diff --git a/resnet152-cifar10-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/README.md b/resnet152-cifar10-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..afba28d75df9b02d0824ece4a4c7e89257137943
--- /dev/null
+++ b/resnet152-cifar10-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: cifar10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: train
+type: transformers
+val_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: test
+```
+
diff --git a/resnet152-cifar10-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/config.json b/resnet152-cifar10-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..fae9a9cc3053b5936d45ecae91b1a2edabf051ba
--- /dev/null
+++ b/resnet152-cifar10-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "automobile",
+    "2": "bird",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "frog",
+    "7": "horse",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "automobile": 1,
+    "bird": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "frog": 6,
+    "horse": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-cifar10-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet152-cifar10-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-cifar10-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-cifar10-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet152-cifar10-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-cifar10-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-cifar10-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/README.md b/resnet152-cifar10-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..72bfaf0c9130293671dad3e4879026607b340bb2
--- /dev/null
+++ b/resnet152-cifar10-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: cifar10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: train
+type: transformers
+val_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: test
+```
+
diff --git a/resnet152-cifar10-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/config.json b/resnet152-cifar10-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..fae9a9cc3053b5936d45ecae91b1a2edabf051ba
--- /dev/null
+++ b/resnet152-cifar10-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "automobile",
+    "2": "bird",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "frog",
+    "7": "horse",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "automobile": 1,
+    "bird": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "frog": 6,
+    "horse": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-cifar10-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet152-cifar10-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-cifar10-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-cifar10-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/README.md b/resnet152-cifar10-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..3f30e412d5373cd6fba6ff973d053cff9e756bf1
--- /dev/null
+++ b/resnet152-cifar10-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: cifar10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: train
+type: transformers
+val_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: test
+```
+
diff --git a/resnet152-cifar10-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/config.json b/resnet152-cifar10-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..fae9a9cc3053b5936d45ecae91b1a2edabf051ba
--- /dev/null
+++ b/resnet152-cifar10-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "automobile",
+    "2": "bird",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "frog",
+    "7": "horse",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "automobile": 1,
+    "bird": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "frog": 6,
+    "horse": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-cifar10-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet152-cifar10-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-cifar10-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-cifar10-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/README.md b/resnet152-cifar10-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..2b27ca3ebe70356c8958d847755158dfd02b0d7a
--- /dev/null
+++ b/resnet152-cifar10-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: cifar10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: train
+type: transformers
+val_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: test
+```
+
diff --git a/resnet152-cifar10-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/config.json b/resnet152-cifar10-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..fae9a9cc3053b5936d45ecae91b1a2edabf051ba
--- /dev/null
+++ b/resnet152-cifar10-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "automobile",
+    "2": "bird",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "frog",
+    "7": "horse",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "automobile": 1,
+    "bird": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "frog": 6,
+    "horse": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-cifar10-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet152-cifar10-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-cifar10-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-cifar100-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md b/resnet152-cifar100-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..52dfe61e4052d13be61b6230ac6fa524df676826
--- /dev/null
+++ b/resnet152-cifar100-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar100.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: cifar100
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: train
+type: transformers
+val_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: test
+```
+
diff --git a/resnet152-cifar100-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/config.json b/resnet152-cifar100-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..acbad7473b8e84235773c84b96dc29cdb56af499
--- /dev/null
+++ b/resnet152-cifar100-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,243 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "apple",
+    "1": "aquarium_fish",
+    "2": "baby",
+    "3": "bear",
+    "4": "beaver",
+    "5": "bed",
+    "6": "bee",
+    "7": "beetle",
+    "8": "bicycle",
+    "9": "bottle",
+    "10": "bowl",
+    "11": "boy",
+    "12": "bridge",
+    "13": "bus",
+    "14": "butterfly",
+    "15": "camel",
+    "16": "can",
+    "17": "castle",
+    "18": "caterpillar",
+    "19": "cattle",
+    "20": "chair",
+    "21": "chimpanzee",
+    "22": "clock",
+    "23": "cloud",
+    "24": "cockroach",
+    "25": "couch",
+    "26": "cra",
+    "27": "crocodile",
+    "28": "cup",
+    "29": "dinosaur",
+    "30": "dolphin",
+    "31": "elephant",
+    "32": "flatfish",
+    "33": "forest",
+    "34": "fox",
+    "35": "girl",
+    "36": "hamster",
+    "37": "house",
+    "38": "kangaroo",
+    "39": "keyboard",
+    "40": "lamp",
+    "41": "lawn_mower",
+    "42": "leopard",
+    "43": "lion",
+    "44": "lizard",
+    "45": "lobster",
+    "46": "man",
+    "47": "maple_tree",
+    "48": "motorcycle",
+    "49": "mountain",
+    "50": "mouse",
+    "51": "mushroom",
+    "52": "oak_tree",
+    "53": "orange",
+    "54": "orchid",
+    "55": "otter",
+    "56": "palm_tree",
+    "57": "pear",
+    "58": "pickup_truck",
+    "59": "pine_tree",
+    "60": "plain",
+    "61": "plate",
+    "62": "poppy",
+    "63": "porcupine",
+    "64": "possum",
+    "65": "rabbit",
+    "66": "raccoon",
+    "67": "ray",
+    "68": "road",
+    "69": "rocket",
+    "70": "rose",
+    "71": "sea",
+    "72": "seal",
+    "73": "shark",
+    "74": "shrew",
+    "75": "skunk",
+    "76": "skyscraper",
+    "77": "snail",
+    "78": "snake",
+    "79": "spider",
+    "80": "squirrel",
+    "81": "streetcar",
+    "82": "sunflower",
+    "83": "sweet_pepper",
+    "84": "table",
+    "85": "tank",
+    "86": "telephone",
+    "87": "television",
+    "88": "tiger",
+    "89": "tractor",
+    "90": "train",
+    "91": "trout",
+    "92": "tulip",
+    "93": "turtle",
+    "94": "wardrobe",
+    "95": "whale",
+    "96": "willow_tree",
+    "97": "wolf",
+    "98": "woman",
+    "99": "worm"
+  },
+  "label2id": {
+    "apple": 0,
+    "aquarium_fish": 1,
+    "baby": 2,
+    "bear": 3,
+    "beaver": 4,
+    "bed": 5,
+    "bee": 6,
+    "beetle": 7,
+    "bicycle": 8,
+    "bottle": 9,
+    "bowl": 10,
+    "boy": 11,
+    "bridge": 12,
+    "bus": 13,
+    "butterfly": 14,
+    "camel": 15,
+    "can": 16,
+    "castle": 17,
+    "caterpillar": 18,
+    "cattle": 19,
+    "chair": 20,
+    "chimpanzee": 21,
+    "clock": 22,
+    "cloud": 23,
+    "cockroach": 24,
+    "couch": 25,
+    "cra": 26,
+    "crocodile": 27,
+    "cup": 28,
+    "dinosaur": 29,
+    "dolphin": 30,
+    "elephant": 31,
+    "flatfish": 32,
+    "forest": 33,
+    "fox": 34,
+    "girl": 35,
+    "hamster": 36,
+    "house": 37,
+    "kangaroo": 38,
+    "keyboard": 39,
+    "lamp": 40,
+    "lawn_mower": 41,
+    "leopard": 42,
+    "lion": 43,
+    "lizard": 44,
+    "lobster": 45,
+    "man": 46,
+    "maple_tree": 47,
+    "motorcycle": 48,
+    "mountain": 49,
+    "mouse": 50,
+    "mushroom": 51,
+    "oak_tree": 52,
+    "orange": 53,
+    "orchid": 54,
+    "otter": 55,
+    "palm_tree": 56,
+    "pear": 57,
+    "pickup_truck": 58,
+    "pine_tree": 59,
+    "plain": 60,
+    "plate": 61,
+    "poppy": 62,
+    "porcupine": 63,
+    "possum": 64,
+    "rabbit": 65,
+    "raccoon": 66,
+    "ray": 67,
+    "road": 68,
+    "rocket": 69,
+    "rose": 70,
+    "sea": 71,
+    "seal": 72,
+    "shark": 73,
+    "shrew": 74,
+    "skunk": 75,
+    "skyscraper": 76,
+    "snail": 77,
+    "snake": 78,
+    "spider": 79,
+    "squirrel": 80,
+    "streetcar": 81,
+    "sunflower": 82,
+    "sweet_pepper": 83,
+    "table": 84,
+    "tank": 85,
+    "telephone": 86,
+    "television": 87,
+    "tiger": 88,
+    "tractor": 89,
+    "train": 90,
+    "trout": 91,
+    "tulip": 92,
+    "turtle": 93,
+    "wardrobe": 94,
+    "whale": 95,
+    "willow_tree": 96,
+    "wolf": 97,
+    "woman": 98,
+    "worm": 99
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-cifar100-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet152-cifar100-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-cifar100-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-cifar100-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/README.md b/resnet152-cifar100-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..95bb009d63293662d48aae533d3937db4bd93a48
--- /dev/null
+++ b/resnet152-cifar100-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar100.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: cifar100
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: train
+type: transformers
+val_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: test
+```
+
diff --git a/resnet152-cifar100-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/config.json b/resnet152-cifar100-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..acbad7473b8e84235773c84b96dc29cdb56af499
--- /dev/null
+++ b/resnet152-cifar100-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,243 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "apple",
+    "1": "aquarium_fish",
+    "2": "baby",
+    "3": "bear",
+    "4": "beaver",
+    "5": "bed",
+    "6": "bee",
+    "7": "beetle",
+    "8": "bicycle",
+    "9": "bottle",
+    "10": "bowl",
+    "11": "boy",
+    "12": "bridge",
+    "13": "bus",
+    "14": "butterfly",
+    "15": "camel",
+    "16": "can",
+    "17": "castle",
+    "18": "caterpillar",
+    "19": "cattle",
+    "20": "chair",
+    "21": "chimpanzee",
+    "22": "clock",
+    "23": "cloud",
+    "24": "cockroach",
+    "25": "couch",
+    "26": "cra",
+    "27": "crocodile",
+    "28": "cup",
+    "29": "dinosaur",
+    "30": "dolphin",
+    "31": "elephant",
+    "32": "flatfish",
+    "33": "forest",
+    "34": "fox",
+    "35": "girl",
+    "36": "hamster",
+    "37": "house",
+    "38": "kangaroo",
+    "39": "keyboard",
+    "40": "lamp",
+    "41": "lawn_mower",
+    "42": "leopard",
+    "43": "lion",
+    "44": "lizard",
+    "45": "lobster",
+    "46": "man",
+    "47": "maple_tree",
+    "48": "motorcycle",
+    "49": "mountain",
+    "50": "mouse",
+    "51": "mushroom",
+    "52": "oak_tree",
+    "53": "orange",
+    "54": "orchid",
+    "55": "otter",
+    "56": "palm_tree",
+    "57": "pear",
+    "58": "pickup_truck",
+    "59": "pine_tree",
+    "60": "plain",
+    "61": "plate",
+    "62": "poppy",
+    "63": "porcupine",
+    "64": "possum",
+    "65": "rabbit",
+    "66": "raccoon",
+    "67": "ray",
+    "68": "road",
+    "69": "rocket",
+    "70": "rose",
+    "71": "sea",
+    "72": "seal",
+    "73": "shark",
+    "74": "shrew",
+    "75": "skunk",
+    "76": "skyscraper",
+    "77": "snail",
