diff --git a/distributed_q_learning/plot/plot.py b/distributed_q_learning/plot/plot.py
index 58ba309..5f66dcf 100644
--- a/distributed_q_learning/plot/plot.py
+++ b/distributed_q_learning/plot/plot.py
@@ -26,20 +26,11 @@ def running_avg(x, ws):
 
 if __name__=='__main__':
 
-    resdir = '../experiments/reproduce_deterministic'
+    resdir = '../experiments/reproduce_deterministic/'
 
     parq_list = glob.glob(join(resdir, '*/tr_rewards.parquet'))
     config_list = glob.glob(join(resdir, '*/*_config.csv'))
 
-
-    config_list = [
-    '../experiments/reproduce_deterministic/1/1_config.csv', 
-    '../experiments/reproduce_deterministic/2/2_config.csv',  
-    '../experiments/reproduce_deterministic/3/3_config.csv',
-    '../experiments/reproduce_deterministic/4/4_config.csv',
-    '../experiments/reproduce_deterministic/5/5_config.csv',
-    ]
-
     ws = 5000
 
     plt.figure(figsize=(15,7), dpi=80)
@@ -68,4 +59,4 @@ def running_avg(x, ws):
     plt.xlabel('Episodes')
     plt.ylabel('Cumulative reward')
     plt.tight_layout()
-    plt.savefig('training.png')
\ No newline at end of file
+    plt.savefig('training.png')
diff --git a/distributed_q_learning/train.py b/distributed_q_learning/train.py
index 51f2c00..d9da105 100644
--- a/distributed_q_learning/train.py
+++ b/distributed_q_learning/train.py
@@ -207,7 +207,7 @@ def eval_batch(
 ], columns=['epsilon', 'epsilon decay', 'alpha', 'alpha decay', 'n_episodes'])
 
 # Other parameters
-out_dir = 'experiments/reproduce_determinstic'
+out_dir = 'experiments/reproduce_deterministic'
 n_workers = multiprocessing.cpu_count()
 master_seed = 666
 log_every = 10_000