---
language:
- id
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: sentiment-lora-r2a0d0.1-0
  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-r2a0d0.1-0

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: 0.3608
- Accuracy: 0.8471
- Precision: 0.8138
- Recall: 0.8243
- F1: 0.8187

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5634        | 1.0   | 122  | 0.5108          | 0.7193   | 0.6572    | 0.6489 | 0.6524 |
| 0.5081        | 2.0   | 244  | 0.5049          | 0.7218   | 0.6829    | 0.7082 | 0.6888 |
| 0.4924        | 3.0   | 366  | 0.4667          | 0.7494   | 0.6977    | 0.6977 | 0.6977 |
| 0.4698        | 4.0   | 488  | 0.4392          | 0.7794   | 0.7349    | 0.7114 | 0.7207 |
| 0.4519        | 5.0   | 610  | 0.4548          | 0.7469   | 0.7169    | 0.7534 | 0.7226 |
| 0.4356        | 6.0   | 732  | 0.4111          | 0.8145   | 0.7770    | 0.7713 | 0.7740 |
| 0.421         | 7.0   | 854  | 0.4101          | 0.7945   | 0.7538    | 0.7721 | 0.7612 |
| 0.4039        | 8.0   | 976  | 0.3829          | 0.8296   | 0.7949    | 0.7919 | 0.7934 |
| 0.3887        | 9.0   | 1098 | 0.3800          | 0.8321   | 0.7972    | 0.7987 | 0.7979 |
| 0.3797        | 10.0  | 1220 | 0.3768          | 0.8371   | 0.8044    | 0.7997 | 0.8020 |
| 0.368         | 11.0  | 1342 | 0.3842          | 0.8221   | 0.7846    | 0.8016 | 0.7918 |
| 0.3598        | 12.0  | 1464 | 0.3778          | 0.8271   | 0.7902    | 0.8051 | 0.7968 |
| 0.3548        | 13.0  | 1586 | 0.3624          | 0.8471   | 0.8167    | 0.8118 | 0.8142 |
| 0.3469        | 14.0  | 1708 | 0.3637          | 0.8446   | 0.8120    | 0.8151 | 0.8135 |
| 0.3431        | 15.0  | 1830 | 0.3685          | 0.8396   | 0.8049    | 0.8165 | 0.8102 |
| 0.3275        | 16.0  | 1952 | 0.3664          | 0.8371   | 0.8017    | 0.8172 | 0.8086 |
| 0.3288        | 17.0  | 2074 | 0.3590          | 0.8396   | 0.8055    | 0.8115 | 0.8084 |
| 0.3335        | 18.0  | 2196 | 0.3607          | 0.8471   | 0.8138    | 0.8243 | 0.8187 |
| 0.3239        | 19.0  | 2318 | 0.3613          | 0.8446   | 0.8107    | 0.8226 | 0.8161 |
| 0.327         | 20.0  | 2440 | 0.3608          | 0.8471   | 0.8138    | 0.8243 | 0.8187 |


### Framework versions

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