+    "78": "snake",
+    "79": "spider",
+    "80": "squirrel",
+    "81": "streetcar",
+    "82": "sunflower",
+    "83": "sweet_pepper",
+    "84": "table",
+    "85": "tank",
+    "86": "telephone",
+    "87": "television",
+    "88": "tiger",
+    "89": "tractor",
+    "90": "train",
+    "91": "trout",
+    "92": "tulip",
+    "93": "turtle",
+    "94": "wardrobe",
+    "95": "whale",
+    "96": "willow_tree",
+    "97": "wolf",
+    "98": "woman",
+    "99": "worm"
+  },
+  "label2id": {
+    "apple": 0,
+    "aquarium_fish": 1,
+    "baby": 2,
+    "bear": 3,
+    "beaver": 4,
+    "bed": 5,
+    "bee": 6,
+    "beetle": 7,
+    "bicycle": 8,
+    "bottle": 9,
+    "bowl": 10,
+    "boy": 11,
+    "bridge": 12,
+    "bus": 13,
+    "butterfly": 14,
+    "camel": 15,
+    "can": 16,
+    "castle": 17,
+    "caterpillar": 18,
+    "cattle": 19,
+    "chair": 20,
+    "chimpanzee": 21,
+    "clock": 22,
+    "cloud": 23,
+    "cockroach": 24,
+    "couch": 25,
+    "cra": 26,
+    "crocodile": 27,
+    "cup": 28,
+    "dinosaur": 29,
+    "dolphin": 30,
+    "elephant": 31,
+    "flatfish": 32,
+    "forest": 33,
+    "fox": 34,
+    "girl": 35,
+    "hamster": 36,
+    "house": 37,
+    "kangaroo": 38,
+    "keyboard": 39,
+    "lamp": 40,
+    "lawn_mower": 41,
+    "leopard": 42,
+    "lion": 43,
+    "lizard": 44,
+    "lobster": 45,
+    "man": 46,
+    "maple_tree": 47,
+    "motorcycle": 48,
+    "mountain": 49,
+    "mouse": 50,
+    "mushroom": 51,
+    "oak_tree": 52,
+    "orange": 53,
+    "orchid": 54,
+    "otter": 55,
+    "palm_tree": 56,
+    "pear": 57,
+    "pickup_truck": 58,
+    "pine_tree": 59,
+    "plain": 60,
+    "plate": 61,
+    "poppy": 62,
+    "porcupine": 63,
+    "possum": 64,
+    "rabbit": 65,
+    "raccoon": 66,
+    "ray": 67,
+    "road": 68,
+    "rocket": 69,
+    "rose": 70,
+    "sea": 71,
+    "seal": 72,
+    "shark": 73,
+    "shrew": 74,
+    "skunk": 75,
+    "skyscraper": 76,
+    "snail": 77,
+    "snake": 78,
+    "spider": 79,
+    "squirrel": 80,
+    "streetcar": 81,
+    "sunflower": 82,
+    "sweet_pepper": 83,
+    "table": 84,
+    "tank": 85,
+    "telephone": 86,
+    "television": 87,
+    "tiger": 88,
+    "tractor": 89,
+    "train": 90,
+    "trout": 91,
+    "tulip": 92,
+    "turtle": 93,
+    "wardrobe": 94,
+    "whale": 95,
+    "willow_tree": 96,
+    "wolf": 97,
+    "woman": 98,
+    "worm": 99
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-cifar100-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet152-cifar100-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-cifar100-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-cifar100-batch_size_256_lr_0.001_training_data_ratio_0.8-1000/README.md b/resnet152-cifar100-batch_size_256_lr_0.001_training_data_ratio_0.8-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..aae24de56a9d81df8d9be1064f16500909343c6a
--- /dev/null
+++ b/resnet152-cifar100-batch_size_256_lr_0.001_training_data_ratio_0.8-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar100.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: cifar100
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: train
+type: transformers
+val_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: test
+```
+
diff --git a/resnet152-cifar100-batch_size_256_lr_0.001_training_data_ratio_0.8-1000/config.json b/resnet152-cifar100-batch_size_256_lr_0.001_training_data_ratio_0.8-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..acbad7473b8e84235773c84b96dc29cdb56af499
--- /dev/null
+++ b/resnet152-cifar100-batch_size_256_lr_0.001_training_data_ratio_0.8-1000/config.json
@@ -0,0 +1,243 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "apple",
+    "1": "aquarium_fish",
+    "2": "baby",
+    "3": "bear",
+    "4": "beaver",
+    "5": "bed",
+    "6": "bee",
+    "7": "beetle",
+    "8": "bicycle",
+    "9": "bottle",
+    "10": "bowl",
+    "11": "boy",
+    "12": "bridge",
+    "13": "bus",
+    "14": "butterfly",
+    "15": "camel",
+    "16": "can",
+    "17": "castle",
+    "18": "caterpillar",
+    "19": "cattle",
+    "20": "chair",
+    "21": "chimpanzee",
+    "22": "clock",
+    "23": "cloud",
+    "24": "cockroach",
+    "25": "couch",
+    "26": "cra",
+    "27": "crocodile",
+    "28": "cup",
+    "29": "dinosaur",
+    "30": "dolphin",
+    "31": "elephant",
+    "32": "flatfish",
+    "33": "forest",
+    "34": "fox",
+    "35": "girl",
+    "36": "hamster",
+    "37": "house",
+    "38": "kangaroo",
+    "39": "keyboard",
+    "40": "lamp",
+    "41": "lawn_mower",
+    "42": "leopard",
+    "43": "lion",
+    "44": "lizard",
+    "45": "lobster",
+    "46": "man",
+    "47": "maple_tree",
+    "48": "motorcycle",
+    "49": "mountain",
+    "50": "mouse",
+    "51": "mushroom",
+    "52": "oak_tree",
+    "53": "orange",
+    "54": "orchid",
+    "55": "otter",
+    "56": "palm_tree",
+    "57": "pear",
+    "58": "pickup_truck",
+    "59": "pine_tree",
+    "60": "plain",
+    "61": "plate",
+    "62": "poppy",
+    "63": "porcupine",
+    "64": "possum",
+    "65": "rabbit",
+    "66": "raccoon",
+    "67": "ray",
+    "68": "road",
+    "69": "rocket",
+    "70": "rose",
+    "71": "sea",
+    "72": "seal",
+    "73": "shark",
+    "74": "shrew",
+    "75": "skunk",
+    "76": "skyscraper",
+    "77": "snail",
+    "78": "snake",
+    "79": "spider",
+    "80": "squirrel",
+    "81": "streetcar",
+    "82": "sunflower",
+    "83": "sweet_pepper",
+    "84": "table",
+    "85": "tank",
+    "86": "telephone",
+    "87": "television",
+    "88": "tiger",
+    "89": "tractor",
+    "90": "train",
+    "91": "trout",
+    "92": "tulip",
+    "93": "turtle",
+    "94": "wardrobe",
+    "95": "whale",
+    "96": "willow_tree",
+    "97": "wolf",
+    "98": "woman",
+    "99": "worm"
+  },
+  "label2id": {
+    "apple": 0,
+    "aquarium_fish": 1,
+    "baby": 2,
+    "bear": 3,
+    "beaver": 4,
+    "bed": 5,
+    "bee": 6,
+    "beetle": 7,
+    "bicycle": 8,
+    "bottle": 9,
+    "bowl": 10,
+    "boy": 11,
+    "bridge": 12,
+    "bus": 13,
+    "butterfly": 14,
+    "camel": 15,
+    "can": 16,
+    "castle": 17,
+    "caterpillar": 18,
+    "cattle": 19,
+    "chair": 20,
+    "chimpanzee": 21,
+    "clock": 22,
+    "cloud": 23,
+    "cockroach": 24,
+    "couch": 25,
+    "cra": 26,
+    "crocodile": 27,
+    "cup": 28,
+    "dinosaur": 29,
+    "dolphin": 30,
+    "elephant": 31,
+    "flatfish": 32,
+    "forest": 33,
+    "fox": 34,
+    "girl": 35,
+    "hamster": 36,
+    "house": 37,
+    "kangaroo": 38,
+    "keyboard": 39,
+    "lamp": 40,
+    "lawn_mower": 41,
+    "leopard": 42,
+    "lion": 43,
+    "lizard": 44,
+    "lobster": 45,
+    "man": 46,
+    "maple_tree": 47,
+    "motorcycle": 48,
+    "mountain": 49,
+    "mouse": 50,
+    "mushroom": 51,
+    "oak_tree": 52,
+    "orange": 53,
+    "orchid": 54,
+    "otter": 55,
+    "palm_tree": 56,
+    "pear": 57,
+    "pickup_truck": 58,
+    "pine_tree": 59,
+    "plain": 60,
+    "plate": 61,
+    "poppy": 62,
+    "porcupine": 63,
+    "possum": 64,
+    "rabbit": 65,
+    "raccoon": 66,
+    "ray": 67,
+    "road": 68,
+    "rocket": 69,
+    "rose": 70,
+    "sea": 71,
+    "seal": 72,
+    "shark": 73,
+    "shrew": 74,
+    "skunk": 75,
+    "skyscraper": 76,
+    "snail": 77,
+    "snake": 78,
+    "spider": 79,
+    "squirrel": 80,
+    "streetcar": 81,
+    "sunflower": 82,
+    "sweet_pepper": 83,
+    "table": 84,
+    "tank": 85,
+    "telephone": 86,
+    "television": 87,
+    "tiger": 88,
+    "tractor": 89,
+    "train": 90,
+    "trout": 91,
+    "tulip": 92,
+    "turtle": 93,
+    "wardrobe": 94,
+    "whale": 95,
+    "willow_tree": 96,
+    "wolf": 97,
+    "woman": 98,
+    "worm": 99
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-cifar100-batch_size_256_lr_0.001_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet152-cifar100-batch_size_256_lr_0.001_training_data_ratio_0.8-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-cifar100-batch_size_256_lr_0.001_training_data_ratio_0.8-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-cifar100-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/README.md b/resnet152-cifar100-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..aae24de56a9d81df8d9be1064f16500909343c6a
--- /dev/null
+++ b/resnet152-cifar100-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar100.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: cifar100
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: train
+type: transformers
+val_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: test
+```
+
diff --git a/resnet152-cifar100-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/config.json b/resnet152-cifar100-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..acbad7473b8e84235773c84b96dc29cdb56af499
--- /dev/null
+++ b/resnet152-cifar100-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,243 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "apple",
+    "1": "aquarium_fish",
+    "2": "baby",
+    "3": "bear",
+    "4": "beaver",
+    "5": "bed",
+    "6": "bee",
+    "7": "beetle",
+    "8": "bicycle",
+    "9": "bottle",
+    "10": "bowl",
+    "11": "boy",
+    "12": "bridge",
+    "13": "bus",
+    "14": "butterfly",
+    "15": "camel",
+    "16": "can",
+    "17": "castle",
+    "18": "caterpillar",
+    "19": "cattle",
+    "20": "chair",
+    "21": "chimpanzee",
+    "22": "clock",
+    "23": "cloud",
+    "24": "cockroach",
+    "25": "couch",
+    "26": "cra",
+    "27": "crocodile",
+    "28": "cup",
+    "29": "dinosaur",
+    "30": "dolphin",
+    "31": "elephant",
+    "32": "flatfish",
+    "33": "forest",
+    "34": "fox",
+    "35": "girl",
+    "36": "hamster",
+    "37": "house",
+    "38": "kangaroo",
+    "39": "keyboard",
+    "40": "lamp",
+    "41": "lawn_mower",
+    "42": "leopard",
+    "43": "lion",
+    "44": "lizard",
+    "45": "lobster",
+    "46": "man",
+    "47": "maple_tree",
+    "48": "motorcycle",
+    "49": "mountain",
+    "50": "mouse",
+    "51": "mushroom",
+    "52": "oak_tree",
+    "53": "orange",
+    "54": "orchid",
+    "55": "otter",
+    "56": "palm_tree",
+    "57": "pear",
+    "58": "pickup_truck",
+    "59": "pine_tree",
+    "60": "plain",
+    "61": "plate",
+    "62": "poppy",
+    "63": "porcupine",
+    "64": "possum",
+    "65": "rabbit",
+    "66": "raccoon",
+    "67": "ray",
+    "68": "road",
+    "69": "rocket",
+    "70": "rose",
+    "71": "sea",
+    "72": "seal",
+    "73": "shark",
+    "74": "shrew",
+    "75": "skunk",
+    "76": "skyscraper",
+    "77": "snail",
+    "78": "snake",
+    "79": "spider",
+    "80": "squirrel",
+    "81": "streetcar",
+    "82": "sunflower",
+    "83": "sweet_pepper",
+    "84": "table",
+    "85": "tank",
+    "86": "telephone",
+    "87": "television",
+    "88": "tiger",
+    "89": "tractor",
+    "90": "train",
+    "91": "trout",
+    "92": "tulip",
+    "93": "turtle",
+    "94": "wardrobe",
+    "95": "whale",
+    "96": "willow_tree",
+    "97": "wolf",
+    "98": "woman",
+    "99": "worm"
+  },
+  "label2id": {
+    "apple": 0,
+    "aquarium_fish": 1,
+    "baby": 2,
+    "bear": 3,
+    "beaver": 4,
+    "bed": 5,
+    "bee": 6,
+    "beetle": 7,
+    "bicycle": 8,
+    "bottle": 9,
+    "bowl": 10,
+    "boy": 11,
+    "bridge": 12,
+    "bus": 13,
+    "butterfly": 14,
+    "camel": 15,
+    "can": 16,
+    "castle": 17,
+    "caterpillar": 18,
+    "cattle": 19,
+    "chair": 20,
+    "chimpanzee": 21,
+    "clock": 22,
+    "cloud": 23,
+    "cockroach": 24,
+    "couch": 25,
+    "cra": 26,
+    "crocodile": 27,
+    "cup": 28,
+    "dinosaur": 29,
+    "dolphin": 30,
+    "elephant": 31,
+    "flatfish": 32,
+    "forest": 33,
+    "fox": 34,
+    "girl": 35,
+    "hamster": 36,
+    "house": 37,
+    "kangaroo": 38,
+    "keyboard": 39,
+    "lamp": 40,
+    "lawn_mower": 41,
+    "leopard": 42,
+    "lion": 43,
+    "lizard": 44,
+    "lobster": 45,
+    "man": 46,
+    "maple_tree": 47,
+    "motorcycle": 48,
+    "mountain": 49,
+    "mouse": 50,
+    "mushroom": 51,
+    "oak_tree": 52,
+    "orange": 53,
+    "orchid": 54,
+    "otter": 55,
+    "palm_tree": 56,
+    "pear": 57,
+    "pickup_truck": 58,
+    "pine_tree": 59,
+    "plain": 60,
+    "plate": 61,
+    "poppy": 62,
+    "porcupine": 63,
+    "possum": 64,
+    "rabbit": 65,
+    "raccoon": 66,
+    "ray": 67,
+    "road": 68,
+    "rocket": 69,
+    "rose": 70,
+    "sea": 71,
+    "seal": 72,
+    "shark": 73,
+    "shrew": 74,
+    "skunk": 75,
+    "skyscraper": 76,
+    "snail": 77,
+    "snake": 78,
+    "spider": 79,
+    "squirrel": 80,
+    "streetcar": 81,
+    "sunflower": 82,
+    "sweet_pepper": 83,
+    "table": 84,
+    "tank": 85,
+    "telephone": 86,
+    "television": 87,
+    "tiger": 88,
+    "tractor": 89,
+    "train": 90,
+    "trout": 91,
+    "tulip": 92,
