Working training loop and testing of trained CharacterModel.

82 files changed, 1936 insertions, 93 deletions

diff --git a/src/training/callbacks/__init__.py b/src/training/callbacks/__init__.py
new file mode 100644
index 0000000..868d739
--- /dev/null
+++ b/src/training/callbacks/__init__.py
@@ -0,0 +1 @@
+"""TBC."""
diff --git a/src/training/callbacks/base.py b/src/training/callbacks/base.py
new file mode 100644
index 0000000..d80a1e5
--- /dev/null
+++ b/src/training/callbacks/base.py
@@ -0,0 +1,101 @@
+"""Metaclass for callback functions."""
+
+from abc import ABC
+from typing import Callable, List, Type
+
+
+class Callback(ABC):
+    """Metaclass for callbacks used in training."""
+
+    def on_fit_begin(self) -> None:
+        """Called when fit begins."""
+        pass
+
+    def on_fit_end(self) -> None:
+        """Called when fit ends."""
+        pass
+
+    def on_train_epoch_begin(self) -> None:
+        """Called at the beginning of an epoch."""
+        pass
+
+    def on_train_epoch_end(self) -> None:
+        """Called at the end of an epoch."""
+        pass
+
+    def on_val_epoch_begin(self) -> None:
+        """Called at the beginning of an epoch."""
+        pass
+
+    def on_val_epoch_end(self) -> None:
+        """Called at the end of an epoch."""
+        pass
+
+    def on_train_batch_begin(self) -> None:
+        """Called at the beginning of an epoch."""
+        pass
+
+    def on_train_batch_end(self) -> None:
+        """Called at the end of an epoch."""
+        pass
+
+    def on_val_batch_begin(self) -> None:
+        """Called at the beginning of an epoch."""
+        pass
+
+    def on_val_batch_end(self) -> None:
+        """Called at the end of an epoch."""
+        pass
+
+
+class CallbackList:
+    """Container for abstracting away callback calls."""
+
+    def __init__(self, callbacks: List[Callable] = None) -> None:
+        """TBC."""
+        self._callbacks = callbacks if callbacks is not None else []
+
+    def append(self, callback: Type[Callback]) -> None:
+        """Append new callback to callback list."""
+        self.callbacks.append(callback)
+
+    def on_fit_begin(self) -> None:
+        """Called when fit begins."""
+        for _ in self._callbacks:
+            pass
+
+    def on_fit_end(self) -> None:
+        """Called when fit ends."""
+        pass
+
+    def on_train_epoch_begin(self) -> None:
+        """Called at the beginning of an epoch."""
+        pass
+
+    def on_train_epoch_end(self) -> None:
+        """Called at the end of an epoch."""
+        pass
+
+    def on_val_epoch_begin(self) -> None:
+        """Called at the beginning of an epoch."""
+        pass
+
+    def on_val_epoch_end(self) -> None:
+        """Called at the end of an epoch."""
+        pass
+
+    def on_train_batch_begin(self) -> None:
+        """Called at the beginning of an epoch."""
+        pass
+
+    def on_train_batch_end(self) -> None:
+        """Called at the end of an epoch."""
+        pass
+
+    def on_val_batch_begin(self) -> None:
+        """Called at the beginning of an epoch."""
+        pass
+
+    def on_val_batch_end(self) -> None:
+        """Called at the end of an epoch."""
+        pass
diff --git a/src/training/callbacks/early_stopping.py b/src/training/callbacks/early_stopping.py
new file mode 100644
index 0000000..4da0e85
--- /dev/null
+++ b/src/training/callbacks/early_stopping.py
@@ -0,0 +1 @@
+"""Implements Early stopping for PyTorch model."""
diff --git a/src/training/experiments/CharacterModel_Emnist_LeNet/0721_231455/config.yml b/src/training/experiments/CharacterModel_Emnist_LeNet/0721_231455/config.yml
new file mode 100644
index 0000000..2595325
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_LeNet/0721_231455/config.yml
@@ -0,0 +1,48 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 8
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.001
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: LeNet
+network_args:
+  input_size:
+  - 28
+  - 28
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  amsgrad: false
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.01
+  weight_decay: 0
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_LeNet/0721_231455/model/best.pt b/src/training/experiments/CharacterModel_Emnist_LeNet/0721_231455/model/best.pt
new file mode 100644
index 0000000..6d78bad
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_LeNet/0721_231455/model/best.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_LeNet/0721_231455/model/last.pt b/src/training/experiments/CharacterModel_Emnist_LeNet/0721_231455/model/last.pt
new file mode 100644
index 0000000..6d78bad
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_LeNet/0721_231455/model/last.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_LeNet/0722_190746/config.yml b/src/training/experiments/CharacterModel_Emnist_LeNet/0722_190746/config.yml
new file mode 100644
index 0000000..2595325
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_LeNet/0722_190746/config.yml
@@ -0,0 +1,48 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 8
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.001
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: LeNet
+network_args:
+  input_size:
+  - 28
+  - 28
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  amsgrad: false
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.01
+  weight_decay: 0
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_LeNet/0722_190746/model/best.pt b/src/training/experiments/CharacterModel_Emnist_LeNet/0722_190746/model/best.pt
new file mode 100644
index 0000000..43a3891
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_LeNet/0722_190746/model/best.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_LeNet/0722_190746/model/last.pt b/src/training/experiments/CharacterModel_Emnist_LeNet/0722_190746/model/last.pt
new file mode 100644
index 0000000..61c03f0
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_LeNet/0722_190746/model/last.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_124928/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_124928/config.yml
new file mode 100644
index 0000000..2aa52cd
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_124928/config.yml
@@ -0,0 +1,43 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 0
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: null
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  amsgrad: false
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.001
+  weight_decay: 0
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_141139/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_141139/config.yml
new file mode 100644
index 0000000..829297d
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_141139/config.yml
@@ -0,0 +1,47 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 0
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.0003
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  amsgrad: false
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.0006
+  weight_decay: 5.0e-05
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_141213/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_141213/config.yml
new file mode 100644
index 0000000..829297d
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_141213/config.yml
@@ -0,0 +1,47 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 0
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.0003
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  amsgrad: false
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.0006
+  weight_decay: 5.0e-05
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_141213/model/best.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_141213/model/best.pt
new file mode 100644
index 0000000..d0db78b
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_141213/model/best.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_141213/model/last.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_141213/model/last.pt
new file mode 100644
index 0000000..d0db78b
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_141213/model/last.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_141433/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_141433/config.yml
new file mode 100644
index 0000000..3df32bb
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_141433/config.yml
@@ -0,0 +1,47 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 0
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.01
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  amsgrad: false
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.1
+  weight_decay: 5.0e-05
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_141433/model/best.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_141433/model/best.pt
new file mode 100644
index 0000000..5914c8f
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_141433/model/best.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_141433/model/last.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_141433/model/last.pt
