diff --git a/.readthedocs.yml b/.readthedocs.yml
index e0e218b..ecbc107 100644
--- a/.readthedocs.yml
+++ b/.readthedocs.yml
@@ -10,13 +10,11 @@ build:
   os: ubuntu-24.04
   tools:
     python: "3.12"
-  jobs:
-    post_create_environment:
-      # Install UV
-      # https://docs.astral.sh/uv/getting-started/installation/#__tabbed_1_1
-      - curl -LsSf https://astral.sh/uv/install.sh | sh
-    post_install:
-      - VIRTUAL_ENV=$READTHEDOCS_VIRTUALENV_PATH uv sync
+
+python:
+  install:
+    - method: uv
+      command: sync
 
 # Build documentation in the "docs/" directory with Sphinx
 sphinx:
diff --git a/CHANGELOG.md b/CHANGELOG.md
index 3503c80..2543049 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,9 +1,6 @@
 # Changelog
 
-## v0.2.0
-
-- Optimization module has been refactored. This is a breaking change.
-- Added initialization base class, He initialization, and Xavier initialization.
-- Added "full-batch" training by setting `batch_size` model parameter to `None`.
-- Documentation updated to include overview.
+## v0.2.1
 
+- Fixed a bug where `SequentialBuilder`could not do full batch training.
+- Added Hinge and Huber loss.
diff --git a/pyproject.toml b/pyproject.toml
index d54fd51..9dbe76d 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "phitodeep"
-version = "0.2.0"
+version = "0.2.1"
 authors = [
     { name = "Ralph Dugue", email = "ralph@phito.dev" }
 ]
diff --git a/src/phitodeep/loss.py b/src/phitodeep/loss.py
index 5a5aec3..5c76d84 100644
--- a/src/phitodeep/loss.py
+++ b/src/phitodeep/loss.py
@@ -54,3 +54,29 @@ def loss_func(self, y_pred, y_true):
 
     def loss_gradient(self, y_pred, y_true):
         return (y_pred - y_true) / (y_pred * (1 - y_pred) + 1e-8)
+
+class Hinge(LossBase):
+    def __init__(self) -> None:
+        super().__init__("Hinge")
+
+    def loss_func(self, y_pred, y_true):
+        return np.maximum(0, 1 - y_pred * y_true)
+
+    def loss_gradient(self, y_pred, y_true):
+        yz = y_pred * y_true
+        return np.where(yz < 1, -y_true, 0)
+
+class Huber(LossBase):
+    def __init__(self, delta=1.0):
+        super().__init__("Huber")
+        self.delta = delta
+
+    def loss_func(self, y_pred, y_true):
+        error = y_true - y_pred
+        L1 = error ** 2 / 2
+        L2 = self.delta * (np.abs(error) - (self.delta / 2))
+        return np.where(np.abs(error) > self.delta, L1, L2)
+
+    def loss_gradient(self, y_pred, y_true):
+        error = y_pred - y_true
+        return np.where(np.abs(error) > self.delta, self.delta * np.sign(error), error)
diff --git a/src/phitodeep/model.py b/src/phitodeep/model.py
index 5fa1033..7388e5e 100644
--- a/src/phitodeep/model.py
+++ b/src/phitodeep/model.py
@@ -160,7 +160,7 @@ def __init__(self):
         self.layers = []
         self.alpha_value = 1
         self.optimizer_type = o.Adam()
-        self.batch_size = 1
+        self.batch_size = None
         self.epochs_value = 1000
         self.loss_class = ls.MeanSquaredError()