+    "turtle": 93,
+    "wardrobe": 94,
+    "whale": 95,
+    "willow_tree": 96,
+    "wolf": 97,
+    "woman": 98,
+    "worm": 99
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-cifar100-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet152-cifar100-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-cifar100-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-cifar100-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/README.md b/resnet152-cifar100-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..dd6b6f8af65dde4b39ee5feadb337bed4751356f
--- /dev/null
+++ b/resnet152-cifar100-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar100.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: cifar100
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: train
+type: transformers
+val_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: test
+```
+
diff --git a/resnet152-cifar100-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/config.json b/resnet152-cifar100-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..acbad7473b8e84235773c84b96dc29cdb56af499
--- /dev/null
+++ b/resnet152-cifar100-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/config.json
@@ -0,0 +1,243 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "apple",
+    "1": "aquarium_fish",
+    "2": "baby",
+    "3": "bear",
+    "4": "beaver",
+    "5": "bed",
+    "6": "bee",
+    "7": "beetle",
+    "8": "bicycle",
+    "9": "bottle",
+    "10": "bowl",
+    "11": "boy",
+    "12": "bridge",
+    "13": "bus",
+    "14": "butterfly",
+    "15": "camel",
+    "16": "can",
+    "17": "castle",
+    "18": "caterpillar",
+    "19": "cattle",
+    "20": "chair",
+    "21": "chimpanzee",
+    "22": "clock",
+    "23": "cloud",
+    "24": "cockroach",
+    "25": "couch",
+    "26": "cra",
+    "27": "crocodile",
+    "28": "cup",
+    "29": "dinosaur",
+    "30": "dolphin",
+    "31": "elephant",
+    "32": "flatfish",
+    "33": "forest",
+    "34": "fox",
+    "35": "girl",
+    "36": "hamster",
+    "37": "house",
+    "38": "kangaroo",
+    "39": "keyboard",
+    "40": "lamp",
+    "41": "lawn_mower",
+    "42": "leopard",
+    "43": "lion",
+    "44": "lizard",
+    "45": "lobster",
+    "46": "man",
+    "47": "maple_tree",
+    "48": "motorcycle",
+    "49": "mountain",
+    "50": "mouse",
+    "51": "mushroom",
+    "52": "oak_tree",
+    "53": "orange",
+    "54": "orchid",
+    "55": "otter",
+    "56": "palm_tree",
+    "57": "pear",
+    "58": "pickup_truck",
+    "59": "pine_tree",
+    "60": "plain",
+    "61": "plate",
+    "62": "poppy",
+    "63": "porcupine",
+    "64": "possum",
+    "65": "rabbit",
+    "66": "raccoon",
+    "67": "ray",
+    "68": "road",
+    "69": "rocket",
+    "70": "rose",
+    "71": "sea",
+    "72": "seal",
+    "73": "shark",
+    "74": "shrew",
+    "75": "skunk",
+    "76": "skyscraper",
+    "77": "snail",
+    "78": "snake",
+    "79": "spider",
+    "80": "squirrel",
+    "81": "streetcar",
+    "82": "sunflower",
+    "83": "sweet_pepper",
+    "84": "table",
+    "85": "tank",
+    "86": "telephone",
+    "87": "television",
+    "88": "tiger",
+    "89": "tractor",
+    "90": "train",
+    "91": "trout",
+    "92": "tulip",
+    "93": "turtle",
+    "94": "wardrobe",
+    "95": "whale",
+    "96": "willow_tree",
+    "97": "wolf",
+    "98": "woman",
+    "99": "worm"
+  },
+  "label2id": {
+    "apple": 0,
+    "aquarium_fish": 1,
+    "baby": 2,
+    "bear": 3,
+    "beaver": 4,
+    "bed": 5,
+    "bee": 6,
+    "beetle": 7,
+    "bicycle": 8,
+    "bottle": 9,
+    "bowl": 10,
+    "boy": 11,
+    "bridge": 12,
+    "bus": 13,
+    "butterfly": 14,
+    "camel": 15,
+    "can": 16,
+    "castle": 17,
+    "caterpillar": 18,
+    "cattle": 19,
+    "chair": 20,
+    "chimpanzee": 21,
+    "clock": 22,
+    "cloud": 23,
+    "cockroach": 24,
+    "couch": 25,
+    "cra": 26,
+    "crocodile": 27,
+    "cup": 28,
+    "dinosaur": 29,
+    "dolphin": 30,
+    "elephant": 31,
+    "flatfish": 32,
+    "forest": 33,
+    "fox": 34,
+    "girl": 35,
+    "hamster": 36,
+    "house": 37,
+    "kangaroo": 38,
+    "keyboard": 39,
+    "lamp": 40,
+    "lawn_mower": 41,
+    "leopard": 42,
+    "lion": 43,
+    "lizard": 44,
+    "lobster": 45,
+    "man": 46,
+    "maple_tree": 47,
+    "motorcycle": 48,
+    "mountain": 49,
+    "mouse": 50,
+    "mushroom": 51,
+    "oak_tree": 52,
+    "orange": 53,
+    "orchid": 54,
+    "otter": 55,
+    "palm_tree": 56,
+    "pear": 57,
+    "pickup_truck": 58,
+    "pine_tree": 59,
+    "plain": 60,
+    "plate": 61,
+    "poppy": 62,
+    "porcupine": 63,
+    "possum": 64,
+    "rabbit": 65,
+    "raccoon": 66,
+    "ray": 67,
+    "road": 68,
+    "rocket": 69,
+    "rose": 70,
+    "sea": 71,
+    "seal": 72,
+    "shark": 73,
+    "shrew": 74,
+    "skunk": 75,
+    "skyscraper": 76,
+    "snail": 77,
+    "snake": 78,
+    "spider": 79,
+    "squirrel": 80,
+    "streetcar": 81,
+    "sunflower": 82,
+    "sweet_pepper": 83,
+    "table": 84,
+    "tank": 85,
+    "telephone": 86,
+    "television": 87,
+    "tiger": 88,
+    "tractor": 89,
+    "train": 90,
+    "trout": 91,
+    "tulip": 92,
+    "turtle": 93,
+    "wardrobe": 94,
+    "whale": 95,
+    "willow_tree": 96,
+    "wolf": 97,
+    "woman": 98,
+    "worm": 99
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-cifar100-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet152-cifar100-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-cifar100-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-dtd-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/README.md b/resnet152-dtd-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..55572d7fcf6e65560e2662d6a68537ae8f2837e7
--- /dev/null
+++ b/resnet152-dtd-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset dtd.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: dtd
+    pretrained: true
+test_datasets: null
+train_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: train
+type: transformers
+val_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: test
+```
+
diff --git a/resnet152-dtd-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/config.json b/resnet152-dtd-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..6cee8e06ce13fa5525fb8517c300e637bc05dba7
--- /dev/null
+++ b/resnet152-dtd-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,137 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "banded",
+    "1": "blotchy",
+    "2": "braided",
+    "3": "bubbly",
+    "4": "bumpy",
+    "5": "chequered",
+    "6": "cobwebbed",
+    "7": "cracked",
+    "8": "crosshatched",
+    "9": "crystalline",
+    "10": "dotted",
+    "11": "fibrous",
+    "12": "flecked",
+    "13": "freckled",
+    "14": "frilly",
+    "15": "gauzy",
+    "16": "grid",
+    "17": "grooved",
+    "18": "honeycombed",
+    "19": "interlaced",
+    "20": "knitted",
+    "21": "lacelike",
+    "22": "lined",
+    "23": "marbled",
+    "24": "matted",
+    "25": "meshed",
+    "26": "paisley",
+    "27": "perforated",
+    "28": "pitted",
+    "29": "pleated",
+    "30": "polka-dotted",
+    "31": "porous",
+    "32": "potholed",
+    "33": "scaly",
+    "34": "smeared",
+    "35": "spiralled",
+    "36": "sprinkled",
+    "37": "stained",
+    "38": "stratified",
+    "39": "striped",
+    "40": "studded",
+    "41": "swirly",
+    "42": "veined",
+    "43": "waffled",
+    "44": "woven",
+    "45": "wrinkled",
+    "46": "zigzagged"
+  },
+  "label2id": {
+    "banded": 0,
+    "blotchy": 1,
+    "braided": 2,
+    "bubbly": 3,
+    "bumpy": 4,
+    "chequered": 5,
+    "cobwebbed": 6,
+    "cracked": 7,
+    "crosshatched": 8,
+    "crystalline": 9,
+    "dotted": 10,
+    "fibrous": 11,
+    "flecked": 12,
+    "freckled": 13,
+    "frilly": 14,
+    "gauzy": 15,
+    "grid": 16,
+    "grooved": 17,
+    "honeycombed": 18,
+    "interlaced": 19,
+    "knitted": 20,
+    "lacelike": 21,
+    "lined": 22,
+    "marbled": 23,
+    "matted": 24,
+    "meshed": 25,
+    "paisley": 26,
+    "perforated": 27,
+    "pitted": 28,
+    "pleated": 29,
+    "polka-dotted": 30,
+    "porous": 31,
+    "potholed": 32,
+    "scaly": 33,
+    "smeared": 34,
+    "spiralled": 35,
+    "sprinkled": 36,
+    "stained": 37,
+    "stratified": 38,
+    "striped": 39,
+    "studded": 40,
+    "swirly": 41,
+    "veined": 42,
+    "waffled": 43,
+    "woven": 44,
+    "wrinkled": 45,
+    "zigzagged": 46
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-dtd-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet152-dtd-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-dtd-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-dtd-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/README.md b/resnet152-dtd-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..c99d01cadbf73a4293ccc907b2900b2b0d09118c
--- /dev/null
+++ b/resnet152-dtd-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset dtd.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: dtd
+    pretrained: true
+test_datasets: null
+train_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: train
+type: transformers
+val_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: test
+```
+
diff --git a/resnet152-dtd-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/config.json b/resnet152-dtd-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..6cee8e06ce13fa5525fb8517c300e637bc05dba7
--- /dev/null
+++ b/resnet152-dtd-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,137 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "banded",
+    "1": "blotchy",
+    "2": "braided",
+    "3": "bubbly",
+    "4": "bumpy",
+    "5": "chequered",
+    "6": "cobwebbed",
+    "7": "cracked",
+    "8": "crosshatched",
+    "9": "crystalline",
+    "10": "dotted",
+    "11": "fibrous",
+    "12": "flecked",
+    "13": "freckled",
+    "14": "frilly",
+    "15": "gauzy",
+    "16": "grid",
+    "17": "grooved",
+    "18": "honeycombed",
+    "19": "interlaced",
+    "20": "knitted",
+    "21": "lacelike",
+    "22": "lined",
+    "23": "marbled",
+    "24": "matted",
+    "25": "meshed",
+    "26": "paisley",
+    "27": "perforated",
+    "28": "pitted",
+    "29": "pleated",
+    "30": "polka-dotted",
+    "31": "porous",
+    "32": "potholed",
+    "33": "scaly",
+    "34": "smeared",
+    "35": "spiralled",
+    "36": "sprinkled",
+    "37": "stained",
+    "38": "stratified",
+    "39": "striped",
+    "40": "studded",
+    "41": "swirly",
+    "42": "veined",
+    "43": "waffled",
+    "44": "woven",
+    "45": "wrinkled",
+    "46": "zigzagged"
+  },
+  "label2id": {
+    "banded": 0,
+    "blotchy": 1,
+    "braided": 2,
+    "bubbly": 3,
+    "bumpy": 4,
+    "chequered": 5,
+    "cobwebbed": 6,
+    "cracked": 7,
+    "crosshatched": 8,
+    "crystalline": 9,
+    "dotted": 10,
+    "fibrous": 11,
+    "flecked": 12,
+    "freckled": 13,
+    "frilly": 14,
+    "gauzy": 15,
+    "grid": 16,
+    "grooved": 17,
+    "honeycombed": 18,
+    "interlaced": 19,
+    "knitted": 20,
+    "lacelike": 21,
+    "lined": 22,
+    "marbled": 23,
+    "matted": 24,
+    "meshed": 25,
+    "paisley": 26,
+    "perforated": 27,
+    "pitted": 28,
+    "pleated": 29,
+    "polka-dotted": 30,
+    "porous": 31,
+    "potholed": 32,
+    "scaly": 33,
+    "smeared": 34,
+    "spiralled": 35,
+    "sprinkled": 36,
+    "stained": 37,
+    "stratified": 38,
+    "striped": 39,
+    "studded": 40,
+    "swirly": 41,
+    "veined": 42,
+    "waffled": 43,
+    "woven": 44,
+    "wrinkled": 45,
+    "zigzagged": 46
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-dtd-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet152-dtd-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-dtd-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-dtd-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/README.md b/resnet152-dtd-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..178724417f57fd8ea337fa747e1f0130c25902e1
--- /dev/null
+++ b/resnet152-dtd-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset dtd.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: dtd
+    pretrained: true
+test_datasets: null
+train_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: train
+type: transformers
+val_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: test
+```
+
diff --git a/resnet152-dtd-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/config.json b/resnet152-dtd-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..6cee8e06ce13fa5525fb8517c300e637bc05dba7
--- /dev/null
+++ b/resnet152-dtd-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,137 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "banded",
+    "1": "blotchy",
+    "2": "braided",
+    "3": "bubbly",
+    "4": "bumpy",
+    "5": "chequered",
+    "6": "cobwebbed",
+    "7": "cracked",
+    "8": "crosshatched",
+    "9": "crystalline",