new file mode 100644
index 0000000..5ba44bb
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_141433/model/last.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_141702/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_141702/config.yml
new file mode 100644
index 0000000..fb75736
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_141702/config.yml
@@ -0,0 +1,47 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 0
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.001
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  amsgrad: false
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.01
+  weight_decay: 5.0e-05
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_141702/model/best.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_141702/model/best.pt
new file mode 100644
index 0000000..96c21c1
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_141702/model/best.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_141702/model/last.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_141702/model/last.pt
new file mode 100644
index 0000000..f024c0d
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_141702/model/last.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_145028/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_145028/config.yml
new file mode 100644
index 0000000..fb75736
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_145028/config.yml
@@ -0,0 +1,47 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 0
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.001
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  amsgrad: false
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.01
+  weight_decay: 5.0e-05
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_150212/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_150212/config.yml
new file mode 100644
index 0000000..fb75736
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_150212/config.yml
@@ -0,0 +1,47 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 0
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.001
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  amsgrad: false
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.01
+  weight_decay: 5.0e-05
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_150301/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_150301/config.yml
new file mode 100644
index 0000000..fb75736
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_150301/config.yml
@@ -0,0 +1,47 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 0
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.001
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  amsgrad: false
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.01
+  weight_decay: 5.0e-05
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_150317/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_150317/config.yml
new file mode 100644
index 0000000..fb75736
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_150317/config.yml
@@ -0,0 +1,47 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 0
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.001
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  amsgrad: false
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.01
+  weight_decay: 5.0e-05
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_151135/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_151135/config.yml
new file mode 100644
index 0000000..fb75736
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_151135/config.yml
@@ -0,0 +1,47 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 0
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.001
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  amsgrad: false
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.01
+  weight_decay: 5.0e-05
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_151135/model/best.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_151135/model/best.pt
new file mode 100644
index 0000000..f833a89
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_151135/model/best.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_151135/model/last.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_151135/model/last.pt
new file mode 100644
index 0000000..f833a89
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_151135/model/last.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_151408/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_151408/config.yml
new file mode 100644
index 0000000..fb75736
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_151408/config.yml
@@ -0,0 +1,47 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 0
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.001
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  amsgrad: false
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.01
+  weight_decay: 5.0e-05
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_153144/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_153144/config.yml
new file mode 100644
index 0000000..829297d
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_153144/config.yml
@@ -0,0 +1,47 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 0
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.0003
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  amsgrad: false
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.0006
+  weight_decay: 5.0e-05
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_153207/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_153207/config.yml
new file mode 100644
index 0000000..fb75736
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_153207/config.yml
@@ -0,0 +1,47 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 0
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.001
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  amsgrad: false
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.01
+  weight_decay: 5.0e-05
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_153310/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_153310/config.yml
new file mode 100644
index 0000000..fb75736
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_153310/config.yml
@@ -0,0 +1,47 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 0
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.001
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  amsgrad: false
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.01
+  weight_decay: 5.0e-05
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_153310/model/best.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_153310/model/best.pt
new file mode 100644
index 0000000..cbbc5e1
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_153310/model/best.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_153310/model/last.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_153310/model/last.pt
new file mode 100644
index 0000000..cbbc5e1
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_153310/model/last.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_175150/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_175150/config.yml
new file mode 100644
index 0000000..fb75736
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_175150/config.yml
@@ -0,0 +1,47 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 0
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.001
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  amsgrad: false
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.01
+  weight_decay: 5.0e-05
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_175150/model/best.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_175150/model/best.pt
new file mode 100644
index 0000000..c93e3c6
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_175150/model/best.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_175150/model/last.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_175150/model/last.pt
new file mode 100644
index 0000000..c93e3c6
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_175150/model/last.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_180741/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_180741/config.yml
new file mode 100644
index 0000000..1be5113
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_180741/config.yml
@@ -0,0 +1,47 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 0
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.001
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: Adam
+optimizer_args:
+  amsgrad: false
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.01
+  weight_decay: 5.0e-05
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_180741/model/best.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_180741/model/best.pt
new file mode 100644
index 0000000..580bad2
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_180741/model/best.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_180741/model/last.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_180741/model/last.pt
