grit-id/id_nergrit_corpus
Updated • 224 • 7
How to use bryanahusna/my-nergrit-model with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("token-classification", model="bryanahusna/my-nergrit-model") # Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("bryanahusna/my-nergrit-model")
model = AutoModelForTokenClassification.from_pretrained("bryanahusna/my-nergrit-model")This model is a fine-tuned version of indolem/indobert-base-uncased on the id_nergrit_corpus dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.4887 | 1.0 | 784 | 0.1891 | 0.7908 | 0.8305 | 0.8102 | 0.9427 |
| 0.1624 | 2.0 | 1568 | 0.1792 | 0.8166 | 0.8424 | 0.8293 | 0.9476 |
Base model
indolem/indobert-base-uncased