+    "10": "dotted",
+    "11": "fibrous",
+    "12": "flecked",
+    "13": "freckled",
+    "14": "frilly",
+    "15": "gauzy",
+    "16": "grid",
+    "17": "grooved",
+    "18": "honeycombed",
+    "19": "interlaced",
+    "20": "knitted",
+    "21": "lacelike",
+    "22": "lined",
+    "23": "marbled",
+    "24": "matted",
+    "25": "meshed",
+    "26": "paisley",
+    "27": "perforated",
+    "28": "pitted",
+    "29": "pleated",
+    "30": "polka-dotted",
+    "31": "porous",
+    "32": "potholed",
+    "33": "scaly",
+    "34": "smeared",
+    "35": "spiralled",
+    "36": "sprinkled",
+    "37": "stained",
+    "38": "stratified",
+    "39": "striped",
+    "40": "studded",
+    "41": "swirly",
+    "42": "veined",
+    "43": "waffled",
+    "44": "woven",
+    "45": "wrinkled",
+    "46": "zigzagged"
+  },
+  "label2id": {
+    "banded": 0,
+    "blotchy": 1,
+    "braided": 2,
+    "bubbly": 3,
+    "bumpy": 4,
+    "chequered": 5,
+    "cobwebbed": 6,
+    "cracked": 7,
+    "crosshatched": 8,
+    "crystalline": 9,
+    "dotted": 10,
+    "fibrous": 11,
+    "flecked": 12,
+    "freckled": 13,
+    "frilly": 14,
+    "gauzy": 15,
+    "grid": 16,
+    "grooved": 17,
+    "honeycombed": 18,
+    "interlaced": 19,
+    "knitted": 20,
+    "lacelike": 21,
+    "lined": 22,
+    "marbled": 23,
+    "matted": 24,
+    "meshed": 25,
+    "paisley": 26,
+    "perforated": 27,
+    "pitted": 28,
+    "pleated": 29,
+    "polka-dotted": 30,
+    "porous": 31,
+    "potholed": 32,
+    "scaly": 33,
+    "smeared": 34,
+    "spiralled": 35,
+    "sprinkled": 36,
+    "stained": 37,
+    "stratified": 38,
+    "striped": 39,
+    "studded": 40,
+    "swirly": 41,
+    "veined": 42,
+    "waffled": 43,
+    "woven": 44,
+    "wrinkled": 45,
+    "zigzagged": 46
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-dtd-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet152-dtd-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-dtd-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-dtd-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/README.md b/resnet152-dtd-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..c27c6533b91d81b474a6145f93552defcc429e38
--- /dev/null
+++ b/resnet152-dtd-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset dtd.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: dtd
+    pretrained: true
+test_datasets: null
+train_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: train
+type: transformers
+val_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: test
+```
+
diff --git a/resnet152-dtd-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/config.json b/resnet152-dtd-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..6cee8e06ce13fa5525fb8517c300e637bc05dba7
--- /dev/null
+++ b/resnet152-dtd-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,137 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "banded",
+    "1": "blotchy",
+    "2": "braided",
+    "3": "bubbly",
+    "4": "bumpy",
+    "5": "chequered",
+    "6": "cobwebbed",
+    "7": "cracked",
+    "8": "crosshatched",
+    "9": "crystalline",
+    "10": "dotted",
+    "11": "fibrous",
+    "12": "flecked",
+    "13": "freckled",
+    "14": "frilly",
+    "15": "gauzy",
+    "16": "grid",
+    "17": "grooved",
+    "18": "honeycombed",
+    "19": "interlaced",
+    "20": "knitted",
+    "21": "lacelike",
+    "22": "lined",
+    "23": "marbled",
+    "24": "matted",
+    "25": "meshed",
+    "26": "paisley",
+    "27": "perforated",
+    "28": "pitted",
+    "29": "pleated",
+    "30": "polka-dotted",
+    "31": "porous",
+    "32": "potholed",
+    "33": "scaly",
+    "34": "smeared",
+    "35": "spiralled",
+    "36": "sprinkled",
+    "37": "stained",
+    "38": "stratified",
+    "39": "striped",
+    "40": "studded",
+    "41": "swirly",
+    "42": "veined",
+    "43": "waffled",
+    "44": "woven",
+    "45": "wrinkled",
+    "46": "zigzagged"
+  },
+  "label2id": {
+    "banded": 0,
+    "blotchy": 1,
+    "braided": 2,
+    "bubbly": 3,
+    "bumpy": 4,
+    "chequered": 5,
+    "cobwebbed": 6,
+    "cracked": 7,
+    "crosshatched": 8,
+    "crystalline": 9,
+    "dotted": 10,
+    "fibrous": 11,
+    "flecked": 12,
+    "freckled": 13,
+    "frilly": 14,
+    "gauzy": 15,
+    "grid": 16,
+    "grooved": 17,
+    "honeycombed": 18,
+    "interlaced": 19,
+    "knitted": 20,
+    "lacelike": 21,
+    "lined": 22,
+    "marbled": 23,
+    "matted": 24,
+    "meshed": 25,
+    "paisley": 26,
+    "perforated": 27,
+    "pitted": 28,
+    "pleated": 29,
+    "polka-dotted": 30,
+    "porous": 31,
+    "potholed": 32,
+    "scaly": 33,
+    "smeared": 34,
+    "spiralled": 35,
+    "sprinkled": 36,
+    "stained": 37,
+    "stratified": 38,
+    "striped": 39,
+    "studded": 40,
+    "swirly": 41,
+    "veined": 42,
+    "waffled": 43,
+    "woven": 44,
+    "wrinkled": 45,
+    "zigzagged": 46
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-dtd-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet152-dtd-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-dtd-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-dtd-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/README.md b/resnet152-dtd-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..a109bdd0fcc0411c3c5941ce81670c09a0c6884a
--- /dev/null
+++ b/resnet152-dtd-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset dtd.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: dtd
+    pretrained: true
+test_datasets: null
+train_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: train
+type: transformers
+val_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: test
+```
+
diff --git a/resnet152-dtd-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/config.json b/resnet152-dtd-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..6cee8e06ce13fa5525fb8517c300e637bc05dba7
--- /dev/null
+++ b/resnet152-dtd-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,137 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "banded",
+    "1": "blotchy",
+    "2": "braided",
+    "3": "bubbly",
+    "4": "bumpy",
+    "5": "chequered",
+    "6": "cobwebbed",
+    "7": "cracked",
+    "8": "crosshatched",
+    "9": "crystalline",
+    "10": "dotted",
+    "11": "fibrous",
+    "12": "flecked",
+    "13": "freckled",
+    "14": "frilly",
+    "15": "gauzy",
+    "16": "grid",
+    "17": "grooved",
+    "18": "honeycombed",
+    "19": "interlaced",
+    "20": "knitted",
+    "21": "lacelike",
+    "22": "lined",
+    "23": "marbled",
+    "24": "matted",
+    "25": "meshed",
+    "26": "paisley",
+    "27": "perforated",
+    "28": "pitted",
+    "29": "pleated",
+    "30": "polka-dotted",
+    "31": "porous",
+    "32": "potholed",
+    "33": "scaly",
+    "34": "smeared",
+    "35": "spiralled",
+    "36": "sprinkled",
+    "37": "stained",
+    "38": "stratified",
+    "39": "striped",
+    "40": "studded",
+    "41": "swirly",
+    "42": "veined",
+    "43": "waffled",
+    "44": "woven",
+    "45": "wrinkled",
+    "46": "zigzagged"
+  },
+  "label2id": {
+    "banded": 0,
+    "blotchy": 1,
+    "braided": 2,
+    "bubbly": 3,
+    "bumpy": 4,
+    "chequered": 5,
+    "cobwebbed": 6,
+    "cracked": 7,
+    "crosshatched": 8,
+    "crystalline": 9,
+    "dotted": 10,
+    "fibrous": 11,
+    "flecked": 12,
+    "freckled": 13,
+    "frilly": 14,
+    "gauzy": 15,
+    "grid": 16,
+    "grooved": 17,
+    "honeycombed": 18,
+    "interlaced": 19,
+    "knitted": 20,
+    "lacelike": 21,
+    "lined": 22,
+    "marbled": 23,
+    "matted": 24,
+    "meshed": 25,
+    "paisley": 26,
+    "perforated": 27,
+    "pitted": 28,
+    "pleated": 29,
+    "polka-dotted": 30,
+    "porous": 31,
+    "potholed": 32,
+    "scaly": 33,
+    "smeared": 34,
+    "spiralled": 35,
+    "sprinkled": 36,
+    "stained": 37,
+    "stratified": 38,
+    "striped": 39,
+    "studded": 40,
+    "swirly": 41,
+    "veined": 42,
+    "waffled": 43,
+    "woven": 44,
+    "wrinkled": 45,
+    "zigzagged": 46
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-dtd-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet152-dtd-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-dtd-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/README.md b/resnet152-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..a723329a049346196dca0993c83649389115522e
--- /dev/null
+++ b/resnet152-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset dtd.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: dtd
+    pretrained: true
+test_datasets: null
+train_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: train
+type: transformers
+val_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: test
+```
+
diff --git a/resnet152-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/config.json b/resnet152-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..6cee8e06ce13fa5525fb8517c300e637bc05dba7
--- /dev/null
+++ b/resnet152-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,137 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "banded",
+    "1": "blotchy",
+    "2": "braided",
+    "3": "bubbly",
+    "4": "bumpy",
+    "5": "chequered",
+    "6": "cobwebbed",
+    "7": "cracked",
+    "8": "crosshatched",
+    "9": "crystalline",
+    "10": "dotted",
+    "11": "fibrous",
+    "12": "flecked",
+    "13": "freckled",
+    "14": "frilly",
+    "15": "gauzy",
+    "16": "grid",
+    "17": "grooved",
+    "18": "honeycombed",
+    "19": "interlaced",
+    "20": "knitted",
+    "21": "lacelike",
+    "22": "lined",
+    "23": "marbled",
+    "24": "matted",
+    "25": "meshed",
+    "26": "paisley",
+    "27": "perforated",
+    "28": "pitted",
+    "29": "pleated",
+    "30": "polka-dotted",
+    "31": "porous",
+    "32": "potholed",
+    "33": "scaly",
+    "34": "smeared",
+    "35": "spiralled",
+    "36": "sprinkled",
+    "37": "stained",
+    "38": "stratified",
+    "39": "striped",
+    "40": "studded",
+    "41": "swirly",
+    "42": "veined",
+    "43": "waffled",
+    "44": "woven",
+    "45": "wrinkled",
+    "46": "zigzagged"
+  },
+  "label2id": {
+    "banded": 0,
+    "blotchy": 1,
+    "braided": 2,
+    "bubbly": 3,
+    "bumpy": 4,
+    "chequered": 5,
+    "cobwebbed": 6,
+    "cracked": 7,
+    "crosshatched": 8,
+    "crystalline": 9,
+    "dotted": 10,
+    "fibrous": 11,
+    "flecked": 12,
+    "freckled": 13,
+    "frilly": 14,
+    "gauzy": 15,
+    "grid": 16,
+    "grooved": 17,
+    "honeycombed": 18,
+    "interlaced": 19,
+    "knitted": 20,
+    "lacelike": 21,
+    "lined": 22,
+    "marbled": 23,
+    "matted": 24,
+    "meshed": 25,
+    "paisley": 26,
+    "perforated": 27,
+    "pitted": 28,
+    "pleated": 29,
+    "polka-dotted": 30,
+    "porous": 31,
+    "potholed": 32,
+    "scaly": 33,
+    "smeared": 34,
+    "spiralled": 35,
+    "sprinkled": 36,
+    "stained": 37,
+    "stratified": 38,
+    "striped": 39,
+    "studded": 40,
+    "swirly": 41,
+    "veined": 42,
+    "waffled": 43,
+    "woven": 44,
+    "wrinkled": 45,
+    "zigzagged": 46
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet152-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/README.md b/resnet152-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..a723329a049346196dca0993c83649389115522e
--- /dev/null
+++ b/resnet152-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset dtd.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: dtd
+    pretrained: true
+test_datasets: null
+train_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: train
+type: transformers
+val_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: test
+```
+
diff --git a/resnet152-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/config.json b/resnet152-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..6cee8e06ce13fa5525fb8517c300e637bc05dba7
--- /dev/null
+++ b/resnet152-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,137 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "banded",
+    "1": "blotchy",
+    "2": "braided",
+    "3": "bubbly",
+    "4": "bumpy",
+    "5": "chequered",
+    "6": "cobwebbed",
+    "7": "cracked",
+    "8": "crosshatched",
+    "9": "crystalline",
+    "10": "dotted",
+    "11": "fibrous",
+    "12": "flecked",
+    "13": "freckled",
+    "14": "frilly",
+    "15": "gauzy",
+    "16": "grid",
+    "17": "grooved",
+    "18": "honeycombed",
+    "19": "interlaced",
+    "20": "knitted",
+    "21": "lacelike",
+    "22": "lined",
+    "23": "marbled",
+    "24": "matted",
+    "25": "meshed",
+    "26": "paisley",
+    "27": "perforated",
+    "28": "pitted",
+    "29": "pleated",
+    "30": "polka-dotted",
+    "31": "porous",
+    "32": "potholed",
+    "33": "scaly",
+    "34": "smeared",
+    "35": "spiralled",
+    "36": "sprinkled",
+    "37": "stained",
+    "38": "stratified",
+    "39": "striped",