new file mode 100644
index 0000000..97e245c
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_180741/model/last.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_181933/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_181933/config.yml
new file mode 100644
index 0000000..d2f98a2
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_181933/config.yml
@@ -0,0 +1,46 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 0
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.001
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: Adamax
+optimizer_args:
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.01
+  weight_decay: 0
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_181933/model/best.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_181933/model/best.pt
new file mode 100644
index 0000000..5a3df56
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_181933/model/best.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_181933/model/last.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_181933/model/last.pt
new file mode 100644
index 0000000..7f28dc3
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_181933/model/last.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_183347/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_183347/config.yml
new file mode 100644
index 0000000..d2f98a2
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_183347/config.yml
@@ -0,0 +1,46 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 0
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.001
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: Adamax
+optimizer_args:
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.01
+  weight_decay: 0
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_183347/model/best.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_183347/model/best.pt
new file mode 100644
index 0000000..6f09780
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_183347/model/best.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_183347/model/last.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_183347/model/last.pt
new file mode 100644
index 0000000..3bb103e
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_183347/model/last.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_190044/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_190044/config.yml
new file mode 100644
index 0000000..a7c66c5
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_190044/config.yml
@@ -0,0 +1,46 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 0
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.001
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.01
+  weight_decay: 0
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_190044/model/best.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_190044/model/best.pt
new file mode 100644
index 0000000..c3e3618
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_190044/model/best.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_190044/model/last.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_190044/model/last.pt
new file mode 100644
index 0000000..c3e3618
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_190044/model/last.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_190633/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_190633/config.yml
new file mode 100644
index 0000000..a7c66c5
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_190633/config.yml
@@ -0,0 +1,46 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 0
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.001
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.01
+  weight_decay: 0
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_190633/model/best.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_190633/model/best.pt
new file mode 100644
index 0000000..44d9b9b
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_190633/model/best.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_190633/model/last.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_190633/model/last.pt
new file mode 100644
index 0000000..44d9b9b
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_190633/model/last.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_190738/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_190738/config.yml
new file mode 100644
index 0000000..a7c66c5
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_190738/config.yml
@@ -0,0 +1,46 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 0
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.001
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.01
+  weight_decay: 0
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_190738/model/best.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_190738/model/best.pt
new file mode 100644
index 0000000..4a0333c
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_190738/model/best.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_190738/model/last.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_190738/model/last.pt
new file mode 100644
index 0000000..4a0333c
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_190738/model/last.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_191111/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191111/config.yml
new file mode 100644
index 0000000..a7c66c5
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191111/config.yml
@@ -0,0 +1,46 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 0
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.001
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.01
+  weight_decay: 0
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_191310/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191310/config.yml
new file mode 100644
index 0000000..08c344c
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191310/config.yml
@@ -0,0 +1,46 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 1
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.001
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.01
+  weight_decay: 0
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_191310/model/best.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191310/model/best.pt
new file mode 100644
index 0000000..076aae1
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191310/model/best.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_191310/model/last.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191310/model/last.pt
new file mode 100644
index 0000000..076aae1
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191310/model/last.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_191412/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191412/config.yml
new file mode 100644
index 0000000..0b9b10e
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191412/config.yml
@@ -0,0 +1,42 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 1
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: null
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: RMSprop
+optimizer_args:
+  alpha: 0.9
+  centered: false
+  eps: 1.0e-07
+  lr: 0.001
+  momentum: 0
+  weight_decay: 0
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_191412/model/best.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191412/model/best.pt
new file mode 100644
index 0000000..2fb0195
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191412/model/best.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_191412/model/last.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191412/model/last.pt
new file mode 100644
index 0000000..2fb0195
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191412/model/last.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_191504/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191504/config.yml
new file mode 100644
index 0000000..93c2854
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191504/config.yml
@@ -0,0 +1,42 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 4
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: null
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: RMSprop
+optimizer_args:
+  alpha: 0.9
+  centered: false
+  eps: 1.0e-07
+  lr: 0.001
+  momentum: 0
+  weight_decay: 0
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_191504/model/best.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191504/model/best.pt
new file mode 100644
index 0000000..9acc5b1
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191504/model/best.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_191504/model/last.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191504/model/last.pt
new file mode 100644
index 0000000..b8cc01c
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191504/model/last.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_191826/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191826/config.yml
new file mode 100644
