Reduce global learning rate by 2x

viswavi · Jun 5, 2023 · d05d231 · d05d231
1 parent e688d82
commit d05d231
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Showing 2 changed files with 3 additions and 6 deletions.
diff --git a/active_semi_clustering/active/pairwise_constraints/gpt3_pc_oracle.py b/active_semi_clustering/active/pairwise_constraints/gpt3_pc_oracle.py
@@ -16,7 +16,7 @@ def __init__(self, X, labels, max_queries_cnt=2500, num_predictions=5, side_info
         self.num_predictions = num_predictions
 
         self.side_information = side_information
-        self.cache_dir = "/projects/ogma1/vijayv/okb-canonicalization/clustering/file/gpt3_cache"
+        self.cache_dir = "/home/vijayv/okb-canonicalization/clustering/file/gpt3_cache"
         self.cache_file = os.path.join(self.cache_dir, "pairwise_constraint_cache_prompt_engineered_classifier_oracle_free_selector_no_duplicate_pairs.jsonl")
         if os.path.exists(self.cache_file):
             self.cache_rows = list(jsonlines.open(self.cache_file))

diff --git a/active_semi_clustering/semi_supervised/pairwise_constraints/sccl.py b/active_semi_clustering/semi_supervised/pairwise_constraints/sccl.py
@@ -40,8 +40,7 @@ def __init__(self,
                  batch_size = 400,
                  linear_transformation = False,
                  canonicalization_side_information=None,
-                 tensorboard_parent_dir="/projects/ogma1/vijayv/okb-canonicalization/clustering/sccl/",
-                 tensorboard_dir="tmp"):
+                 tensorboard_parent_dir="/projects/ogma1/vijayv/okb-canonicalization/clustering/sccl/",                 tensorboard_dir="tmp"):
         self.n_clusters = n_clusters
         self.max_iter = max_iter
         self.normalize_vectors = normalize_vectors
@@ -82,8 +81,6 @@ def fit(self, X, pairwise_constraints):
 
         train_loader = util_data.DataLoader(X.astype("float32"), batch_size=self.batch_size, shuffle=True, num_workers=1)
 
-        breakpoint()
-
         model = SCCLMatrix(emb_size=X.shape[1], cluster_centers=cluster_centers, include_contrastive_loss=self.include_contrastive_loss, linear_transformation = self.linear_transformation) 
         model = model.cuda()
 
@@ -95,7 +92,7 @@ def fit(self, X, pairwise_constraints):
 
         # optimize  
         Args = namedtuple("Args", "lr lr_scale lr_scale_scl eta temperature objective print_freq max_iter batch_size tensorboard")
-        args = Args(1e-05, 100, 100, 10, 0.5, "SCCL", 300, 2500 * X.shape[0] / self.batch_size, self.batch_size, tensorboard)
+        args = Args(5e-06, 100, 100, 10, 0.5, "SCCL", 300, 2000 * X.shape[0] / self.batch_size, self.batch_size, tensorboard)
 
 
         optimizer = get_optimizer_linear_transformation(model, args, include_contrastive_loss=self.include_contrastive_loss, linear_transformation=self.linear_transformation)