---
language:
- id
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: sentiment-lora-r2a1d0.15-0
  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-r2a1d0.15-0

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: 0.3672
- Accuracy: 0.8321
- Precision: 0.7961
- Recall: 0.8087
- F1: 0.8018

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.563         | 1.0   | 122  | 0.5138          | 0.7243   | 0.6636    | 0.6549 | 0.6586 |
| 0.509         | 2.0   | 244  | 0.5057          | 0.7168   | 0.6763    | 0.6996 | 0.6820 |
| 0.4924        | 3.0   | 366  | 0.4708          | 0.7393   | 0.6877    | 0.6931 | 0.6901 |
| 0.468         | 4.0   | 488  | 0.4379          | 0.7845   | 0.7412    | 0.7200 | 0.7286 |
| 0.4495        | 5.0   | 610  | 0.4466          | 0.7594   | 0.7233    | 0.7548 | 0.7313 |
| 0.4334        | 6.0   | 732  | 0.4041          | 0.8271   | 0.7927    | 0.7851 | 0.7887 |
| 0.415         | 7.0   | 854  | 0.4057          | 0.7995   | 0.7590    | 0.7756 | 0.7660 |
| 0.3974        | 8.0   | 976  | 0.3852          | 0.8321   | 0.7982    | 0.7937 | 0.7959 |
| 0.3849        | 9.0   | 1098 | 0.3829          | 0.8246   | 0.7880    | 0.7909 | 0.7894 |
| 0.3771        | 10.0  | 1220 | 0.3786          | 0.8396   | 0.8065    | 0.8065 | 0.8065 |
| 0.3633        | 11.0  | 1342 | 0.3843          | 0.8296   | 0.7931    | 0.8069 | 0.7993 |
| 0.3591        | 12.0  | 1464 | 0.3833          | 0.8296   | 0.7931    | 0.8069 | 0.7993 |
| 0.354         | 13.0  | 1586 | 0.3705          | 0.8396   | 0.8065    | 0.8065 | 0.8065 |
| 0.3451        | 14.0  | 1708 | 0.3709          | 0.8371   | 0.8028    | 0.8072 | 0.8049 |
| 0.3403        | 15.0  | 1830 | 0.3733          | 0.8321   | 0.7960    | 0.8112 | 0.8027 |
| 0.3282        | 16.0  | 1952 | 0.3715          | 0.8346   | 0.7988    | 0.8155 | 0.8061 |
| 0.3286        | 17.0  | 2074 | 0.3664          | 0.8321   | 0.7965    | 0.8037 | 0.7999 |
| 0.3348        | 18.0  | 2196 | 0.3670          | 0.8271   | 0.7904    | 0.8001 | 0.7949 |
| 0.325         | 19.0  | 2318 | 0.3669          | 0.8321   | 0.7961    | 0.8087 | 0.8018 |
| 0.3266        | 20.0  | 2440 | 0.3672          | 0.8321   | 0.7961    | 0.8087 | 0.8018 |


### Framework versions

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