index 0000000..7340941
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191826/config.yml
@@ -0,0 +1,47 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 8
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.001
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  amsgrad: false
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.01
+  weight_decay: 0
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_191826/model/best.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191826/model/best.pt
new file mode 100644
index 0000000..26bfb07
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191826/model/best.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0721_191826/model/last.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191826/model/last.pt
new file mode 100644
index 0000000..26bfb07
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0721_191826/model/last.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0722_191559/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0722_191559/config.yml
new file mode 100644
index 0000000..90f0e13
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0722_191559/config.yml
@@ -0,0 +1,49 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 8
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 33
+  max_lr: 0.001
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  amsgrad: false
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.01
+  weight_decay: 0
+resume_experiment: last
+train_args:
+  batch_size: 256
+  epochs: 33
+  val_metric: accuracy
+verbosity: 1
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0722_191559/model/best.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0722_191559/model/best.pt
new file mode 100644
index 0000000..f0f297b
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0722_191559/model/best.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0722_191559/model/last.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0722_191559/model/last.pt
new file mode 100644
index 0000000..c1adda5
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0722_191559/model/last.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0722_213125/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0722_213125/config.yml
new file mode 100644
index 0000000..8d77de5
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0722_213125/config.yml
@@ -0,0 +1,49 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 8
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.001
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  amsgrad: false
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.01
+  weight_decay: 0
+resume_experiment: null
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
+verbosity: 2
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0722_213413/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0722_213413/config.yml
new file mode 100644
index 0000000..8d77de5
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0722_213413/config.yml
@@ -0,0 +1,49 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 8
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.001
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  amsgrad: false
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.01
+  weight_decay: 0
+resume_experiment: null
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
+verbosity: 2
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0722_213413/model/best.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0722_213413/model/best.pt
new file mode 100644
index 0000000..e985997
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0722_213413/model/best.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0722_213413/model/last.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0722_213413/model/last.pt
new file mode 100644
index 0000000..e985997
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0722_213413/model/last.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0722_213549/config.yml b/src/training/experiments/CharacterModel_Emnist_MLP/0722_213549/config.yml
new file mode 100644
index 0000000..8d77de5
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0722_213549/config.yml
@@ -0,0 +1,49 @@
+criterion: CrossEntropyLoss
+criterion_args:
+  ignore_index: -100
+  reduction: mean
+  weight: null
+data_loader_args:
+  batch_size: 256
+  cuda: true
+  num_workers: 8
+  sample_to_balance: true
+  seed: 4711
+  shuffle: true
+  splits:
+  - train
+  - val
+  subsample_fraction: null
+  target_transform: null
+  transform: null
+dataloader: EmnistDataLoader
+device: cuda:0
+experiment_group: Sample Experiments
+lr_scheduler: OneCycleLR
+lr_scheduler_args:
+  epochs: 16
+  max_lr: 0.001
+  steps_per_epoch: 1314
+metrics:
+- accuracy
+model: CharacterModel
+network: MLP
+network_args:
+  input_size: 784
+  num_layers: 3
+  output_size: 62
+optimizer: AdamW
+optimizer_args:
+  amsgrad: false
+  betas:
+  - 0.9
+  - 0.999
+  eps: 1.0e-08
+  lr: 0.01
+  weight_decay: 0
+resume_experiment: null
+train_args:
+  batch_size: 256
+  epochs: 16
+  val_metric: accuracy
+verbosity: 2
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0722_213549/model/best.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0722_213549/model/best.pt
new file mode 100644
index 0000000..0dde787
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0722_213549/model/best.pt
diff --git a/src/training/experiments/CharacterModel_Emnist_MLP/0722_213549/model/last.pt b/src/training/experiments/CharacterModel_Emnist_MLP/0722_213549/model/last.pt
new file mode 100644
index 0000000..e02738b
--- /dev/null
+++ b/src/training/experiments/CharacterModel_Emnist_MLP/0722_213549/model/last.pt
diff --git a/src/training/experiments/sample.yml b/src/training/experiments/sample.yml
new file mode 100644
index 0000000..0ed560d
--- /dev/null
+++ b/src/training/experiments/sample.yml
@@ -0,0 +1,43 @@
+experiment_group: Sample Experiments
+experiments:
+    - dataloader: EmnistDataLoader
+      model: CharacterModel
+      metrics: [accuracy]
+      network: MLP
+      network_args:
+        input_shape: 784
+        num_layers: 2
+      train_args:
+        batch_size: 256
+        epochs: 16
+      criterion: CrossEntropyLoss
+      criterion_args:
+        weight: null
+        ignore_index: -100
+        reduction: mean
+      optimizer: AdamW
+      optimizer_args:
+        lr: 3.e-4
+        betas: [0.9, 0.999]
+        eps: 1.e-08
+        weight_decay: 0
+        amsgrad: false
+      lr_scheduler: OneCycleLR
+      lr_scheduler_args:
+        max_lr: 3.e-5
+        epochs: 16
+    # - dataloader: EmnistDataLoader
+    #   model: CharacterModel
+    #   network: MLP
+    #   network_args:
+    #     input_shape: 784
+    #     num_layers: 4
+    #   train_args:
+    #     batch_size: 256
+    # - dataloader: EmnistDataLoader
+    #   model: CharacterModel
+    #   network: LeNet
+    #   network_args:
+    #     input_shape: [28, 28]
+    #   train_args:
+    #     batch_size: 256
diff --git a/src/training/experiments/sample_experiment.yml b/src/training/experiments/sample_experiment.yml
new file mode 100644
index 0000000..e8d5023
--- /dev/null
+++ b/src/training/experiments/sample_experiment.yml
@@ -0,0 +1,56 @@
+experiment_group: Sample Experiments
+experiments:
+    - dataloader: EmnistDataLoader
+      data_loader_args:
+        splits: [train, val]
+        sample_to_balance: true
+        subsample_fraction: null
+        transform: null
+        target_transform: null
+        batch_size: 256
+        shuffle: true
+        num_workers: 8
+        cuda: true
+        seed: 4711
+      model: CharacterModel
+      metrics: [accuracy]
+      network: MLP
+      network_args:
+        input_size: 784
+        output_size: 62
+        num_layers: 3
+      # network: LeNet
+      # network_args:
+      #   input_size: [28, 28]
+      #   output_size: 62
+      train_args:
+        batch_size: 256
+        epochs: 16
+        val_metric: accuracy
+      criterion: CrossEntropyLoss
+      criterion_args:
+        weight: null
+        ignore_index: -100
+        reduction: mean
+      # optimizer: RMSprop
+      # optimizer_args:
+      #   lr: 1.e-3
+      #   alpha: 0.9
+      #   eps: 1.e-7
+      #   momentum: 0
+      #   weight_decay: 0
+      #   centered: false
+      optimizer: AdamW
+      optimizer_args:
+        lr: 1.e-2
+        betas: [0.9, 0.999]
+        eps: 1.e-08
+        weight_decay: 0
+        amsgrad: false
+      # lr_scheduler: null
+      lr_scheduler: OneCycleLR
+      lr_scheduler_args:
+        max_lr: 1.e-3
+        epochs: 16
+      verbosity: 2 # 0, 1, 2
+      resume_experiment: null
diff --git a/src/training/prepare_experiments.py b/src/training/prepare_experiments.py
index 1ab8f00..eb872d7 100644
--- a/src/training/prepare_experiments.py
+++ b/src/training/prepare_experiments.py
@@ -1,22 +1,24 @@
 """Run a experiment from a config file."""
 import json
+from subprocess import check_call
 
