---
language:
- id
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: sentiment-base-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-base-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: 0.3540
- Accuracy: 0.8546
- Precision: 0.8233
- Recall: 0.8297
- F1: 0.8264

## 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: 1
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5623        | 1.0   | 122  | 0.5053          | 0.7168   | 0.6410    | 0.5796 | 0.5795 |
| 0.518         | 2.0   | 244  | 0.4861          | 0.7293   | 0.6674    | 0.5960 | 0.5998 |
| 0.4835        | 3.0   | 366  | 0.4552          | 0.7694   | 0.7211    | 0.7094 | 0.7145 |
| 0.4497        | 4.0   | 488  | 0.4223          | 0.7945   | 0.7521    | 0.7521 | 0.7521 |
| 0.4266        | 5.0   | 610  | 0.3996          | 0.8170   | 0.7814    | 0.7680 | 0.7741 |
| 0.3907        | 6.0   | 732  | 0.3830          | 0.8195   | 0.7818    | 0.7873 | 0.7845 |
| 0.3742        | 7.0   | 854  | 0.3684          | 0.8346   | 0.8016    | 0.7955 | 0.7984 |
| 0.3616        | 8.0   | 976  | 0.3720          | 0.8271   | 0.7902    | 0.8051 | 0.7968 |
| 0.3294        | 9.0   | 1098 | 0.3689          | 0.8371   | 0.8019    | 0.8147 | 0.8077 |
| 0.3207        | 10.0  | 1220 | 0.3632          | 0.8396   | 0.8047    | 0.8190 | 0.8111 |
| 0.3214        | 11.0  | 1342 | 0.3577          | 0.8371   | 0.8017    | 0.8172 | 0.8086 |
| 0.3167        | 12.0  | 1464 | 0.3607          | 0.8396   | 0.8046    | 0.8215 | 0.8119 |
| 0.289         | 13.0  | 1586 | 0.3684          | 0.8346   | 0.7988    | 0.8155 | 0.8061 |
| 0.2997        | 14.0  | 1708 | 0.3480          | 0.8496   | 0.8193    | 0.8161 | 0.8177 |
| 0.2986        | 15.0  | 1830 | 0.3576          | 0.8496   | 0.8169    | 0.8261 | 0.8212 |
| 0.2914        | 16.0  | 1952 | 0.3497          | 0.8496   | 0.8180    | 0.8211 | 0.8195 |
| 0.278         | 17.0  | 2074 | 0.3540          | 0.8521   | 0.8207    | 0.8254 | 0.8229 |
| 0.2887        | 18.0  | 2196 | 0.3516          | 0.8521   | 0.8207    | 0.8254 | 0.8229 |
| 0.2829        | 19.0  | 2318 | 0.3537          | 0.8521   | 0.8207    | 0.8254 | 0.8229 |
| 0.2771        | 20.0  | 2440 | 0.3540          | 0.8546   | 0.8233    | 0.8297 | 0.8264 |


### Framework versions

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