ncbi/ncbi_disease
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How to use d2d22/biogpt-ner-checkpoint with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("token-classification", model="d2d22/biogpt-ner-checkpoint") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("d2d22/biogpt-ner-checkpoint")
model = AutoModelForTokenClassification.from_pretrained("d2d22/biogpt-ner-checkpoint", device_map="auto")This model is a fine-tuned version of microsoft/biogpt 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 |
|---|---|---|---|---|---|---|---|
| 0.2864 | 1.0 | 680 | 0.1610 | 0.3376 | 0.3977 | 0.3652 | 0.9478 |
| 0.1663 | 2.0 | 1360 | 0.1442 | 0.3721 | 0.4752 | 0.4174 | 0.9541 |
| 0.1054 | 3.0 | 2040 | 0.1431 | 0.4286 | 0.5337 | 0.4754 | 0.9577 |
Base model
microsoft/biogpt