Update README.md

README.md

@@ -2,7 +2,7 @@
 license: cc-by-4.0
 ---
 
-Mirror of OpenFold parameters as provided in https://github.com/aqlaboratory/openfold. Stopgap solution as the original download link was down. All rights to the authors.
+Mirror of OpenFold parameters as provided in https://github.com/aqlaboratory/openfold. Stopgap solution as the original download link was down. Updated based on the s3 bucket parameter update. All rights to the authors.
 
 OpenFold model parameters, v. 06_22. 
 
@@ -12,6 +12,9 @@ Trained using OpenFold on 44 A100s using the training schedule from Table 4 in
 the AlphaFold supplement. AlphaFold was used as the pre-distillation model. 
 Training data is hosted publicly in the "OpenFold Training Data" RODA repository.
 
+To improve model diversity, we forked training after the initial training phase
+and finetuned an additonal branch without templates.
+
 # Parameter files:
 
 Parameter files fall into the following categories:
@@ -22,21 +25,35 @@ Parameter files fall into the following categories:
         Checkpoints in chronological order corresponding to peaks in the 
         validation LDDT-Ca during the finetuning phase. Roughly evenly spaced 
         across the 45 finetuning epochs.
+        
+        NOTE: finetuning_1.pt, which was included in a previous release, has
+        been deprecated.
+    finetuning_no_templ_x.pt
+        Checkpoints in chronological order corresponding to peaks during an
+        additional finetuning phase also starting from the 'initial_training.pt' 
+        checkpoint but with templates disabled.
+    finetuning_no_templ_ptm_x.pt
+        Checkpoints in chronological order corresponding to peaks during the 
+        pTM training phase of the `no_templ` branch. Models in this category
+        include the pTM module and comprise the most recent of the checkpoints
+        in said branch.
     finetuning_ptm_x.pt:
-        Checkpoints in chronological order corresponding to peaks inthe pTM
-        training phase, a short additional training phase that takes place 
-        after finetuning. Models in this category include the pTM module and 
-        comprise the most recent of the checkpoints in this directory.
+        Checkpoints in chronological order corresponding to peaks in the pTM
+        training phase of the mainline branch. Models in this category include 
+        the pTM module and comprise the most recent of the checkpoints in said
+        branch.
     
 Average validation LDDT-Ca scores for each of the checkpoints are listed below. 
 The validation set contains approximately 180 chains drawn from CAMEO over a 
 three-month period at the end of 2021.
 
     initial_training: 0.9088
-    finetuning_ptm_1: 0.9075
-    finetuning_ptm_2: 0.9097
-    finetuning_1: 0.9089
     finetuning_2: 0.9061
     finetuning_3: 0.9075
     finetuning_4: 0.9059
-    finetuning_5: 0.9054
+    finetuning_5: 0.9054
+    finetuning_no_templ_1: 0.9014
+    finetuning_no_templ_2: 0.9032
+    finetuning_no_templ_ptm_1: 0.9025
+    finetuning_ptm_1: 0.9075
+    finetuning_ptm_2: 0.9097