Update README.md
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README.md
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@@ -268,43 +268,46 @@ Largest cluster size: 15
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### On contextual generated examples:
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using `model_context_eval.ipynb`:
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**Generated 50 examples from input as context:**
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```
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Total generated: 200
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Overall validity rate: 100.00%
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Input: O=C(C[C@@H]1N([C@@H](CCC1)C[C@@H](C2=CC=CC=C2)O)C)C3=CC=CC=C3
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Validity: 100.00%
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Avg Similarity: 0.
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Lipinski Pass Rate: 38.00%
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Input: O=C2N(C)[C@H](c1cnccc1)CC2
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Validity: 100.00%
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Avg Similarity: 0.
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Lipinski Pass Rate:
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Input: O=C1/C=C\C=C2/N1C[C@@H]3CNC[C@H]2C3
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Validity: 100.00%
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Avg Similarity: 0.
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Lipinski Pass Rate: 98.00%
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Input: n1c2cc3c(cc2ncc1)[C@@H]4CNC[C@H]3C4
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Validity: 100.00%
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Avg Similarity: 0.
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Lipinski Pass Rate:
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```
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Example outputs:
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**t-SNE:**
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## ❤️ Support the Project
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### On contextual generated examples:
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using `model_context_eval.ipynb` as 4 nAChR-a4b2 partial agonists as inputs:
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**Generated 50 examples from input as context:**
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```
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=== Summary ===
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Total generated: 200
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Overall validity rate: 100.00%
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Input: O=C(C[C@@H]1N([C@@H](CCC1)C[C@@H](C2=CC=CC=C2)O)C)C3=CC=CC=C3
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Validity: 100.00%
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Avg Similarity: 0.620
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Lipinski Pass Rate: 38.00%
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Input: O=C2N(C)[C@H](c1cnccc1)CC2
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Validity: 100.00%
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Avg Similarity: 0.399
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Lipinski Pass Rate: 84.00%
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Input: O=C1/C=C\C=C2/N1C[C@@H]3CNC[C@H]2C3
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Validity: 100.00%
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Avg Similarity: 0.613
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Lipinski Pass Rate: 98.00%
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Input: n1c2cc3c(cc2ncc1)[C@@H]4CNC[C@H]3C4
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Validity: 100.00%
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Avg Similarity: 0.501
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Lipinski Pass Rate: 100.00%
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```
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Example outputs:
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**t-SNE:**
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## ❤️ Support the Project
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