# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("onionLad/identifier-deberta")
model = AutoModelForTokenClassification.from_pretrained("onionLad/identifier-deberta")Quick Links
identifier-deberta
This model is a fine-tuned version of microsoft/deberta-v3-base on data derived from the PLABA dataset. Training was performed over 3 epochs with learning rate 2e-5. The model achieves the following performance:
- Validation Loss: 0.112134
- Precision: 0.455793
- Recall: 0.379442
- F1: 0.414127
- Accuracy: 0.961042
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="onionLad/identifier-deberta")