diff --git a/pyproject.toml b/pyproject.toml
index 9ad67878..112c8f9a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -10,7 +10,7 @@ namespaces = true
 
 [project]
 name = "aiXplain"
-version = "0.2.5rc"
+version = "0.2.12"
 description = "aiXplain SDK adds AI functions to software."
 readme = "README.md"
 requires-python = ">=3.5, <4"
@@ -51,7 +51,7 @@ dependencies = [
     "filetype>=1.2.0",
     "click>=7.1.2,<8.0.0",
     "PyYAML>=6.0.1",
-    "dataclasses-json==0.6.1"
+    "dataclasses-json>=0.5.2"
 ]
 
 [project.urls]
diff --git a/tests/functional/finetune/data/finetune_test_end2end.json b/tests/functional/finetune/data/finetune_test_end2end.json
index ead1fd88..80768de9 100644
--- a/tests/functional/finetune/data/finetune_test_end2end.json
+++ b/tests/functional/finetune/data/finetune_test_end2end.json
@@ -10,17 +10,17 @@
     {
         "model_name": "aiR",
         "model_id": "6499cc946eb5633de15d82a1",
-        "dataset_name": "Test search dataset metadata",
+        "dataset_name": "Test search dataset",
         "inference_data": "Hello!",
         "required_dev": false,
-        "search_metadata": true
+        "search_metadata": false
     },
     {
         "model_name": "vectara",
         "model_id": "655e20f46eb563062a1aa301",
-        "dataset_name": "Test search dataset metadata",
+        "dataset_name": "Test search dataset",
         "inference_data": "Hello!",
         "required_dev": false,
-        "search_metadata": true
+        "search_metadata": false
     }
 ]
\ No newline at end of file
diff --git a/tests/functional/finetune/finetune_functional_test.py b/tests/functional/finetune/finetune_functional_test.py
index 94693f05..ffa9ad5a 100644
--- a/tests/functional/finetune/finetune_functional_test.py
+++ b/tests/functional/finetune/finetune_functional_test.py
@@ -83,6 +83,8 @@ def test_end2end(run_input_map):
         time.sleep(5)
         end = time.time()
     assert finetune_model.check_finetune_status().model_status.value == "onboarded"
+    time.sleep(30)
+    print(f"Model dict: {finetune_model.__dict__}")
     result = finetune_model.run(run_input_map["inference_data"])
     print(f"Result: {result}")
     assert result is not None