 import click
 from loguru import logger
 import yaml
 
 
-def run_experiment(experiment_filename: str) -> None:
+def run_experiments(experiments_filename: str) -> None:
     """Run experiment from file."""
-    with open(experiment_filename) as f:
+    with open(experiments_filename) as f:
         experiments_config = yaml.safe_load(f)
     num_experiments = len(experiments_config["experiments"])
     for index in range(num_experiments):
         experiment_config = experiments_config["experiments"][index]
         experiment_config["experiment_group"] = experiments_config["experiment_group"]
-        print(
-            f"python training/run_experiment.py --gpu=-1 '{json.dumps(experiment_config)}'"
-        )
+        # cmd = f"python training/run_experiment.py --gpu=-1 '{json.dumps(experiment_config)}'"
+        cmd = f"poetry run run-experiment --gpu=-1 --save --experiment_config '{json.dumps(experiment_config)}'"
+        print(cmd)
+        check_call(cmd, shell=True)
 
 
 @click.command()
@@ -26,9 +28,9 @@ def run_experiment(experiment_filename: str) -> None:
     type=str,
     help="Filename of Yaml file of experiments to run.",
 )
-def main(experiment_filename: str) -> None:
+def main(experiments_filename: str) -> None:
     """Parse command-line arguments and run experiments from provided file."""
-    run_experiment(experiment_filename)
+    run_experiments(experiments_filename)
 
 
 if __name__ == "__main__":
diff --git a/src/training/run_experiment.py b/src/training/run_experiment.py
index 8296e59..0b29ce9 100644
--- a/src/training/run_experiment.py
+++ b/src/training/run_experiment.py
@@ -1,17 +1,64 @@
 """Script to run experiments."""
+from datetime import datetime
+from glob import glob
 import importlib
+import json
 import os
-from typing import Dict
+from pathlib import Path
+import re
+from typing import Callable, Dict, Tuple
 
 import click
+from loguru import logger
 import torch
+from tqdm import tqdm
+from training.gpu_manager import GPUManager
 from training.train import Trainer
+import yaml
 
 
-def run_experiment(
-    experiment_config: Dict, save_weights: bool, gpu_index: int, use_wandb: bool = False
-) -> None:
-    """Short summary."""
+EXPERIMENTS_DIRNAME = Path(__file__).parents[0].resolve() / "experiments"
+
+
+DEFAULT_TRAIN_ARGS = {"batch_size": 64, "epochs": 16}
+
+
+def get_level(experiment_config: Dict) -> int:
+    """Sets the logger level."""
+    if experiment_config["verbosity"] == 0:
+        return 40
+    elif experiment_config["verbosity"] == 1:
+        return 20
+    else:
+        return 10
+
+
+def create_experiment_dir(model: Callable, experiment_config: Dict) -> Path:
+    """Create new experiment."""
+    EXPERIMENTS_DIRNAME.mkdir(parents=True, exist_ok=True)
+    experiment_dir = EXPERIMENTS_DIRNAME / model.__name__
+    if experiment_config["resume_experiment"] is None:
+        experiment = datetime.now().strftime("%m%d_%H%M%S")
+        logger.debug(f"Creating a new experiment called {experiment}")
+    else:
+        available_experiments = glob(str(experiment_dir) + "/*")
+        available_experiments.sort()
+        if experiment_config["resume_experiment"] == "last":
+            experiment = available_experiments[-1]
+            logger.debug(f"Resuming the latest experiment {experiment}")
+        else:
+            experiment = experiment_config["resume_experiment"]
+            assert (
+                str(experiment_dir / experiment) in available_experiments
+            ), "Experiment does not exist."
+            logger.debug(f"Resuming the experiment {experiment}")
+
+    experiment_dir = experiment_dir / experiment
+    return experiment_dir
+
+
+def load_modules_and_arguments(experiment_config: Dict) -> Tuple[Callable, Dict]:
+    """Loads all modules and arguments."""
     # Import the data loader module and arguments.
     datasets_module = importlib.import_module("text_recognizer.datasets")
     data_loader_ = getattr(datasets_module, experiment_config["dataloader"])
@@ -21,8 +68,11 @@ def run_experiment(
     models_module = importlib.import_module("text_recognizer.models")
     model_class_ = getattr(models_module, experiment_config["model"])
 
