Update README.md

README.md

@@ -24,6 +24,49 @@ data resources. This endeavor is crucial for maximizing the efficacy of computat
 constrained, ensuring that Bayesian optimization remains a viable and effective tool for advancing research and applications in 
 deep learning for chemistry and beyond.
 
+Results:
+|   N  | Learning Rate          | Loss            |
+|------|------------------|-----------------|
+|  200 | 0.084878         | 0.010064        |
+|  400 | 0.059692         | 0.003261        |
+|  600 | 0.055656         | 0.003610        |
+|  800 | 0.029240         | 0.001820        |
+| 1000 | 0.017758         | 0.001970        |
+| 1200 | 0.027993         | 0.003351        |
+| 1400 | 0.018717         | 0.002034        |
+| 1600 | 0.023550         | 0.002136        |
+| 1800 | 0.014614         | 0.002025        |
+| 2000 | 0.009610         | 0.001134        |
+
+|   N  | Batch Size | Loss       |
+|------|--------|------------|
+|  200 | 120    | 0.0080974  |
+|  400 | 21     | 0.002841   |
+|  600 | 27     | 0.002955   |
+|  800 | 16     | 0.002613   |
+| 1000 | 22     | 0.002506   |
+| 1200 | 22     | 0.002462   |
+| 1400 | 30     | 0.001593   |
+| 1600 | 16     | 0.002007   |
+| 1800 | 18     | 0.002203   |
+| 2000 | 16     | 0.002041   |
+
+|   N  | # of Neurons | Loss       |
+|------|--------|------------|
+|  200 | 111    | 0.0084131  |
+|  400 | 47     | 0.0043065  |
+|  600 | 51     | 0.002910   |
+|  800 | 32     | 0.002574   |
+| 1000 | 22     | 0.002193   |
+| 1200 | 34     | 0.002597   |
+| 1400 | 22     | 0.002111   |
+| 1600 | -    | -        |
+| 1800 | 48     | 0.001758   |
+| 2000 | 59     | 0.001668   |
+
+
+
+
 References:
 
 1. Anatole von Lilienfeld and Kieron Burke. “Retrospective on a decade of machine learning for chemical discovery”. In: Nature Communications 11.1 (Sept. 2020). DOI: 10.1038/s41467- 020- 18556- 9. URL: https: