ncbi/ncbi_disease
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How to use Randomui/finetuned with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("token-classification", model="Randomui/finetuned") # Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("Randomui/finetuned")
model = AutoModelForTokenClassification.from_pretrained("Randomui/finetuned", device_map="auto")This model is a fine-tuned version of microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext 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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 170 | 0.0582 | 0.7621 | 0.8506 | 0.8040 | 0.9816 |
| No log | 2.0 | 340 | 0.0588 | 0.8074 | 0.8535 | 0.8298 | 0.9828 |
| 0.0712 | 3.0 | 510 | 0.0568 | 0.8246 | 0.8725 | 0.8479 | 0.9839 |