-    # Import metric.
-    metric_fn_ = getattr(models_module, experiment_config["metric"])
+    # Import metrics.
+    metric_fns_ = {
+        metric: getattr(models_module, metric)
+        for metric in experiment_config["metrics"]
+    }
 
     # Import network module and arguments.
     network_module = importlib.import_module("text_recognizer.networks")
@@ -38,38 +88,145 @@ def run_experiment(
     optimizer_args = experiment_config.get("optimizer_args", {})
 
     # Learning rate scheduler
-    lr_scheduler_ = None
-    lr_scheduler_args = None
     if experiment_config["lr_scheduler"] is not None:
         lr_scheduler_ = getattr(
             torch.optim.lr_scheduler, experiment_config["lr_scheduler"]
         )
         lr_scheduler_args = experiment_config.get("lr_scheduler_args", {})
+    else:
+        lr_scheduler_ = None
+        lr_scheduler_args = None
+
+    model_args = {
+        "data_loader": data_loader_,
+        "data_loader_args": data_loader_args,
+        "metrics": metric_fns_,
+        "network_fn": network_fn_,
+        "network_args": network_args,
+        "criterion": criterion_,
+        "criterion_args": criterion_args,
+        "optimizer": optimizer_,
+        "optimizer_args": optimizer_args,
+        "lr_scheduler": lr_scheduler_,
+        "lr_scheduler_args": lr_scheduler_args,
+    }
+
+    return model_class_, model_args
+
+
+def run_experiment(
+    experiment_config: Dict, save_weights: bool, device: str, use_wandb: bool = False
+) -> None:
+    """Runs an experiment."""
+
+    # Load the modules and model arguments.
+    model_class_, model_args = load_modules_and_arguments(experiment_config)
+
+    # Initializes the model with experiment config.
+    model = model_class_(**model_args, device=device)
+
+    # Create new experiment.
+    experiment_dir = create_experiment_dir(model, experiment_config)
+
+    # Create log and model directories.
+    log_dir = experiment_dir / "log"
+    model_dir = experiment_dir / "model"
+
+    # Get checkpoint path.
+    checkpoint_path = model_dir / "last.pt"
+    if not checkpoint_path.exists():
+        checkpoint_path = None
 
-    # Device
-    # TODO fix gpu manager
-    device = None
-
-    model = model_class_(
-        network_fn=network_fn_,
-        network_args=network_args,
-        data_loader=data_loader_,
-        data_loader_args=data_loader_args,
-        metrics=metric_fn_,
-        criterion=criterion_,
-        criterion_args=criterion_args,
-        optimizer=optimizer_,
-        optimizer_args=optimizer_args,
-        lr_scheduler=lr_scheduler_,
-        lr_scheduler_args=lr_scheduler_args,
-        device=device,
+    # Make sure the log directory exists.
+    log_dir.mkdir(parents=True, exist_ok=True)
+
+    # Have to remove default logger to get tqdm to work properly.
+    logger.remove()
+
+    # Fetch verbosity level.
+    level = get_level(experiment_config)
+
+    logger.add(lambda msg: tqdm.write(msg, end=""), colorize=True, level=level)
+    logger.add(
+        str(log_dir / "train.log"),
+        format="{time:YYYY-MM-DD at HH:mm:ss} | {level} | {message}",
     )
 
-    # TODO: Fix checkpoint path and wandb
+    if "cuda" in device:
+        gpu_index = re.sub("[^0-9]+", "", device)
+        logger.info(
+            f"Running experiment with config {experiment_config} on GPU {gpu_index}"
+        )
+    else:
+        logger.info(f"Running experiment with config {experiment_config} on CPU")
+
+    logger.info(f"The class mapping is {model.mapping}")
+
+    # Pŕints a summary of the network in terminal.
+    model.summary()
+
+    experiment_config["train_args"] = {
+        **DEFAULT_TRAIN_ARGS,
+        **experiment_config.get("train_args", {}),
+    }
+
+    experiment_config["experiment_group"] = experiment_config.get(
+        "experiment_group", None
+    )
+
+    experiment_config["device"] = device
+
+    # Save the config used in the experiment folder.
+    config_path = experiment_dir / "config.yml"
+    with open(str(config_path), "w") as f:
+        yaml.dump(experiment_config, f)
+
+    # TODO: wandb
     trainer = Trainer(
         model=model,
-        epochs=experiment_config["epochs"],
-        val_metric=experiment_config["metric"],
+        model_dir=model_dir,
+        epochs=experiment_config["train_args"]["epochs"],
+        val_metric=experiment_config["train_args"]["val_metric"],
+        checkpoint_path=checkpoint_path,
     )
 
