|
--- |
|
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. |
