Text Classification
Transformers
Safetensors
Indonesian
bert
natural-language-inference
indonesian
perturbation-robustness
text-embeddings-inference
Instructions to use fabhiansan/indoBERT-Large-FactChecking-Summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fabhiansan/indoBERT-Large-FactChecking-Summarization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fabhiansan/indoBERT-Large-FactChecking-Summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fabhiansan/indoBERT-Large-FactChecking-Summarization") model = AutoModelForSequenceClassification.from_pretrained("fabhiansan/indoBERT-Large-FactChecking-Summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "total_samples": 13877, | |
| "accuracy": 0.8509043741442675, | |
| "macro_precision": 0.8192254366193239, | |
| "macro_recall": 0.8151287416913957, | |
| "macro_f1": 0.8171262560991883, | |
| "average_loss": 0.8716882247996837, | |
| "classification_report": { | |
| "label_0": { | |
| "precision": 0.8919000301114123, | |
| "recall": 0.8995748127151245, | |
| "f1-score": 0.8957209818053525, | |
| "support": 9878.0 | |
| }, | |
| "label_1": { | |
| "precision": 0.7465508431272355, | |
| "recall": 0.7306826706676669, | |
| "f1-score": 0.7385315303930241, | |
| "support": 3999.0 | |
| }, | |
| "accuracy": 0.8509043741442675, | |
| "macro avg": { | |
| "precision": 0.8192254366193239, | |
| "recall": 0.8151287416913957, | |
| "f1-score": 0.8171262560991883, | |
| "support": 13877.0 | |
| }, | |
| "weighted avg": { | |
| "precision": 0.8500140750238774, | |
| "recall": 0.8509043741442675, | |
| "f1-score": 0.8504229623344365, | |
| "support": 13877.0 | |
| } | |
| }, | |
| "confusion_matrix": [ | |
| [ | |
| 8886, | |
| 992 | |
| ], | |
| [ | |
| 1077, | |
| 2922 | |
| ] | |
| ], | |
| "evaluation_duration_seconds": 1649.3387715816498 | |
| } |