     trainer.fit()
+
+    score = trainer.validate()
+
+    logger.info(f"Validation set evaluation: {score}")
+
+    if save_weights:
+        model.save_weights(model_dir)
+
+
+@click.command()
+@click.option(
+    "--experiment_config",
+    type=str,
+    help='Experiment JSON, e.g. \'{"dataloader": "EmnistDataLoader", "model": "CharacterModel", "network": "mlp"}\'',
+)
+@click.option("--gpu", type=int, default=0, help="Provide the index of the GPU to use.")
+@click.option(
+    "--save",
+    is_flag=True,
+    help="If set, the final weights will be saved to a canonical, version-controlled location.",
+)
+@click.option(
+    "--nowandb", is_flag=False, help="If true, do not use wandb for this run."
+)
+def main(experiment_config: str, gpu: int, save: bool, nowandb: bool) -> None:
+    """Run experiment."""
+    if gpu < 0:
+        gpu_manager = GPUManager(True)
+        gpu = gpu_manager.get_free_gpu()
+
+    device = "cuda:" + str(gpu)
+
+    experiment_config = json.loads(experiment_config)
+    os.environ["CUDA_VISIBLE_DEVICES"] = f"{gpu}"
+    run_experiment(experiment_config, save, device, nowandb)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/src/training/train.py b/src/training/train.py
index 4a452b6..8cd5110 100644
--- a/src/training/train.py
+++ b/src/training/train.py
@@ -1,8 +1,8 @@
 """Training script for PyTorch models."""
 
-from datetime import datetime
 from pathlib import Path
-from typing import Callable, Dict, Optional
+import time
+from typing import Dict, Optional, Type
 
 from loguru import logger
 import numpy as np
@@ -11,6 +11,7 @@ from tqdm import tqdm, trange
 from training.util import RunningAverage
 import wandb
 
+from text_recognizer.models import Model
 
 torch.backends.cudnn.benchmark = True
 np.random.seed(4711)
@@ -18,17 +19,16 @@ torch.manual_seed(4711)
 torch.cuda.manual_seed(4711)
 
 
-EXPERIMENTS_DIRNAME = Path(__file__).parents[0].resolve() / "experiments"
-
-
 class Trainer:
     """Trainer for training PyTorch models."""
 
     # TODO implement wandb.
+    # TODO implement Bayesian parameter search.
 
     def __init__(
         self,
-        model: Callable,
+        model: Type[Model],
+        model_dir: Path,
         epochs: int,
         val_metric: str = "accuracy",
         checkpoint_path: Optional[Path] = None,
@@ -37,7 +37,8 @@ class Trainer:
         """Initialization of the Trainer.
 
         Args:
-            model (Callable): A model object.
+            model (Type[Model]): A model object.
+            model_dir (Path): Path to the model directory.
             epochs (int): Number of epochs to train.
             val_metric (str): The validation metric to evaluate the model on. Defaults to "accuracy".
             checkpoint_path (Optional[Path]): The path to a previously trained model. Defaults to None.
@@ -45,6 +46,7 @@ class Trainer:
 
         """
         self.model = model
+        self.model_dir = model_dir
         self.epochs = epochs
         self.checkpoint_path = checkpoint_path
         self.start_epoch = 0
@@ -58,7 +60,10 @@ class Trainer:
 
         self.val_metric = val_metric
         self.best_val_metric = 0.0
-        logger.add(self.model.name + "_{time}.log")
+
+        # Parse the name of the experiment.
+        experiment_dir = str(self.model_dir.parents[1]).split("/")
+        self.experiment_name = experiment_dir[-2] + "/" + experiment_dir[-1]
 
     def train(self) -> None:
         """Training loop."""
@@ -68,13 +73,13 @@ class Trainer:
         # Running average for the loss.
         loss_avg = RunningAverage()
 
-        data_loader = self.model.data_loaders["train"]
+        data_loader = self.model.data_loaders("train")
 
         with tqdm(
             total=len(data_loader),
             leave=False,
             unit="step",
-            bar_format="{n_fmt}/{total_fmt} {bar} {remaining} {rate_inv_fmt}{postfix}",
+            bar_format="{n_fmt}/{total_fmt} |{bar:20}| {remaining} {rate_inv_fmt}{postfix}",
         ) as t:
             for data, targets in data_loader:
 
@@ -85,7 +90,7 @@ class Trainer:
 
                 # Forward pass.
                 # Get the network prediction.
-                output = self.model.predict(data)
+                output = self.model.network(data)
 
                 # Compute the loss.
                 loss = self.model.criterion(output, targets)
@@ -105,16 +110,20 @@ class Trainer:
                 output = output.data.cpu()
                 targets = targets.data.cpu()
                 metrics = {
-                    metric: round(self.model.metrics[metric](output, targets), 4)
+                    metric: self.model.metrics[metric](output, targets)
                     for metric in self.model.metrics
                 }
-                metrics["loss"] = round(loss_avg(), 4)
+                metrics["loss"] = loss_avg()
 
                 # Update Tqdm progress bar.
                 t.set_postfix(**metrics)
                 t.update()
 
-    def evaluate(self) -> Dict:
+                # If the model has a learning rate scheduler, compute a step.
+                if self.model.lr_scheduler is not None:
+                    self.model.lr_scheduler.step()
+
+    def validate(self) -> Dict:
         """Evaluation loop.
 
