ncbi/ncbi_disease
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How to use adigo/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("token-classification", model="adigo/bert-finetuned-ner") # Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("adigo/bert-finetuned-ner")
model = AutoModelForTokenClassification.from_pretrained("adigo/bert-finetuned-ner")This model is a fine-tuned version of emilyalsentzer/Bio_ClinicalBERT 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 |
|---|---|---|---|---|---|---|---|
| 0.1204 | 1.0 | 680 | 0.0536 | 0.7417 | 0.8247 | 0.7810 | 0.9824 |
| 0.0386 | 2.0 | 1360 | 0.0542 | 0.7808 | 0.8463 | 0.8122 | 0.9831 |
| 0.0144 | 3.0 | 2040 | 0.0623 | 0.7953 | 0.8590 | 0.8259 | 0.9841 |
Base model
emilyalsentzer/Bio_ClinicalBERT