Merge branch 'main' of https://github.com/tschomacker/generalizing-pa…

…ssages-identification-bert into main : Please enter a commit message to explain why this merge is necessary, merge
tschomacker · Dec 14, 2022 · 55946cf · 55946cf
2 parents bd7cfda + 6b6b3f2
commit 55946cf
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diff --git a/README.md b/README.md
@@ -152,7 +152,7 @@ PRETRAINED_MODEL_STR = "deepset/gbert-large"
 EVALUATION_TOKENIZER = AutoTokenizer.from_pretrained(PRETRAINED_MODEL_STR)
 labels = ['reflexive']
 saved_model_path = os.path.join('..','output','saved_models', 
-                                'reflexive_ex_mk_binary_gbert-large_monaco_epochs:20_lamb_0.0001_None_dh:0.3_da:0.0.pt')
+                                'reflexive_ex_mk_binary_gbert-large_monaco-ex-kleist_epochs_20_lamb_0.0001_None_dh_0.3_da_0.0.pt')
 
 device = 'cuda' if cuda.is_available() else 'cpu'
 fine_tuned_model = load_model(model_path = saved_model_path, device = device, 

diff --git a/src/ml/model_util.py b/src/ml/model_util.py
@@ -103,7 +103,7 @@ def load_model(model_path, device, petrained_model_str, no_labels):
     #except RuntimeError: 
         # 'Attempting to deserialize object on a CUDA '
     #    print('loading a cuda model on the CPU')
-    trained_model.load_state_dict(torch.load(model_path, map_location=torch.device(device)))
+    trained_model.load_state_dict(torch.load(model_path, map_location=torch.device(device)), strict=False)
     trained_model.to(device)
     return trained_model