---
language:
- id
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: sentiment-lora-r8a2d0.15-1
  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-r8a2d0.15-1

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: 0.3168
- Accuracy: 0.8722
- Precision: 0.8528
- Recall: 0.8321
- F1: 0.8413

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5647        | 1.0   | 122  | 0.5166          | 0.7068   | 0.6380    | 0.6250 | 0.6297 |
| 0.5067        | 2.0   | 244  | 0.4954          | 0.7343   | 0.6870    | 0.7020 | 0.6926 |
| 0.4617        | 3.0   | 366  | 0.4391          | 0.7920   | 0.7491    | 0.7503 | 0.7497 |
| 0.4044        | 4.0   | 488  | 0.3911          | 0.8145   | 0.7761    | 0.7788 | 0.7774 |
| 0.382         | 5.0   | 610  | 0.3827          | 0.8195   | 0.7849    | 0.8198 | 0.7962 |
| 0.3494        | 6.0   | 732  | 0.3528          | 0.8421   | 0.8092    | 0.8108 | 0.8100 |
| 0.3423        | 7.0   | 854  | 0.3442          | 0.8546   | 0.8239    | 0.8272 | 0.8255 |
| 0.33          | 8.0   | 976  | 0.3400          | 0.8672   | 0.8479    | 0.8235 | 0.8342 |
| 0.3296        | 9.0   | 1098 | 0.3349          | 0.8496   | 0.8245    | 0.8036 | 0.8128 |
| 0.3074        | 10.0  | 1220 | 0.3349          | 0.8622   | 0.8467    | 0.8100 | 0.8249 |
| 0.2911        | 11.0  | 1342 | 0.3240          | 0.8697   | 0.8503    | 0.8278 | 0.8377 |
| 0.2855        | 12.0  | 1464 | 0.3273          | 0.8722   | 0.8463    | 0.8446 | 0.8454 |
| 0.2903        | 13.0  | 1586 | 0.3285          | 0.8647   | 0.8472    | 0.8167 | 0.8296 |
| 0.2896        | 14.0  | 1708 | 0.3254          | 0.8672   | 0.8479    | 0.8235 | 0.8342 |
| 0.2744        | 15.0  | 1830 | 0.3241          | 0.8647   | 0.8377    | 0.8342 | 0.8359 |
| 0.2691        | 16.0  | 1952 | 0.3210          | 0.8571   | 0.8289    | 0.8239 | 0.8264 |
| 0.2671        | 17.0  | 2074 | 0.3208          | 0.8697   | 0.8503    | 0.8278 | 0.8377 |
| 0.2736        | 18.0  | 2196 | 0.3179          | 0.8722   | 0.8512    | 0.8346 | 0.8422 |
| 0.2662        | 19.0  | 2318 | 0.3180          | 0.8722   | 0.8544    | 0.8296 | 0.8404 |
| 0.2664        | 20.0  | 2440 | 0.3168          | 0.8722   | 0.8528    | 0.8321 | 0.8413 |


### Framework versions

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