---
language:
- id
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: sentiment-lora-r8a0d0.05-1
  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-r8a0d0.05-1

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: 0.3148
- Accuracy: 0.8697
- Precision: 0.8474
- Recall: 0.8328
- F1: 0.8395

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5657        | 1.0   | 122  | 0.5161          | 0.7243   | 0.6616    | 0.6474 | 0.6529 |
| 0.5088        | 2.0   | 244  | 0.4913          | 0.7393   | 0.6917    | 0.7056 | 0.6971 |
| 0.4682        | 3.0   | 366  | 0.4424          | 0.7845   | 0.7401    | 0.7425 | 0.7413 |
| 0.4114        | 4.0   | 488  | 0.3980          | 0.8095   | 0.7702    | 0.7702 | 0.7702 |
| 0.3862        | 5.0   | 610  | 0.3890          | 0.8145   | 0.7783    | 0.8088 | 0.7889 |
| 0.3512        | 6.0   | 732  | 0.3583          | 0.8496   | 0.8245    | 0.8036 | 0.8128 |
| 0.3428        | 7.0   | 854  | 0.3496          | 0.8521   | 0.8207    | 0.8254 | 0.8229 |
| 0.3254        | 8.0   | 976  | 0.3425          | 0.8496   | 0.8245    | 0.8036 | 0.8128 |
| 0.3226        | 9.0   | 1098 | 0.3388          | 0.8571   | 0.8310    | 0.8189 | 0.8245 |
| 0.3063        | 10.0  | 1220 | 0.3376          | 0.8647   | 0.8439    | 0.8217 | 0.8315 |
| 0.2939        | 11.0  | 1342 | 0.3319          | 0.8672   | 0.8463    | 0.8260 | 0.8351 |
| 0.2838        | 12.0  | 1464 | 0.3323          | 0.8546   | 0.8263    | 0.8196 | 0.8229 |
| 0.2916        | 13.0  | 1586 | 0.3283          | 0.8647   | 0.8472    | 0.8167 | 0.8296 |
| 0.2826        | 14.0  | 1708 | 0.3244          | 0.8672   | 0.8463    | 0.8260 | 0.8351 |
| 0.2739        | 15.0  | 1830 | 0.3231          | 0.8697   | 0.8449    | 0.8378 | 0.8412 |
| 0.2674        | 16.0  | 1952 | 0.3221          | 0.8697   | 0.8449    | 0.8378 | 0.8412 |
| 0.2648        | 17.0  | 2074 | 0.3193          | 0.8722   | 0.8528    | 0.8321 | 0.8413 |
| 0.2687        | 18.0  | 2196 | 0.3172          | 0.8697   | 0.8460    | 0.8353 | 0.8404 |
| 0.264         | 19.0  | 2318 | 0.3170          | 0.8747   | 0.8552    | 0.8363 | 0.8448 |
| 0.2637        | 20.0  | 2440 | 0.3148          | 0.8697   | 0.8474    | 0.8328 | 0.8395 |


### Framework versions

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