---
license: cc-by-sa-4.0
datasets:
- kornwtp/indonlu-smsa
language:
- id
metrics:
- accuracy
- f1
- precision
- recall
base_model:
- indolem/indobertweet-base-uncased
pipeline_tag: text-classification
library_name: transformers
---


## IndoBERTweet finetuned with IndoNLU smsa_doc-sentiment-prosa (Positive and Negative Sentiment Only)
## Training Details

<table border="1">
  <thead>
    <tr>
      <th>Epoch</th>
      <th>Training Loss</th>
      <th>Validation Loss</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td>1</td>
      <td>0.149900</td>
      <td>0.139475</td>
    </tr>
    <tr>
      <td>2</td>
      <td>0.131600</td>
      <td>0.143117</td>
    </tr>
    <tr>
      <td>3</td>
      <td>0.036600</td>
      <td>0.192144</td>
    </tr>
  </tbody>
</table>



## Evaluation

<!-- This section describes the evaluation protocols and provides the results. -->

<table border="1">
  <thead>
    <tr>
      <th>Class</th>
      <th>Precision</th>
      <th>Recall</th>
      <th>F1-Score</th>
      <th>Support</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td>Positive</td>
      <td>0.98</td>
      <td>0.94</td>
      <td>0.96</td>
      <td>1098</td>
    </tr>
    <tr>
      <td>Negative</td>
      <td>0.89</td>
      <td>0.96</td>
      <td>0.93</td>
      <td>601</td>
    </tr>
    <tr>
      <td colspan="5"></td>
    </tr>
    <tr>
      <td>Accuracy</td>
      <td colspan="3">0.95</td>
      <td>1699</td>
    </tr>
    <tr>
      <td>Macro Avg</td>
      <td>0.93</td>
      <td>0.95</td>
      <td>0.94</td>
      <td>1699</td>
    </tr>
    <tr>
      <td>Weighted Avg</td>
      <td>0.95</td>
      <td>0.95</td>
      <td>0.95</td>
      <td>1699</td>
    </tr>
  </tbody>
</table>


## Citation
If you use this model, please cite:

A. Pratama and M. Rosyda, “ANALISIS SENTIMEN DALAM APLIKASI X TERHADAP PENGUNGSI ROHINGYA DENGAN LSTM”, SKANIKA, vol. 8, no. 1, pp. 95-105, Jan. 2025.