Indonesian QEA for Public Figure in News Article with BERT
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How to use damand2061/pfsa-id-NusaBERT with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("token-classification", model="damand2061/pfsa-id-NusaBERT") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("damand2061/pfsa-id-NusaBERT")
model = AutoModelForTokenClassification.from_pretrained("damand2061/pfsa-id-NusaBERT", device_map="auto")This model is a fine-tuned version of LazarusNLP/NusaBERT-base on an unknown dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Train Loss | Validation Loss | Validation F1 | Validation Accuracy | Epoch |
|---|---|---|---|---|
| 0.4655 | 0.2722 | 0.6325 | 0.9143 | 0 |
| 0.2608 | 0.2483 | 0.7049 | 0.9203 | 1 |
| 0.2179 | 0.2391 | 0.7479 | 0.9242 | 2 |
| 0.1888 | 0.2393 | 0.7669 | 0.9245 | 3 |
| 0.1672 | 0.2417 | 0.7748 | 0.9257 | 4 |
Base model
LazarusNLP/NusaBERT-base