+    "40": "studded",
+    "41": "swirly",
+    "42": "veined",
+    "43": "waffled",
+    "44": "woven",
+    "45": "wrinkled",
+    "46": "zigzagged"
+  },
+  "label2id": {
+    "banded": 0,
+    "blotchy": 1,
+    "braided": 2,
+    "bubbly": 3,
+    "bumpy": 4,
+    "chequered": 5,
+    "cobwebbed": 6,
+    "cracked": 7,
+    "crosshatched": 8,
+    "crystalline": 9,
+    "dotted": 10,
+    "fibrous": 11,
+    "flecked": 12,
+    "freckled": 13,
+    "frilly": 14,
+    "gauzy": 15,
+    "grid": 16,
+    "grooved": 17,
+    "honeycombed": 18,
+    "interlaced": 19,
+    "knitted": 20,
+    "lacelike": 21,
+    "lined": 22,
+    "marbled": 23,
+    "matted": 24,
+    "meshed": 25,
+    "paisley": 26,
+    "perforated": 27,
+    "pitted": 28,
+    "pleated": 29,
+    "polka-dotted": 30,
+    "porous": 31,
+    "potholed": 32,
+    "scaly": 33,
+    "smeared": 34,
+    "spiralled": 35,
+    "sprinkled": 36,
+    "stained": 37,
+    "stratified": 38,
+    "striped": 39,
+    "studded": 40,
+    "swirly": 41,
+    "veined": 42,
+    "waffled": 43,
+    "woven": 44,
+    "wrinkled": 45,
+    "zigzagged": 46
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet152-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-dtd-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/README.md b/resnet152-dtd-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e6851102db373d3568235fa17e3ce199c20b2dc3
--- /dev/null
+++ b/resnet152-dtd-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset dtd.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: dtd
+    pretrained: true
+test_datasets: null
+train_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: train
+type: transformers
+val_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: test
+```
+
diff --git a/resnet152-dtd-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/config.json b/resnet152-dtd-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..6cee8e06ce13fa5525fb8517c300e637bc05dba7
--- /dev/null
+++ b/resnet152-dtd-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/config.json
@@ -0,0 +1,137 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "banded",
+    "1": "blotchy",
+    "2": "braided",
+    "3": "bubbly",
+    "4": "bumpy",
+    "5": "chequered",
+    "6": "cobwebbed",
+    "7": "cracked",
+    "8": "crosshatched",
+    "9": "crystalline",
+    "10": "dotted",
+    "11": "fibrous",
+    "12": "flecked",
+    "13": "freckled",
+    "14": "frilly",
+    "15": "gauzy",
+    "16": "grid",
+    "17": "grooved",
+    "18": "honeycombed",
+    "19": "interlaced",
+    "20": "knitted",
+    "21": "lacelike",
+    "22": "lined",
+    "23": "marbled",
+    "24": "matted",
+    "25": "meshed",
+    "26": "paisley",
+    "27": "perforated",
+    "28": "pitted",
+    "29": "pleated",
+    "30": "polka-dotted",
+    "31": "porous",
+    "32": "potholed",
+    "33": "scaly",
+    "34": "smeared",
+    "35": "spiralled",
+    "36": "sprinkled",
+    "37": "stained",
+    "38": "stratified",
+    "39": "striped",
+    "40": "studded",
+    "41": "swirly",
+    "42": "veined",
+    "43": "waffled",
+    "44": "woven",
+    "45": "wrinkled",
+    "46": "zigzagged"
+  },
+  "label2id": {
+    "banded": 0,
+    "blotchy": 1,
+    "braided": 2,
+    "bubbly": 3,
+    "bumpy": 4,
+    "chequered": 5,
+    "cobwebbed": 6,
+    "cracked": 7,
+    "crosshatched": 8,
+    "crystalline": 9,
+    "dotted": 10,
+    "fibrous": 11,
+    "flecked": 12,
+    "freckled": 13,
+    "frilly": 14,
+    "gauzy": 15,
+    "grid": 16,
+    "grooved": 17,
+    "honeycombed": 18,
+    "interlaced": 19,
+    "knitted": 20,
+    "lacelike": 21,
+    "lined": 22,
+    "marbled": 23,
+    "matted": 24,
+    "meshed": 25,
+    "paisley": 26,
+    "perforated": 27,
+    "pitted": 28,
+    "pleated": 29,
+    "polka-dotted": 30,
+    "porous": 31,
+    "potholed": 32,
+    "scaly": 33,
+    "smeared": 34,
+    "spiralled": 35,
+    "sprinkled": 36,
+    "stained": 37,
+    "stratified": 38,
+    "striped": 39,
+    "studded": 40,
+    "swirly": 41,
+    "veined": 42,
+    "waffled": 43,
+    "woven": 44,
+    "wrinkled": 45,
+    "zigzagged": 46
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-dtd-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet152-dtd-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-dtd-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/README.md b/resnet152-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..2573283ebc3aa1fa2c2cac94a89c13b6018b3590
--- /dev/null
+++ b/resnet152-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset emnist_letters.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: emnist_letters
+    pretrained: true
+test_datasets: null
+train_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: train
+type: transformers
+val_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: test
+```
+
diff --git a/resnet152-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/config.json b/resnet152-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1de185c4a239f93470f739721235a30bac76536e
--- /dev/null
+++ b/resnet152-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,95 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "A",
+    "1": "B",
+    "2": "C",
+    "3": "D",
+    "4": "E",
+    "5": "F",
+    "6": "G",
+    "7": "H",
+    "8": "I",
+    "9": "J",
+    "10": "K",
+    "11": "L",
+    "12": "M",
+    "13": "N",
+    "14": "O",
+    "15": "P",
+    "16": "Q",
+    "17": "R",
+    "18": "S",
+    "19": "T",
+    "20": "U",
+    "21": "V",
+    "22": "W",
+    "23": "X",
+    "24": "Y",
+    "25": "Z"
+  },
+  "label2id": {
+    "A": 0,
+    "B": 1,
+    "C": 2,
+    "D": 3,
+    "E": 4,
+    "F": 5,
+    "G": 6,
+    "H": 7,
+    "I": 8,
+    "J": 9,
+    "K": 10,
+    "L": 11,
+    "M": 12,
+    "N": 13,
+    "O": 14,
+    "P": 15,
+    "Q": 16,
+    "R": 17,
+    "S": 18,
+    "T": 19,
+    "U": 20,
+    "V": 21,
+    "W": 22,
+    "X": 23,
+    "Y": 24,
+    "Z": 25
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet152-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/README.md b/resnet152-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..f7b3e542924e83e476ed485975b858ec99c001e2
--- /dev/null
+++ b/resnet152-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset emnist_letters.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: emnist_letters
+    pretrained: true
+test_datasets: null
+train_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: train
+type: transformers
+val_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: test
+```
+
diff --git a/resnet152-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/config.json b/resnet152-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1de185c4a239f93470f739721235a30bac76536e
--- /dev/null
+++ b/resnet152-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,95 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "A",
+    "1": "B",
+    "2": "C",
+    "3": "D",
+    "4": "E",
+    "5": "F",
+    "6": "G",
+    "7": "H",
+    "8": "I",
+    "9": "J",
+    "10": "K",
+    "11": "L",
+    "12": "M",
+    "13": "N",
+    "14": "O",
+    "15": "P",
+    "16": "Q",
+    "17": "R",
+    "18": "S",
+    "19": "T",
+    "20": "U",
+    "21": "V",
+    "22": "W",
+    "23": "X",
+    "24": "Y",
+    "25": "Z"
+  },
+  "label2id": {
+    "A": 0,
+    "B": 1,
+    "C": 2,
+    "D": 3,
+    "E": 4,
+    "F": 5,
+    "G": 6,
+    "H": 7,
+    "I": 8,
+    "J": 9,
+    "K": 10,
+    "L": 11,
+    "M": 12,
+    "N": 13,
+    "O": 14,
+    "P": 15,
+    "Q": 16,
+    "R": 17,
+    "S": 18,
+    "T": 19,
+    "U": 20,
+    "V": 21,
+    "W": 22,
+    "X": 23,
+    "Y": 24,
+    "Z": 25
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet152-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-emnist_letters-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/README.md b/resnet152-emnist_letters-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..aac0ffadb1caa859a408899a50fc5b769ff82da0
--- /dev/null
+++ b/resnet152-emnist_letters-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset emnist_letters.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: emnist_letters
+    pretrained: true
+test_datasets: null
+train_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: train
+type: transformers
+val_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: test
+```
+
diff --git a/resnet152-emnist_letters-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/config.json b/resnet152-emnist_letters-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1de185c4a239f93470f739721235a30bac76536e
--- /dev/null
+++ b/resnet152-emnist_letters-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,95 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "A",
+    "1": "B",
+    "2": "C",
+    "3": "D",
+    "4": "E",
+    "5": "F",
+    "6": "G",
+    "7": "H",
+    "8": "I",
+    "9": "J",
+    "10": "K",
+    "11": "L",
+    "12": "M",
+    "13": "N",
+    "14": "O",
+    "15": "P",
+    "16": "Q",
+    "17": "R",
+    "18": "S",
+    "19": "T",
+    "20": "U",
+    "21": "V",
+    "22": "W",
+    "23": "X",
+    "24": "Y",
+    "25": "Z"
+  },
+  "label2id": {
+    "A": 0,
+    "B": 1,
+    "C": 2,
+    "D": 3,
+    "E": 4,
+    "F": 5,
+    "G": 6,
+    "H": 7,
+    "I": 8,
+    "J": 9,
+    "K": 10,
+    "L": 11,
+    "M": 12,
+    "N": 13,
+    "O": 14,
+    "P": 15,
+    "Q": 16,
+    "R": 17,
+    "S": 18,
+    "T": 19,
+    "U": 20,
+    "V": 21,
+    "W": 22,
+    "X": 23,
+    "Y": 24,
+    "Z": 25
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-emnist_letters-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet152-emnist_letters-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-emnist_letters-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-emnist_letters-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/README.md b/resnet152-emnist_letters-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..f7b3e542924e83e476ed485975b858ec99c001e2
--- /dev/null
+++ b/resnet152-emnist_letters-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset emnist_letters.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: emnist_letters
+    pretrained: true
+test_datasets: null
+train_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: train
+type: transformers
+val_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: test
+```
+
diff --git a/resnet152-emnist_letters-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/config.json b/resnet152-emnist_letters-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1de185c4a239f93470f739721235a30bac76536e
--- /dev/null
+++ b/resnet152-emnist_letters-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,95 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "A",
+    "1": "B",
+    "2": "C",
+    "3": "D",
+    "4": "E",
+    "5": "F",
+    "6": "G",
+    "7": "H",
+    "8": "I",
+    "9": "J",
+    "10": "K",
+    "11": "L",
+    "12": "M",
+    "13": "N",
+    "14": "O",
+    "15": "P",
+    "16": "Q",
+    "17": "R",
+    "18": "S",
+    "19": "T",
+    "20": "U",
+    "21": "V",
+    "22": "W",
+    "23": "X",
+    "24": "Y",
+    "25": "Z"
+  },
+  "label2id": {
+    "A": 0,
+    "B": 1,
+    "C": 2,
+    "D": 3,
+    "E": 4,
+    "F": 5,
+    "G": 6,
+    "H": 7,
+    "I": 8,
+    "J": 9,
+    "K": 10,
+    "L": 11,
+    "M": 12,
+    "N": 13,
+    "O": 14,
+    "P": 15,
+    "Q": 16,
+    "R": 17,
+    "S": 18,
+    "T": 19,
+    "U": 20,
+    "V": 21,
+    "W": 22,
+    "X": 23,
+    "Y": 24,
+    "Z": 25
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-emnist_letters-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet152-emnist_letters-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-emnist_letters-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/README.md b/resnet152-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..b38d97a56d26e7e6ea2bb481f949be6d6e33c7f5
--- /dev/null
+++ b/resnet152-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset emnist_letters.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: emnist_letters
+    pretrained: true
+test_datasets: null
+train_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: train
+type: transformers
+val_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: test
+```
+
diff --git a/resnet152-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/config.json b/resnet152-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1de185c4a239f93470f739721235a30bac76536e
--- /dev/null
+++ b/resnet152-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,95 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "A",
+    "1": "B",
+    "2": "C",
+    "3": "D",
+    "4": "E",
+    "5": "F",
+    "6": "G",
+    "7": "H",
+    "8": "I",
+    "9": "J",
+    "10": "K",
+    "11": "L",
+    "12": "M",
+    "13": "N",
+    "14": "O",
+    "15": "P",