         Returns:
@@ -125,7 +134,7 @@ class Trainer:
         self.model.eval()
 
         # Running average for the loss.
-        data_loader = self.model.data_loaders["val"]
+        data_loader = self.model.data_loaders("val")
 
         # Running average for the loss.
         loss_avg = RunningAverage()
@@ -137,7 +146,7 @@ class Trainer:
             total=len(data_loader),
             leave=False,
             unit="step",
-            bar_format="{n_fmt}/{total_fmt} {bar} {remaining} {rate_inv_fmt}{postfix}",
+            bar_format="{n_fmt}/{total_fmt} |{bar:20}| {remaining} {rate_inv_fmt}{postfix}",
         ) as t:
             for data, targets in data_loader:
                 data, targets = (
@@ -145,22 +154,23 @@ class Trainer:
                     targets.to(self.model.device),
                 )
 
-                # Forward pass.
-                # Get the network prediction.
-                output = self.model.predict(data)
+                with torch.no_grad():
+                    # Forward pass.
+                    # Get the network prediction.
+                    output = self.model.network(data)
 
-                # Compute the loss.
-                loss = self.model.criterion(output, targets)
+                    # Compute the loss.
+                    loss = self.model.criterion(output, targets)
 
                 # Compute metrics.
                 loss_avg.update(loss.item())
                 output = output.data.cpu()
                 targets = targets.data.cpu()
                 metrics = {
-                    metric: round(self.model.metrics[metric](output, targets), 4)
+                    metric: self.model.metrics[metric](output, targets)
                     for metric in self.model.metrics
                 }
-                metrics["loss"] = round(loss.item(), 4)
+                metrics["loss"] = loss.item()
 
                 summary.append(metrics)
 
@@ -170,7 +180,7 @@ class Trainer:
 
         # Compute mean of all metrics.
         metrics_mean = {
-            metric: np.mean(x[metric] for x in summary) for metric in summary[0]
+            metric: np.mean([x[metric] for x in summary]) for metric in summary[0]
         }
         metrics_str = " - ".join(f"{k}: {v}" for k, v in metrics_mean.items())
         logger.debug(metrics_str)
@@ -179,55 +189,34 @@ class Trainer:
 
     def fit(self) -> None:
         """Runs the training and evaluation loop."""
-        # Create new experiment.
-        EXPERIMENTS_DIRNAME.mkdir(parents=True, exist_ok=True)
-        experiment = datetime.now().strftime("%m%d_%H%M%S")
-        experiment_dir = EXPERIMENTS_DIRNAME / self.model.network.__name__ / experiment
-
-        # Create log and model directories.
-        log_dir = experiment_dir / "log"
-        model_dir = experiment_dir / "model"
-
-        # Make sure the log directory exists.
-        log_dir.mkdir(parents=True, exist_ok=True)
-
-        logger.add(
-            str(log_dir / "train.log"),
-            format="{time:YYYY-MM-DD at HH:mm:ss} | {level} | {message}",
-        )
-
-        logger.debug(
-            f"Running an experiment called {self.model.network.__name__}/{experiment}."
-        )
-
-        # Pŕints a summary of the network in terminal.
-        self.model.summary()
 
+        logger.debug(f"Running an experiment called {self.experiment_name}.")
+        t_start = time.time()
         # Run the training loop.
         for epoch in trange(
-            total=self.epochs,
+            self.epochs,
             initial=self.start_epoch,
-            leave=True,
-            bar_format="{desc}: {n_fmt}/{total_fmt} {bar} {remaining}{postfix}",
+            leave=False,
+            bar_format="{desc}: {n_fmt}/{total_fmt} |{bar:10}| {remaining}{postfix}",
             desc="Epoch",
         ):
             # Perform one training pass over the training set.
             self.train()
 
             # Evaluate the model on the validation set.
-            val_metrics = self.evaluate()
-
-            # If the model has a learning rate scheduler, compute a step.
-            if self.model.lr_scheduler is not None:
-                self.model.lr_scheduler.step()
+            val_metrics = self.validate()
 
             # The validation metric to evaluate the model on, e.g. accuracy.
             val_metric = val_metrics[self.val_metric]
             is_best = val_metric >= self.best_val_metric
-
+            self.best_val_metric = val_metric if is_best else self.best_val_metric
             # Save checkpoint.
-            self.model.save_checkpoint(model_dir, is_best, epoch, self.val_metric)
+            self.model.save_checkpoint(self.model_dir, is_best, epoch, self.val_metric)
 
             if self.start_epoch > 0 and epoch + self.start_epoch == self.epochs:
                 logger.debug(f"Trained the model for {self.epochs} number of epochs.")
                 break
+
+        t_end = time.time()
+        t_training = t_end - t_start
+        logger.info(f"Training took {t_training:.2f} s.")