ncbi/ncbi_disease
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How to use Umesh/biobert-finetuned-ncbi with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("token-classification", model="Umesh/biobert-finetuned-ncbi") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("Umesh/biobert-finetuned-ncbi")
model = AutoModelForTokenClassification.from_pretrained("Umesh/biobert-finetuned-ncbi", device_map="auto")This model is a fine-tuned version of dmis-lab/biobert-v1.1 on the ncbi_disease 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 |
|---|---|---|---|---|---|---|---|
| 0.1049 | 1.0 | 680 | 0.0588 | 0.7826 | 0.7776 | 0.7801 | 0.9806 |
| 0.0362 | 2.0 | 1360 | 0.0539 | 0.8084 | 0.8577 | 0.8323 | 0.9852 |
| 0.0109 | 3.0 | 2040 | 0.0590 | 0.8193 | 0.8640 | 0.8411 | 0.9856 |