Update README.md

README.md

@@ -145,7 +145,7 @@ outputs = tokenizer.batch_encode_plus(smiles_list, padding=True, truncation=True
 
 
 ## 📚 Early VAE Evaluation (vs. ChemBERTa's) [WIP for Scaling]
-1st Epoch, on ~13K samples of len(token_ids)<=25; embed_dim=64, hidden_dim=128, latent_dim=64, num_layers=2; batch_size= 16 * 4 (grad acc) 
+Using `benchmark_simpler.py`: 1st Epoch, on ~13K samples of len(token_ids)<=25; embed_dim=64, hidden_dim=128, latent_dim=64, num_layers=2; batch_size= 16 * 4 (grad acc) 
 
 Latent Space Visualization based on SMILES Interpolation Validity