ncbi/ncbi_disease
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How to use suyingxi0/checkpoints with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("token-classification", model="suyingxi0/checkpoints") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("suyingxi0/checkpoints")
model = AutoModelForTokenClassification.from_pretrained("suyingxi0/checkpoints", 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 |
|---|---|---|---|---|---|---|---|
| 0.0425 | 1.0 | 680 | 0.0668 | 0.6871 | 0.7675 | 0.7251 | 0.9786 |
| 0.0399 | 2.0 | 1360 | 0.0656 | 0.7100 | 0.8056 | 0.7548 | 0.9803 |
| 0.0154 | 3.0 | 2040 | 0.0905 | 0.7190 | 0.8030 | 0.7587 | 0.9803 |
Base model
microsoft/biogpt