---
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: indonesian-brand-indoBERT-finetuned
  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. -->

# indonesian-brand-indoBERT-finetuned

This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6848
- Accuracy: 0.8601
- Precision: 0.8601
- Recall: 0.8601
- F1: 0.8601

## 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: 1e-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
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 304  | 0.4935          | 0.8132   | 0.8132    | 0.8132 | 0.8132 |
| 0.5911        | 2.0   | 608  | 0.4046          | 0.8362   | 0.8362    | 0.8362 | 0.8362 |
| 0.5911        | 3.0   | 912  | 0.4873          | 0.8305   | 0.8305    | 0.8305 | 0.8305 |
| 0.3204        | 4.0   | 1216 | 0.4774          | 0.8560   | 0.8560    | 0.8560 | 0.8560 |
| 0.2154        | 5.0   | 1520 | 0.5759          | 0.8486   | 0.8486    | 0.8486 | 0.8486 |
| 0.2154        | 6.0   | 1824 | 0.6334          | 0.8568   | 0.8568    | 0.8568 | 0.8568 |
| 0.1454        | 7.0   | 2128 | 0.6848          | 0.8601   | 0.8601    | 0.8601 | 0.8601 |
| 0.1454        | 8.0   | 2432 | 0.7325          | 0.8560   | 0.8560    | 0.8560 | 0.8560 |
| 0.0982        | 9.0   | 2736 | 0.7782          | 0.8568   | 0.8568    | 0.8568 | 0.8568 |
| 0.0729        | 10.0  | 3040 | 0.7979          | 0.8584   | 0.8584    | 0.8584 | 0.8584 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2