+    "16": "Q",
+    "17": "R",
+    "18": "S",
+    "19": "T",
+    "20": "U",
+    "21": "V",
+    "22": "W",
+    "23": "X",
+    "24": "Y",
+    "25": "Z"
+  },
+  "label2id": {
+    "A": 0,
+    "B": 1,
+    "C": 2,
+    "D": 3,
+    "E": 4,
+    "F": 5,
+    "G": 6,
+    "H": 7,
+    "I": 8,
+    "J": 9,
+    "K": 10,
+    "L": 11,
+    "M": 12,
+    "N": 13,
+    "O": 14,
+    "P": 15,
+    "Q": 16,
+    "R": 17,
+    "S": 18,
+    "T": 19,
+    "U": 20,
+    "V": 21,
+    "W": 22,
+    "X": 23,
+    "Y": 24,
+    "Z": 25
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet152-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-eurosat-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/README.md b/resnet152-eurosat-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..cd32e6580ed6913724aeb8f31abdd12698cfb680
--- /dev/null
+++ b/resnet152-eurosat-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset eurosat.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: eurosat
+    pretrained: true
+test_datasets: null
+train_datasets:
+  eurosat:
+    _target_: datasets.load_dataset
+    path: tanganke/eurosat
+    split: train
+type: transformers
+val_datasets:
+  eurosat:
+    _target_: datasets.load_dataset
+    path: tanganke/eurosat
+    split: test
+```
+
diff --git a/resnet152-eurosat-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/config.json b/resnet152-eurosat-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..3fbee75f8255e01f77ec81c2c941301ad8f54ddc
--- /dev/null
+++ b/resnet152-eurosat-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "annual crop land",
+    "1": "forest",
+    "2": "brushland or shrubland",
+    "3": "highway or road",
+    "4": "industrial buildings or commercial buildings",
+    "5": "pasture land",
+    "6": "permanent crop land",
+    "7": "residential buildings or homes or apartments",
+    "8": "river",
+    "9": "lake or sea"
+  },
+  "label2id": {
+    "annual crop land": 0,
+    "brushland or shrubland": 2,
+    "forest": 1,
+    "highway or road": 3,
+    "industrial buildings or commercial buildings": 4,
+    "lake or sea": 9,
+    "pasture land": 5,
+    "permanent crop land": 6,
+    "residential buildings or homes or apartments": 7,
+    "river": 8
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-eurosat-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet152-eurosat-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-eurosat-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/README.md b/resnet152-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..07809faa476d6f3477a65626153fa0529173ba30
--- /dev/null
+++ b/resnet152-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset eurosat.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: eurosat
+    pretrained: true
+test_datasets: null
+train_datasets:
+  eurosat:
+    _target_: datasets.load_dataset
+    path: tanganke/eurosat
+    split: train
+type: transformers
+val_datasets:
+  eurosat:
+    _target_: datasets.load_dataset
+    path: tanganke/eurosat
+    split: test
+```
+
diff --git a/resnet152-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/config.json b/resnet152-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..3fbee75f8255e01f77ec81c2c941301ad8f54ddc
--- /dev/null
+++ b/resnet152-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "annual crop land",
+    "1": "forest",
+    "2": "brushland or shrubland",
+    "3": "highway or road",
+    "4": "industrial buildings or commercial buildings",
+    "5": "pasture land",
+    "6": "permanent crop land",
+    "7": "residential buildings or homes or apartments",
+    "8": "river",
+    "9": "lake or sea"
+  },
+  "label2id": {
+    "annual crop land": 0,
+    "brushland or shrubland": 2,
+    "forest": 1,
+    "highway or road": 3,
+    "industrial buildings or commercial buildings": 4,
+    "lake or sea": 9,
+    "pasture land": 5,
+    "permanent crop land": 6,
+    "residential buildings or homes or apartments": 7,
+    "river": 8
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet152-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-eurosat-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/README.md b/resnet152-eurosat-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..cd32e6580ed6913724aeb8f31abdd12698cfb680
--- /dev/null
+++ b/resnet152-eurosat-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset eurosat.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: eurosat
+    pretrained: true
+test_datasets: null
+train_datasets:
+  eurosat:
+    _target_: datasets.load_dataset
+    path: tanganke/eurosat
+    split: train
+type: transformers
+val_datasets:
+  eurosat:
+    _target_: datasets.load_dataset
+    path: tanganke/eurosat
+    split: test
+```
+
diff --git a/resnet152-eurosat-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/config.json b/resnet152-eurosat-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..3fbee75f8255e01f77ec81c2c941301ad8f54ddc
--- /dev/null
+++ b/resnet152-eurosat-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "annual crop land",
+    "1": "forest",
+    "2": "brushland or shrubland",
+    "3": "highway or road",
+    "4": "industrial buildings or commercial buildings",
+    "5": "pasture land",
+    "6": "permanent crop land",
+    "7": "residential buildings or homes or apartments",
+    "8": "river",
+    "9": "lake or sea"
+  },
+  "label2id": {
+    "annual crop land": 0,
+    "brushland or shrubland": 2,
+    "forest": 1,
+    "highway or road": 3,
+    "industrial buildings or commercial buildings": 4,
+    "lake or sea": 9,
+    "pasture land": 5,
+    "permanent crop land": 6,
+    "residential buildings or homes or apartments": 7,
+    "river": 8
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-eurosat-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet152-eurosat-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-eurosat-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-eurosat-batch_size_256_lr_0.005_training_data_ratio_0.8-3000/README.md b/resnet152-eurosat-batch_size_256_lr_0.005_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..c48c2df17318b268fbd672974ddb7504fc21c233
--- /dev/null
+++ b/resnet152-eurosat-batch_size_256_lr_0.005_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset eurosat.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: eurosat
+    pretrained: true
+test_datasets: null
+train_datasets:
+  eurosat:
+    _target_: datasets.load_dataset
+    path: tanganke/eurosat
+    split: train
+type: transformers
+val_datasets:
+  eurosat:
+    _target_: datasets.load_dataset
+    path: tanganke/eurosat
+    split: test
+```
+
diff --git a/resnet152-eurosat-batch_size_256_lr_0.005_training_data_ratio_0.8-3000/config.json b/resnet152-eurosat-batch_size_256_lr_0.005_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..3fbee75f8255e01f77ec81c2c941301ad8f54ddc
--- /dev/null
+++ b/resnet152-eurosat-batch_size_256_lr_0.005_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "annual crop land",
+    "1": "forest",
+    "2": "brushland or shrubland",
+    "3": "highway or road",
+    "4": "industrial buildings or commercial buildings",
+    "5": "pasture land",
+    "6": "permanent crop land",
+    "7": "residential buildings or homes or apartments",
+    "8": "river",
+    "9": "lake or sea"
+  },
+  "label2id": {
+    "annual crop land": 0,
+    "brushland or shrubland": 2,
+    "forest": 1,
+    "highway or road": 3,
+    "industrial buildings or commercial buildings": 4,
+    "lake or sea": 9,
+    "pasture land": 5,
+    "permanent crop land": 6,
+    "residential buildings or homes or apartments": 7,
+    "river": 8
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-eurosat-batch_size_256_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet152-eurosat-batch_size_256_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-eurosat-batch_size_256_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-eurosat-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/README.md b/resnet152-eurosat-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..6d977fa7a0297369dcb0ab1875cb8f1da408dea7
--- /dev/null
+++ b/resnet152-eurosat-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset eurosat.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: eurosat
+    pretrained: true
+test_datasets: null
+train_datasets:
+  eurosat:
+    _target_: datasets.load_dataset
+    path: tanganke/eurosat
+    split: train
+type: transformers
+val_datasets:
+  eurosat:
+    _target_: datasets.load_dataset
+    path: tanganke/eurosat
+    split: test
+```
+
diff --git a/resnet152-eurosat-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/config.json b/resnet152-eurosat-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..3fbee75f8255e01f77ec81c2c941301ad8f54ddc
--- /dev/null
+++ b/resnet152-eurosat-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "annual crop land",
+    "1": "forest",
+    "2": "brushland or shrubland",
+    "3": "highway or road",
+    "4": "industrial buildings or commercial buildings",
+    "5": "pasture land",
+    "6": "permanent crop land",
+    "7": "residential buildings or homes or apartments",
+    "8": "river",
+    "9": "lake or sea"
+  },
+  "label2id": {
+    "annual crop land": 0,
+    "brushland or shrubland": 2,
+    "forest": 1,
+    "highway or road": 3,
+    "industrial buildings or commercial buildings": 4,
+    "lake or sea": 9,
+    "pasture land": 5,
+    "permanent crop land": 6,
+    "residential buildings or homes or apartments": 7,
+    "river": 8
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-eurosat-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet152-eurosat-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-eurosat-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/README.md b/resnet152-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..423d126c174e116dabd223993a23290d869ffa90
--- /dev/null
+++ b/resnet152-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fashion_mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: fashion_mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: train
+type: transformers
+val_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: test
+```
+
diff --git a/resnet152-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/config.json b/resnet152-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..99626e1d853a8525a84a8d4ca7c121c77c398eed
--- /dev/null
+++ b/resnet152-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "T - shirt / top",
+    "1": "Trouser",
+    "2": "Pullover",
+    "3": "Dress",
+    "4": "Coat",
+    "5": "Sandal",
+    "6": "Shirt",
+    "7": "Sneaker",
+    "8": "Bag",
+    "9": "Ankle boot"
+  },
+  "label2id": {
+    "Ankle boot": 9,
+    "Bag": 8,
+    "Coat": 4,
+    "Dress": 3,
+    "Pullover": 2,
+    "Sandal": 5,
+    "Shirt": 6,
+    "Sneaker": 7,
+    "T - shirt / top": 0,
+    "Trouser": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet152-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-fashion_mnist-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/README.md b/resnet152-fashion_mnist-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..3043512eab7b561caccbb9eca8c9162fc2b045a3
--- /dev/null
+++ b/resnet152-fashion_mnist-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fashion_mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: fashion_mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: train
+type: transformers
+val_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: test
+```
+
diff --git a/resnet152-fashion_mnist-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/config.json b/resnet152-fashion_mnist-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..99626e1d853a8525a84a8d4ca7c121c77c398eed
--- /dev/null
+++ b/resnet152-fashion_mnist-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "T - shirt / top",
+    "1": "Trouser",
+    "2": "Pullover",
+    "3": "Dress",
+    "4": "Coat",
+    "5": "Sandal",
+    "6": "Shirt",
+    "7": "Sneaker",
+    "8": "Bag",
+    "9": "Ankle boot"
+  },
+  "label2id": {
+    "Ankle boot": 9,
+    "Bag": 8,
+    "Coat": 4,
+    "Dress": 3,
+    "Pullover": 2,
+    "Sandal": 5,
+    "Shirt": 6,
+    "Sneaker": 7,
+    "T - shirt / top": 0,
+    "Trouser": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-fashion_mnist-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet152-fashion_mnist-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-fashion_mnist-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-fashion_mnist-batch_size_256_lr_0.01_training_data_ratio_0.8-1000/README.md b/resnet152-fashion_mnist-batch_size_256_lr_0.01_training_data_ratio_0.8-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..9061a712d50d4cdb64fe974649fc0bf547b8916b
--- /dev/null
