: mit
base_model: indobenchmark/indobert-base-p2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: koneksi_model
  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. -->

# koneksi_model

This model is a fine-tuned version of [indobenchmark/indobert-base-p2](https://huggingface.co/indobenchmark/indobert-base-p2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0917
- Accuracy: 0.75
- F1: 0.7493
- Precision: 0.7497
- Recall: 0.7491

## 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: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 0.52  | 50   | 0.5014          | 0.7812   | 0.7810 | 0.7865    | 0.7839 |
| No log        | 1.04  | 100  | 0.5135          | 0.7708   | 0.7708 | 0.7732    | 0.7726 |
| No log        | 1.56  | 150  | 0.5564          | 0.7552   | 0.7503 | 0.7924    | 0.7624 |
| No log        | 2.08  | 200  | 0.5628          | 0.7604   | 0.7572 | 0.7659    | 0.7570 |
| No log        | 2.6   | 250  | 0.8524          | 0.7083   | 0.7037 | 0.7132    | 0.7043 |
| No log        | 3.12  | 300  | 0.6830          | 0.7448   | 0.7432 | 0.7456    | 0.7428 |
| No log        | 3.65  | 350  | 0.9662          | 0.7292   | 0.7262 | 0.7321    | 0.7261 |
| No log        | 4.17  | 400  | 0.9936          | 0.7656   | 0.7656 | 0.7659    | 0.7663 |
| No log        | 4.69  | 450  | 1.0558          | 0.7604   | 0.7603 | 0.7604    | 0.7609 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0