metadata
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
| Epoch | Training Loss | Validation Loss |
|---|---|---|
| 1 | 0.149900 | 0.139475 |
| 2 | 0.131600 | 0.143117 |
| 3 | 0.036600 | 0.192144 |
Evaluation
| Class | Precision | Recall | F1-Score | Support |
|---|---|---|---|---|
| Positive | 0.98 | 0.94 | 0.96 | 1098 |
| Negative | 0.89 | 0.96 | 0.93 | 601 |
| Accuracy | 0.95 | 1699 | ||
| Macro Avg | 0.93 | 0.95 | 0.94 | 1699 |
| Weighted Avg | 0.95 | 0.95 | 0.95 | 1699 |
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.