---
language:
- id
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: sentiment-lora-r4a2d0.15-1
  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. -->

# sentiment-lora-r4a2d0.15-1

This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3312
- Accuracy: 0.8622
- Precision: 0.8414
- Recall: 0.8175
- F1: 0.8279

## 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: 5e-05
- train_batch_size: 30
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.566         | 1.0   | 122  | 0.5206          | 0.7143   | 0.6484    | 0.6353 | 0.6403 |
| 0.5117        | 2.0   | 244  | 0.5062          | 0.7343   | 0.6880    | 0.7045 | 0.6939 |
| 0.4804        | 3.0   | 366  | 0.4667          | 0.7669   | 0.7182    | 0.7126 | 0.7152 |
| 0.4345        | 4.0   | 488  | 0.4350          | 0.7920   | 0.7494    | 0.7403 | 0.7445 |
| 0.4081        | 5.0   | 610  | 0.4337          | 0.7945   | 0.7565    | 0.7846 | 0.7661 |
| 0.3793        | 6.0   | 732  | 0.3923          | 0.8195   | 0.7857    | 0.7673 | 0.7753 |
| 0.3665        | 7.0   | 854  | 0.3765          | 0.8296   | 0.7949    | 0.7919 | 0.7934 |
| 0.3471        | 8.0   | 976  | 0.3681          | 0.8371   | 0.8089    | 0.7872 | 0.7966 |
| 0.3498        | 9.0   | 1098 | 0.3677          | 0.8321   | 0.8024    | 0.7812 | 0.7904 |
| 0.3282        | 10.0  | 1220 | 0.3634          | 0.8346   | 0.8074    | 0.7805 | 0.7917 |
| 0.3149        | 11.0  | 1342 | 0.3537          | 0.8446   | 0.8180    | 0.7976 | 0.8065 |
| 0.3092        | 12.0  | 1464 | 0.3529          | 0.8496   | 0.8202    | 0.8136 | 0.8167 |
| 0.3135        | 13.0  | 1586 | 0.3471          | 0.8521   | 0.8332    | 0.7979 | 0.8122 |
| 0.3103        | 14.0  | 1708 | 0.3427          | 0.8622   | 0.8430    | 0.8150 | 0.8269 |
| 0.2974        | 15.0  | 1830 | 0.3372          | 0.8622   | 0.8385    | 0.8225 | 0.8298 |
| 0.2905        | 16.0  | 1952 | 0.3345          | 0.8697   | 0.8488    | 0.8303 | 0.8386 |
| 0.2895        | 17.0  | 2074 | 0.3339          | 0.8622   | 0.8430    | 0.8150 | 0.8269 |
| 0.2922        | 18.0  | 2196 | 0.3319          | 0.8697   | 0.8488    | 0.8303 | 0.8386 |
| 0.2843        | 19.0  | 2318 | 0.3319          | 0.8622   | 0.8430    | 0.8150 | 0.8269 |
| 0.287         | 20.0  | 2440 | 0.3312          | 0.8622   | 0.8414    | 0.8175 | 0.8279 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.15.2