---
language:
- id
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: sentiment-lora-r4a2d0.1-0
  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-r4a2d0.1-0

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: 0.3483
- Accuracy: 0.8446
- Precision: 0.8111
- Recall: 0.8201
- F1: 0.8153

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5617        | 1.0   | 122  | 0.5117          | 0.7193   | 0.6580    | 0.6514 | 0.6543 |
| 0.5046        | 2.0   | 244  | 0.4917          | 0.7419   | 0.7042    | 0.7324 | 0.7112 |
| 0.4798        | 3.0   | 366  | 0.4466          | 0.7594   | 0.7129    | 0.7248 | 0.7179 |
| 0.4374        | 4.0   | 488  | 0.3994          | 0.8195   | 0.7866    | 0.7648 | 0.7741 |
| 0.4037        | 5.0   | 610  | 0.4150          | 0.7845   | 0.7480    | 0.7800 | 0.7575 |
| 0.3741        | 6.0   | 732  | 0.3737          | 0.8371   | 0.8028    | 0.8072 | 0.8049 |
| 0.3574        | 7.0   | 854  | 0.3776          | 0.8221   | 0.7845    | 0.7991 | 0.7909 |
| 0.3387        | 8.0   | 976  | 0.3654          | 0.8446   | 0.8120    | 0.8151 | 0.8135 |
| 0.3293        | 9.0   | 1098 | 0.3627          | 0.8371   | 0.8021    | 0.8122 | 0.8068 |
| 0.3209        | 10.0  | 1220 | 0.3553          | 0.8371   | 0.8032    | 0.8047 | 0.8040 |
| 0.2967        | 11.0  | 1342 | 0.3674          | 0.8346   | 0.7989    | 0.8130 | 0.8052 |
| 0.2928        | 12.0  | 1464 | 0.3707          | 0.8321   | 0.7960    | 0.8112 | 0.8027 |
| 0.2967        | 13.0  | 1586 | 0.3514          | 0.8471   | 0.8153    | 0.8168 | 0.8160 |
| 0.2934        | 14.0  | 1708 | 0.3507          | 0.8421   | 0.8083    | 0.8158 | 0.8119 |
| 0.2811        | 15.0  | 1830 | 0.3553          | 0.8346   | 0.7991    | 0.8105 | 0.8043 |
| 0.2738        | 16.0  | 1952 | 0.3555          | 0.8421   | 0.8077    | 0.8208 | 0.8136 |
| 0.2717        | 17.0  | 2074 | 0.3468          | 0.8496   | 0.8174    | 0.8236 | 0.8204 |
| 0.278         | 18.0  | 2196 | 0.3510          | 0.8421   | 0.8080    | 0.8183 | 0.8127 |
| 0.2701        | 19.0  | 2318 | 0.3471          | 0.8471   | 0.8142    | 0.8218 | 0.8178 |
| 0.2722        | 20.0  | 2440 | 0.3483          | 0.8446   | 0.8111    | 0.8201 | 0.8153 |


### Framework versions

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