Update README.md

README.md

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 [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/npcomposer/npcomposer/runs/lpvwn86m)
 # NPComposer
 
-NPComposer is a conditional molecular generation model trained by fine-tuning GP-MoLFormer — a 46.8M parameter transformer decoder foundation model — on the COCONUT database containing over 700,000 experimentally validated natural products.
+NPComposer is a conditional molecular generation model trained by fine-tuning GP-MoLFormer [ibm-research/GP-MoLFormer-Uniq](https://huggingface.co/ibm-research/GP-MoLFormer-Uniq) — a 46.8M parameter transformer decoder foundation model — on the COCONUT database containing over 700,000 experimentally validated natural products.
 https://github.com/shawnralyn/NPComposer
 
 By providing class labels and molecular property information as special tokens during model fine-tuning, NPComposer allows for conditional natural product generation based on: NP biosynthesis pathway (7 pathways including Alkaloids, Terpenoids, Shikimates and Phenylpropanoids, etc.), NP superclass (70+ superclasses), presence or absence of glycoside, number of aromatic rings (0–22), QED drug-likeness (0–1), and synthetic accessibility score (1–10).
 
-This model is a fine-tuned version of [ibm-research/GP-MoLFormer-Uniq](https://huggingface.co/ibm-research/GP-MoLFormer-Uniq) on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.2718
-
 ## Model description
 
 [More information needed](https://github.com/shawnralyn/NPComposer)