+++ b/resnet152-fashion_mnist-batch_size_256_lr_0.01_training_data_ratio_0.8-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fashion_mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: fashion_mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: train
+type: transformers
+val_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: test
+```
+
diff --git a/resnet152-fashion_mnist-batch_size_256_lr_0.01_training_data_ratio_0.8-1000/config.json b/resnet152-fashion_mnist-batch_size_256_lr_0.01_training_data_ratio_0.8-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..99626e1d853a8525a84a8d4ca7c121c77c398eed
--- /dev/null
+++ b/resnet152-fashion_mnist-batch_size_256_lr_0.01_training_data_ratio_0.8-1000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "T - shirt / top",
+    "1": "Trouser",
+    "2": "Pullover",
+    "3": "Dress",
+    "4": "Coat",
+    "5": "Sandal",
+    "6": "Shirt",
+    "7": "Sneaker",
+    "8": "Bag",
+    "9": "Ankle boot"
+  },
+  "label2id": {
+    "Ankle boot": 9,
+    "Bag": 8,
+    "Coat": 4,
+    "Dress": 3,
+    "Pullover": 2,
+    "Sandal": 5,
+    "Shirt": 6,
+    "Sneaker": 7,
+    "T - shirt / top": 0,
+    "Trouser": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-fashion_mnist-batch_size_256_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet152-fashion_mnist-batch_size_256_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-fashion_mnist-batch_size_256_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/README.md b/resnet152-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..f1e66447ce310afe593146f1c7b6fa05294e6f28
--- /dev/null
+++ b/resnet152-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fashion_mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: fashion_mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: train
+type: transformers
+val_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: test
+```
+
diff --git a/resnet152-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/config.json b/resnet152-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..99626e1d853a8525a84a8d4ca7c121c77c398eed
--- /dev/null
+++ b/resnet152-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "T - shirt / top",
+    "1": "Trouser",
+    "2": "Pullover",
+    "3": "Dress",
+    "4": "Coat",
+    "5": "Sandal",
+    "6": "Shirt",
+    "7": "Sneaker",
+    "8": "Bag",
+    "9": "Ankle boot"
+  },
+  "label2id": {
+    "Ankle boot": 9,
+    "Bag": 8,
+    "Coat": 4,
+    "Dress": 3,
+    "Pullover": 2,
+    "Sandal": 5,
+    "Shirt": 6,
+    "Sneaker": 7,
+    "T - shirt / top": 0,
+    "Trouser": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet152-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/README.md b/resnet152-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..798a6e1c2522480d0e7749e8b344b5217ded5696
--- /dev/null
+++ b/resnet152-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fashion_mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: fashion_mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: train
+type: transformers
+val_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: test
+```
+
diff --git a/resnet152-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/config.json b/resnet152-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..99626e1d853a8525a84a8d4ca7c121c77c398eed
--- /dev/null
+++ b/resnet152-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "T - shirt / top",
+    "1": "Trouser",
+    "2": "Pullover",
+    "3": "Dress",
+    "4": "Coat",
+    "5": "Sandal",
+    "6": "Shirt",
+    "7": "Sneaker",
+    "8": "Bag",
+    "9": "Ankle boot"
+  },
+  "label2id": {
+    "Ankle boot": 9,
+    "Bag": 8,
+    "Coat": 4,
+    "Dress": 3,
+    "Pullover": 2,
+    "Sandal": 5,
+    "Shirt": 6,
+    "Sneaker": 7,
+    "T - shirt / top": 0,
+    "Trouser": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet152-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-fer2013-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/README.md b/resnet152-fer2013-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..f0f527f6335e1b275b251685c3b6a9680d4d6f9d
--- /dev/null
+++ b/resnet152-fer2013-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,74 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fer2013.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: fer2013
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: train
+type: transformers
+val_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: test
+```
+
diff --git a/resnet152-fer2013-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/config.json b/resnet152-fer2013-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..874518c652ec15eb6e18b82397e47e4f485a6af7
--- /dev/null
+++ b/resnet152-fer2013-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,57 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "angry",
+    "1": "disgusted",
+    "2": "fearful",
+    "3": "happy",
+    "4": "neutral",
+    "5": "sad",
+    "6": "surprised"
+  },
+  "label2id": {
+    "angry": 0,
+    "disgusted": 1,
+    "fearful": 2,
+    "happy": 3,
+    "neutral": 4,
+    "sad": 5,
+    "surprised": 6
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-fer2013-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet152-fer2013-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-fer2013-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-fer2013-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/README.md b/resnet152-fer2013-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..2eed29d68bddb5f69b26086ca9289547fe13027e
--- /dev/null
+++ b/resnet152-fer2013-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,74 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fer2013.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: fer2013
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: train
+type: transformers
+val_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: test
+```
+
diff --git a/resnet152-fer2013-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/config.json b/resnet152-fer2013-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..874518c652ec15eb6e18b82397e47e4f485a6af7
--- /dev/null
+++ b/resnet152-fer2013-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,57 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "angry",
+    "1": "disgusted",
+    "2": "fearful",
+    "3": "happy",
+    "4": "neutral",
+    "5": "sad",
+    "6": "surprised"
+  },
+  "label2id": {
+    "angry": 0,
+    "disgusted": 1,
+    "fearful": 2,
+    "happy": 3,
+    "neutral": 4,
+    "sad": 5,
+    "surprised": 6
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-fer2013-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet152-fer2013-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-fer2013-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/README.md b/resnet152-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..563d00787d4b818947ea78a1561caa4bf51cc1fd
--- /dev/null
+++ b/resnet152-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,74 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fer2013.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: fer2013
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: train
+type: transformers
+val_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: test
+```
+
diff --git a/resnet152-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/config.json b/resnet152-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..874518c652ec15eb6e18b82397e47e4f485a6af7
--- /dev/null
+++ b/resnet152-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,57 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "angry",
+    "1": "disgusted",
+    "2": "fearful",
+    "3": "happy",
+    "4": "neutral",
+    "5": "sad",
+    "6": "surprised"
+  },
+  "label2id": {
+    "angry": 0,
+    "disgusted": 1,
+    "fearful": 2,
+    "happy": 3,
+    "neutral": 4,
+    "sad": 5,
+    "surprised": 6
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet152-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/README.md b/resnet152-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..563d00787d4b818947ea78a1561caa4bf51cc1fd
--- /dev/null
+++ b/resnet152-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,74 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fer2013.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: fer2013
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: train
+type: transformers
+val_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: test
+```
+
diff --git a/resnet152-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/config.json b/resnet152-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..874518c652ec15eb6e18b82397e47e4f485a6af7
--- /dev/null
+++ b/resnet152-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,57 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "angry",
+    "1": "disgusted",
+    "2": "fearful",
+    "3": "happy",
+    "4": "neutral",
+    "5": "sad",
+    "6": "surprised"
+  },
+  "label2id": {
+    "angry": 0,
+    "disgusted": 1,
+    "fearful": 2,
+    "happy": 3,
+    "neutral": 4,
+    "sad": 5,
+    "surprised": 6
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet152-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/README.md b/resnet152-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..81ae378b0786d377e1a38245aae7328fa9a08c19
--- /dev/null
+++ b/resnet152-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,74 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fer2013.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: fer2013
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: train
+type: transformers
+val_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: test
+```
+
diff --git a/resnet152-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/config.json b/resnet152-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..874518c652ec15eb6e18b82397e47e4f485a6af7
--- /dev/null
+++ b/resnet152-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,57 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "angry",
+    "1": "disgusted",
+    "2": "fearful",
+    "3": "happy",
+    "4": "neutral",
+    "5": "sad",
+    "6": "surprised"
+  },
+  "label2id": {
+    "angry": 0,
+    "disgusted": 1,
+    "fearful": 2,
+    "happy": 3,
+    "neutral": 4,
+    "sad": 5,
+    "surprised": 6
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet152-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-fer2013-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/README.md b/resnet152-fer2013-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..51b61a4f7a58d85be7c9f11b75ef7e9018147937
--- /dev/null
+++ b/resnet152-fer2013-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/README.md
@@ -0,0 +1,74 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fer2013.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: fer2013
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: train
+type: transformers
+val_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: test
+```
+
diff --git a/resnet152-fer2013-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/config.json b/resnet152-fer2013-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..874518c652ec15eb6e18b82397e47e4f485a6af7
--- /dev/null
+++ b/resnet152-fer2013-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/config.json
@@ -0,0 +1,57 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "angry",
+    "1": "disgusted",
+    "2": "fearful",
+    "3": "happy",
+    "4": "neutral",
+    "5": "sad",
+    "6": "surprised"
+  },
+  "label2id": {
+    "angry": 0,
+    "disgusted": 1,
+    "fearful": 2,
+    "happy": 3,
+    "neutral": 4,
+    "sad": 5,
+    "surprised": 6
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-fer2013-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet152-fer2013-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-fer2013-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/README.md b/resnet152-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..59dc67fd6cf0c4451dcc617b2de75eda18ebad1f
--- /dev/null
+++ b/resnet152-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,74 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fer2013.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: fer2013
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: train
+type: transformers
+val_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: test
+```
+
diff --git a/resnet152-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/config.json b/resnet152-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..874518c652ec15eb6e18b82397e47e4f485a6af7
--- /dev/null
+++ b/resnet152-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,57 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "angry",
+    "1": "disgusted",
+    "2": "fearful",
+    "3": "happy",
+    "4": "neutral",
+    "5": "sad",
+    "6": "surprised"
+  },
+  "label2id": {
