diff --git a/README.md b/README.md
index fc21e37..f394657 100644
--- a/README.md
+++ b/README.md
@@ -84,6 +84,10 @@ If importance sampling based methods are evaluating to 0, consider visualising t
 The different kinds of importance samples can also be visualised by querying the ```traj_is_weights``` attribute of a given ```ImportanceSampler``` object. If for example, vanilla importance sampling is being used and the samples are not ```NaN``` or ```Inf``` then visualising the ```traj_is_weights``` may provide insight. In particular, IS weights will tend to inifinity when the evaluation policy places large density on an action in comparison to the behaviour policy.
 
 ### Release log
+
+#### 7.0.1
+* Made the logging location for d3rlpy/FQE callback an optional parameter
+
 #### 7.0.0 (Major API release)
 * Altered ISEstimator and OPEEstimatorBase APIs to depend on EmpiricalMeanDenomBase and WeightDenomBase
   * EmpiricalMeanDenomBase and WeightDenomBase seperatly define functions over the dataset value and weights of the individul trajectory weights, respectively. This allows a far greater number of estimators to be flexibly implemented
diff --git a/src/offline_rl_ope/_version.py b/src/offline_rl_ope/_version.py
index 195960c..9538eee 100644
--- a/src/offline_rl_ope/_version.py
+++ b/src/offline_rl_ope/_version.py
@@ -1 +1 @@
-__version__ = "7.0.0"
\ No newline at end of file
+__version__ = "7.0.1"
\ No newline at end of file
diff --git a/src/offline_rl_ope/api/d3rlpy/Callbacks/DM.py b/src/offline_rl_ope/api/d3rlpy/Callbacks/DM.py
index aced7fd..21e714f 100644
--- a/src/offline_rl_ope/api/d3rlpy/Callbacks/DM.py
+++ b/src/offline_rl_ope/api/d3rlpy/Callbacks/DM.py
@@ -33,7 +33,8 @@ def __init__(
         model_fit_kwargs:Dict, 
         dataset:MDPDataset, 
         fqe_impl_init:Optional[FQEImplInitArg]=None, 
-        device:DeviceArg = False
+        device:DeviceArg = False,
+        logs_loc:Optional[str] = None
         ) -> None:
         super().__init__(debug=False, debug_path="")
         self.__scorers = scorers
@@ -41,7 +42,10 @@ def __init__(
         self.__fqe_cls = fqe_cls
         self.__model_init_kwargs = model_init_kwargs
         self.__model_fit_kwargs = model_fit_kwargs
-        self.__logs_loc = os.path.join(os.getcwd(), "tmp_fqe_logs_loc")
+        if logs_loc:
+            self.__logs_loc = logs_loc
+        else:
+            self.__logs_loc = os.path.join(os.getcwd(), "tmp_fqe_logs_loc")
         self.__cur_exp = 0
         os.mkdir(self.__logs_loc)
         self.__fqe_impl_init = fqe_impl_init