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---
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. |