diff --git a/sbx/crossq/crossq.py b/sbx/crossq/crossq.py
index 94e2bbc..4a1ffeb 100644
--- a/sbx/crossq/crossq.py
+++ b/sbx/crossq/crossq.py
@@ -211,7 +211,7 @@ def train(self, gradient_steps: int, batch_size: int) -> None:
             self.policy.actor_state,
             self.ent_coef_state,
             self.key,
-            (actor_loss_value, qf_loss_value, ent_coef_value),
+            (actor_loss_value, qf_loss_value, ent_coef_loss),
         ) = self._train(
             self.gamma,
             self.target_entropy,
@@ -224,11 +224,14 @@ def train(self, gradient_steps: int, batch_size: int) -> None:
             self.ent_coef_state,
             self.key,
         )
+        ent_coef_value = self.ent_coef_state.apply_fn({"params": self.ent_coef_state.params})
         self._n_updates += gradient_steps
         self.logger.record("train/n_updates", self._n_updates, exclude="tensorboard")
         self.logger.record("train/actor_loss", actor_loss_value.item())
         self.logger.record("train/critic_loss", qf_loss_value.item())
         self.logger.record("train/ent_coef", ent_coef_value.item())
+        if isinstance(self.ent_coef, EntropyCoef):
+            self.logger.record("train/ent_coef_loss", ent_coef_loss.item())
 
     @staticmethod
     @jax.jit
diff --git a/sbx/sac/sac.py b/sbx/sac/sac.py
index 11f8ff5..f566aea 100644
--- a/sbx/sac/sac.py
+++ b/sbx/sac/sac.py
@@ -213,7 +213,7 @@ def train(self, gradient_steps: int, batch_size: int) -> None:
             self.policy.actor_state,
             self.ent_coef_state,
             self.key,
-            (actor_loss_value, qf_loss_value, ent_coef_value),
+            (actor_loss_value, qf_loss_value, ent_coef_loss),
         ) = self._train(
             self.gamma,
             self.tau,
@@ -227,11 +227,15 @@ def train(self, gradient_steps: int, batch_size: int) -> None:
             self.ent_coef_state,
             self.key,
         )
+        ent_coef_value = self.ent_coef_state.apply_fn({"params": self.ent_coef_state.params})
+
         self._n_updates += gradient_steps
         self.logger.record("train/n_updates", self._n_updates, exclude="tensorboard")
         self.logger.record("train/actor_loss", actor_loss_value.item())
         self.logger.record("train/critic_loss", qf_loss_value.item())
         self.logger.record("train/ent_coef", ent_coef_value.item())
+        if isinstance(self.ent_coef, EntropyCoef):
+            self.logger.record("train/ent_coef_loss", ent_coef_loss.item())
 
     @staticmethod
     @jax.jit
diff --git a/sbx/tqc/tqc.py b/sbx/tqc/tqc.py
index 5161f4d..b65c0c5 100644
--- a/sbx/tqc/tqc.py
+++ b/sbx/tqc/tqc.py
@@ -216,7 +216,7 @@ def train(self, gradient_steps: int, batch_size: int) -> None:
             self.policy.actor_state,
             self.ent_coef_state,
             self.key,
-            (qf1_loss_value, qf2_loss_value, actor_loss_value, ent_coef_value),
+            (qf1_loss_value, qf2_loss_value, actor_loss_value, ent_coef_loss),
         ) = self._train(
             self.gamma,
             self.tau,
@@ -232,11 +232,15 @@ def train(self, gradient_steps: int, batch_size: int) -> None:
             self.ent_coef_state,
             self.key,
         )
+        ent_coef_value = self.ent_coef_state.apply_fn({"params": self.ent_coef_state.params})
+
         self._n_updates += gradient_steps
         self.logger.record("train/n_updates", self._n_updates, exclude="tensorboard")
         self.logger.record("train/actor_loss", actor_loss_value.item())
         self.logger.record("train/critic_loss", qf1_loss_value.item())
         self.logger.record("train/ent_coef", ent_coef_value.item())
+        if isinstance(self.ent_coef, EntropyCoef):
+            self.logger.record("train/ent_coef_loss", ent_coef_loss.item())
 
     @staticmethod
     @partial(jax.jit, static_argnames=["n_target_quantiles"])