---
language:
- id
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: sentiment-lora-r8a2d0.05-0
  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-r8a2d0.05-0

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: 0.3260
- Accuracy: 0.8622
- Precision: 0.8319
- Recall: 0.8400
- F1: 0.8357

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5609        | 1.0   | 122  | 0.5086          | 0.7193   | 0.6580    | 0.6514 | 0.6543 |
| 0.4986        | 2.0   | 244  | 0.4855          | 0.7494   | 0.7127    | 0.7427 | 0.7201 |
| 0.4593        | 3.0   | 366  | 0.4238          | 0.7694   | 0.7249    | 0.7394 | 0.7309 |
| 0.3957        | 4.0   | 488  | 0.3916          | 0.8070   | 0.7670    | 0.7735 | 0.7700 |
| 0.3658        | 5.0   | 610  | 0.4266          | 0.7995   | 0.7641    | 0.7981 | 0.7744 |
| 0.3345        | 6.0   | 732  | 0.3666          | 0.8371   | 0.8028    | 0.8072 | 0.8049 |
| 0.3237        | 7.0   | 854  | 0.3714          | 0.8396   | 0.8045    | 0.8265 | 0.8136 |
| 0.304         | 8.0   | 976  | 0.3537          | 0.8421   | 0.8083    | 0.8158 | 0.8119 |
| 0.3027        | 9.0   | 1098 | 0.3531          | 0.8446   | 0.8111    | 0.8201 | 0.8153 |
| 0.2962        | 10.0  | 1220 | 0.3382          | 0.8521   | 0.8220    | 0.8204 | 0.8212 |
| 0.2721        | 11.0  | 1342 | 0.3490          | 0.8496   | 0.8162    | 0.8311 | 0.8229 |
| 0.2693        | 12.0  | 1464 | 0.3502          | 0.8546   | 0.8220    | 0.8372 | 0.8288 |
| 0.2745        | 13.0  | 1586 | 0.3284          | 0.8571   | 0.8289    | 0.8239 | 0.8264 |
| 0.2712        | 14.0  | 1708 | 0.3297          | 0.8596   | 0.8299    | 0.8332 | 0.8315 |
| 0.256         | 15.0  | 1830 | 0.3357          | 0.8647   | 0.8346    | 0.8442 | 0.8391 |
| 0.2504        | 16.0  | 1952 | 0.3346          | 0.8571   | 0.8255    | 0.8364 | 0.8306 |
| 0.2487        | 17.0  | 2074 | 0.3242          | 0.8571   | 0.8281    | 0.8264 | 0.8272 |
| 0.2514        | 18.0  | 2196 | 0.3309          | 0.8622   | 0.8314    | 0.8425 | 0.8365 |
| 0.2451        | 19.0  | 2318 | 0.3243          | 0.8622   | 0.8333    | 0.8350 | 0.8341 |
| 0.2461        | 20.0  | 2440 | 0.3260          | 0.8622   | 0.8319    | 0.8400 | 0.8357 |


### Framework versions

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