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

# general_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: 0.2986
- Accuracy: 0.9119
- F1: 0.8872
- Precision: 0.8921
- Recall: 0.8827

## 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        | 0.06  | 50   | 0.3626          | 0.8748   | 0.8410 | 0.8423    | 0.8398 |
| No log        | 0.13  | 100  | 0.3231          | 0.8962   | 0.8699 | 0.8666    | 0.8734 |
| No log        | 0.19  | 150  | 0.4256          | 0.8974   | 0.8626 | 0.8892    | 0.8437 |
| No log        | 0.25  | 200  | 0.3339          | 0.9031   | 0.8744 | 0.8845    | 0.8658 |
| No log        | 0.31  | 250  | 0.3043          | 0.8823   | 0.8587 | 0.8446    | 0.8792 |
| No log        | 0.38  | 300  | 0.3125          | 0.9056   | 0.8808 | 0.8802    | 0.8813 |
| No log        | 0.44  | 350  | 0.2946          | 0.9075   | 0.8838 | 0.8813    | 0.8863 |
| No log        | 0.5   | 400  | 0.2924          | 0.9125   | 0.8898 | 0.8884    | 0.8912 |
| No log        | 0.57  | 450  | 0.2991          | 0.8855   | 0.8632 | 0.8480    | 0.8865 |
| 0.3562        | 0.63  | 500  | 0.2986          | 0.9119   | 0.8872 | 0.8921    | 0.8827 |
| 0.3562        | 0.69  | 550  | 0.2851          | 0.8779   | 0.8564 | 0.8395    | 0.8864 |
| 0.3562        | 0.75  | 600  | 0.3272          | 0.9125   | 0.8868 | 0.8968    | 0.8781 |
| 0.3562        | 0.82  | 650  | 0.3438          | 0.8987   | 0.8636 | 0.8933    | 0.8431 |


### Framework versions

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