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diff --git a/environment/agent.py b/environment/agent.py
index 9287a21..c8a85c4 100644
--- a/environment/agent.py
+++ b/environment/agent.py
@@ -1026,7 +1026,10 @@ def train(agent: Agent,
         agent.learn(env, total_timesteps=train_timesteps, verbose=1)
         base_env.on_training_end()
     except KeyboardInterrupt:
-        pass
+        if save_handler is not None:
+            save_handler.agent.update_num_timesteps(save_handler.num_timesteps)
+            save_handler.save_agent()
+
 
     env.close()
 
diff --git a/user/pvp_match.py b/user/pvp_match.py
deleted file mode 100644
index 9ee7d754..0000000
--- a/user/pvp_match.py
+++ /dev/null
@@ -1,28 +0,0 @@
-# import skvideo
-# import skvideo.io
-from environment.environment import RenderMode
-from environment.agent import SB3Agent, CameraResolution, RecurrentPPOAgent, BasedAgent, UserInputAgent, ConstantAgent, run_match, run_real_time_match, gen_reward_manager
-from user.my_agent import SubmittedAgent, ConstantAgent
-
-reward_manager = gen_reward_manager()
-
-experiment_dir_1 = "experiment_6/" #input('Model experiment directory name (e.g. experiment_1): ')
-model_name_1 = "rl_model00_steps" #input('Name of first model (e.g. rl_model_100_steps): ')
-
-my_agent = UserInputAgent()
-#opponent = SubmittedAgent(None)
-opponent = ConstantAgent()
-# my_agent = UserInputAgent()
-# opponent = ConstantAgent()
-
-num_matches = 2 #int(input('Number of matches: '))
-#opponent=BasedAgent()
-match_time = 50000000000
-# 270
-# Run a single real-time match
-run_real_time_match(
-    agent_1=my_agent,
-    agent_2=opponent,
-    max_timesteps=30 * 999990000,  # Match time in frames (adjust as needed)
-    resolution=CameraResolution.LOW,
-)
\ No newline at end of file