grit-id/id_nergrit_corpus
Updated • 191 • 7
How to use koosty/mobilebert-uncased-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("token-classification", model="koosty/mobilebert-uncased-finetuned-ner") # Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("koosty/mobilebert-uncased-finetuned-ner")
model = AutoModelForTokenClassification.from_pretrained("koosty/mobilebert-uncased-finetuned-ner")This model is a fine-tuned version of google/mobilebert-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 |
|---|---|---|---|---|---|---|---|
| 0.6239 | 1.0 | 1567 | 0.4989 | 0.5842 | 0.4877 | 0.5316 | 0.8688 |
| 0.5356 | 2.0 | 3134 | 0.4003 | 0.6368 | 0.5879 | 0.6113 | 0.8905 |
| 0.4035 | 3.0 | 4701 | 0.3800 | 0.6700 | 0.6136 | 0.6406 | 0.8974 |