+    "angry": 0,
+    "disgusted": 1,
+    "fearful": 2,
+    "happy": 3,
+    "neutral": 4,
+    "sad": 5,
+    "surprised": 6
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet152-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/README.md b/resnet152-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..59dc67fd6cf0c4451dcc617b2de75eda18ebad1f
--- /dev/null
+++ b/resnet152-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,74 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fer2013.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: fer2013
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: train
+type: transformers
+val_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: test
+```
+
diff --git a/resnet152-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/config.json b/resnet152-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..874518c652ec15eb6e18b82397e47e4f485a6af7
--- /dev/null
+++ b/resnet152-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,57 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "angry",
+    "1": "disgusted",
+    "2": "fearful",
+    "3": "happy",
+    "4": "neutral",
+    "5": "sad",
+    "6": "surprised"
+  },
+  "label2id": {
+    "angry": 0,
+    "disgusted": 1,
+    "fearful": 2,
+    "happy": 3,
+    "neutral": 4,
+    "sad": 5,
+    "surprised": 6
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet152-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-food101-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/README.md b/resnet152-food101-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..ce38082f38f6e4ad7311cbd7222ea0232edf79c3
--- /dev/null
+++ b/resnet152-food101-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset food101.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: food101
+    pretrained: true
+test_datasets: null
+train_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: train
+type: transformers
+val_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: validation
+```
+
diff --git a/resnet152-food101-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/config.json b/resnet152-food101-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..002738700083d19b6f2089a9c2d0959b8ee2b0bb
--- /dev/null
+++ b/resnet152-food101-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,245 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "apple pie",
+    "1": "baby back ribs",
+    "2": "baklava",
+    "3": "beef carpaccio",
+    "4": "beef tartare",
+    "5": "beet salad",
+    "6": "beignets",
+    "7": "bibimbap",
+    "8": "bread pudding",
+    "9": "breakfast burrito",
+    "10": "bruschetta",
+    "11": "caesar salad",
+    "12": "cannoli",
+    "13": "caprese salad",
+    "14": "carrot cake",
+    "15": "ceviche",
+    "16": "cheese plate",
+    "17": "cheesecake",
+    "18": "chicken curry",
+    "19": "chicken quesadilla",
+    "20": "chicken wings",
+    "21": "chocolate cake",
+    "22": "chocolate mousse",
+    "23": "churros",
+    "24": "clam chowder",
+    "25": "club sandwich",
+    "26": "crab cakes",
+    "27": "creme brulee",
+    "28": "croque madame",
+    "29": "cup cakes",
+    "30": "deviled eggs",
+    "31": "donuts",
+    "32": "dumplings",
+    "33": "edamame",
+    "34": "eggs benedict",
+    "35": "escargots",
+    "36": "falafel",
+    "37": "filet mignon",
+    "38": "fish and chips",
+    "39": "foie gras",
+    "40": "french fries",
+    "41": "french onion soup",
+    "42": "french toast",
+    "43": "fried calamari",
+    "44": "fried rice",
+    "45": "frozen yogurt",
+    "46": "garlic bread",
+    "47": "gnocchi",
+    "48": "greek salad",
+    "49": "grilled cheese sandwich",
+    "50": "grilled salmon",
+    "51": "guacamole",
+    "52": "gyoza",
+    "53": "hamburger",
+    "54": "hot and sour soup",
+    "55": "hot dog",
+    "56": "huevos rancheros",
+    "57": "hummus",
+    "58": "ice cream",
+    "59": "lasagna",
+    "60": "lobster bisque",
+    "61": "lobster roll sandwich",
+    "62": "macaroni and cheese",
+    "63": "macarons",
+    "64": "miso soup",
+    "65": "mussels",
+    "66": "nachos",
+    "67": "omelette",
+    "68": "onion rings",
+    "69": "oysters",
+    "70": "pad thai",
+    "71": "paella",
+    "72": "pancakes",
+    "73": "panna cotta",
+    "74": "peking duck",
+    "75": "pho",
+    "76": "pizza",
+    "77": "pork chop",
+    "78": "poutine",
+    "79": "prime rib",
+    "80": "pulled pork sandwich",
+    "81": "ramen",
+    "82": "ravioli",
+    "83": "red velvet cake",
+    "84": "risotto",
+    "85": "samosa",
+    "86": "sashimi",
+    "87": "scallops",
+    "88": "seaweed salad",
+    "89": "shrimp and grits",
+    "90": "spaghetti bolognese",
+    "91": "spaghetti carbonara",
+    "92": "spring rolls",
+    "93": "steak",
+    "94": "strawberry shortcake",
+    "95": "sushi",
+    "96": "tacos",
+    "97": "takoyaki",
+    "98": "tiramisu",
+    "99": "tuna tartare",
+    "100": "waffles"
+  },
+  "label2id": {
+    "apple pie": 0,
+    "baby back ribs": 1,
+    "baklava": 2,
+    "beef carpaccio": 3,
+    "beef tartare": 4,
+    "beet salad": 5,
+    "beignets": 6,
+    "bibimbap": 7,
+    "bread pudding": 8,
+    "breakfast burrito": 9,
+    "bruschetta": 10,
+    "caesar salad": 11,
+    "cannoli": 12,
+    "caprese salad": 13,
+    "carrot cake": 14,
+    "ceviche": 15,
+    "cheese plate": 16,
+    "cheesecake": 17,
+    "chicken curry": 18,
+    "chicken quesadilla": 19,
+    "chicken wings": 20,
+    "chocolate cake": 21,
+    "chocolate mousse": 22,
+    "churros": 23,
+    "clam chowder": 24,
+    "club sandwich": 25,
+    "crab cakes": 26,
+    "creme brulee": 27,
+    "croque madame": 28,
+    "cup cakes": 29,
+    "deviled eggs": 30,
+    "donuts": 31,
+    "dumplings": 32,
+    "edamame": 33,
+    "eggs benedict": 34,
+    "escargots": 35,
+    "falafel": 36,
+    "filet mignon": 37,
+    "fish and chips": 38,
+    "foie gras": 39,
+    "french fries": 40,
+    "french onion soup": 41,
+    "french toast": 42,
+    "fried calamari": 43,
+    "fried rice": 44,
+    "frozen yogurt": 45,
+    "garlic bread": 46,
+    "gnocchi": 47,
+    "greek salad": 48,
+    "grilled cheese sandwich": 49,
+    "grilled salmon": 50,
+    "guacamole": 51,
+    "gyoza": 52,
+    "hamburger": 53,
+    "hot and sour soup": 54,
+    "hot dog": 55,
+    "huevos rancheros": 56,
+    "hummus": 57,
+    "ice cream": 58,
+    "lasagna": 59,
+    "lobster bisque": 60,
+    "lobster roll sandwich": 61,
+    "macaroni and cheese": 62,
+    "macarons": 63,
+    "miso soup": 64,
+    "mussels": 65,
+    "nachos": 66,
+    "omelette": 67,
+    "onion rings": 68,
+    "oysters": 69,
+    "pad thai": 70,
+    "paella": 71,
+    "pancakes": 72,
+    "panna cotta": 73,
+    "peking duck": 74,
+    "pho": 75,
+    "pizza": 76,
+    "pork chop": 77,
+    "poutine": 78,
+    "prime rib": 79,
+    "pulled pork sandwich": 80,
+    "ramen": 81,
+    "ravioli": 82,
+    "red velvet cake": 83,
+    "risotto": 84,
+    "samosa": 85,
+    "sashimi": 86,
+    "scallops": 87,
+    "seaweed salad": 88,
+    "shrimp and grits": 89,
+    "spaghetti bolognese": 90,
+    "spaghetti carbonara": 91,
+    "spring rolls": 92,
+    "steak": 93,
+    "strawberry shortcake": 94,
+    "sushi": 95,
+    "tacos": 96,
+    "takoyaki": 97,
+    "tiramisu": 98,
+    "tuna tartare": 99,
+    "waffles": 100
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-food101-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet152-food101-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-food101-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-food101-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/README.md b/resnet152-food101-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..df9a69f2384fcf701ca94f5a963adfd2c490777b
--- /dev/null
+++ b/resnet152-food101-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset food101.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: food101
+    pretrained: true
+test_datasets: null
+train_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: train
+type: transformers
+val_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: validation
+```
+
diff --git a/resnet152-food101-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/config.json b/resnet152-food101-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..002738700083d19b6f2089a9c2d0959b8ee2b0bb
--- /dev/null
+++ b/resnet152-food101-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,245 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "apple pie",
+    "1": "baby back ribs",
+    "2": "baklava",
+    "3": "beef carpaccio",
+    "4": "beef tartare",
+    "5": "beet salad",
+    "6": "beignets",
+    "7": "bibimbap",
+    "8": "bread pudding",
+    "9": "breakfast burrito",
+    "10": "bruschetta",
+    "11": "caesar salad",
+    "12": "cannoli",
+    "13": "caprese salad",
+    "14": "carrot cake",
+    "15": "ceviche",
+    "16": "cheese plate",
+    "17": "cheesecake",
+    "18": "chicken curry",
+    "19": "chicken quesadilla",
+    "20": "chicken wings",
+    "21": "chocolate cake",
+    "22": "chocolate mousse",
+    "23": "churros",
+    "24": "clam chowder",
+    "25": "club sandwich",
+    "26": "crab cakes",
+    "27": "creme brulee",
+    "28": "croque madame",
+    "29": "cup cakes",
+    "30": "deviled eggs",
+    "31": "donuts",
+    "32": "dumplings",
+    "33": "edamame",
+    "34": "eggs benedict",
+    "35": "escargots",
+    "36": "falafel",
+    "37": "filet mignon",
+    "38": "fish and chips",
+    "39": "foie gras",
+    "40": "french fries",
+    "41": "french onion soup",
+    "42": "french toast",
+    "43": "fried calamari",
+    "44": "fried rice",
+    "45": "frozen yogurt",
+    "46": "garlic bread",
+    "47": "gnocchi",
+    "48": "greek salad",
+    "49": "grilled cheese sandwich",
+    "50": "grilled salmon",
+    "51": "guacamole",
+    "52": "gyoza",
+    "53": "hamburger",
+    "54": "hot and sour soup",
+    "55": "hot dog",
+    "56": "huevos rancheros",
+    "57": "hummus",
+    "58": "ice cream",
+    "59": "lasagna",
+    "60": "lobster bisque",
+    "61": "lobster roll sandwich",
+    "62": "macaroni and cheese",
+    "63": "macarons",
+    "64": "miso soup",
+    "65": "mussels",
+    "66": "nachos",
+    "67": "omelette",
+    "68": "onion rings",
+    "69": "oysters",
+    "70": "pad thai",
+    "71": "paella",
+    "72": "pancakes",
+    "73": "panna cotta",
+    "74": "peking duck",
+    "75": "pho",
+    "76": "pizza",
+    "77": "pork chop",
+    "78": "poutine",
+    "79": "prime rib",
+    "80": "pulled pork sandwich",
+    "81": "ramen",
+    "82": "ravioli",
+    "83": "red velvet cake",
+    "84": "risotto",
+    "85": "samosa",
+    "86": "sashimi",
+    "87": "scallops",
+    "88": "seaweed salad",
+    "89": "shrimp and grits",
+    "90": "spaghetti bolognese",
+    "91": "spaghetti carbonara",
+    "92": "spring rolls",
+    "93": "steak",
+    "94": "strawberry shortcake",
+    "95": "sushi",
+    "96": "tacos",
+    "97": "takoyaki",
+    "98": "tiramisu",
+    "99": "tuna tartare",
+    "100": "waffles"
+  },
+  "label2id": {
+    "apple pie": 0,
+    "baby back ribs": 1,
+    "baklava": 2,
+    "beef carpaccio": 3,
+    "beef tartare": 4,
+    "beet salad": 5,
+    "beignets": 6,
+    "bibimbap": 7,
+    "bread pudding": 8,
+    "breakfast burrito": 9,
+    "bruschetta": 10,
+    "caesar salad": 11,
+    "cannoli": 12,
+    "caprese salad": 13,
+    "carrot cake": 14,
+    "ceviche": 15,
+    "cheese plate": 16,
+    "cheesecake": 17,
+    "chicken curry": 18,
+    "chicken quesadilla": 19,
+    "chicken wings": 20,
+    "chocolate cake": 21,
+    "chocolate mousse": 22,
+    "churros": 23,
+    "clam chowder": 24,
+    "club sandwich": 25,
+    "crab cakes": 26,
+    "creme brulee": 27,
+    "croque madame": 28,
+    "cup cakes": 29,
+    "deviled eggs": 30,
+    "donuts": 31,
+    "dumplings": 32,
+    "edamame": 33,
+    "eggs benedict": 34,
+    "escargots": 35,
+    "falafel": 36,
+    "filet mignon": 37,
+    "fish and chips": 38,
+    "foie gras": 39,
+    "french fries": 40,
+    "french onion soup": 41,
+    "french toast": 42,
+    "fried calamari": 43,
+    "fried rice": 44,
+    "frozen yogurt": 45,
+    "garlic bread": 46,
+    "gnocchi": 47,
+    "greek salad": 48,
+    "grilled cheese sandwich": 49,
+    "grilled salmon": 50,
+    "guacamole": 51,
+    "gyoza": 52,
+    "hamburger": 53,
+    "hot and sour soup": 54,
+    "hot dog": 55,
+    "huevos rancheros": 56,
+    "hummus": 57,
+    "ice cream": 58,
+    "lasagna": 59,
+    "lobster bisque": 60,
+    "lobster roll sandwich": 61,
+    "macaroni and cheese": 62,
+    "macarons": 63,
+    "miso soup": 64,
+    "mussels": 65,
+    "nachos": 66,
+    "omelette": 67,
+    "onion rings": 68,
+    "oysters": 69,
+    "pad thai": 70,
+    "paella": 71,
+    "pancakes": 72,
+    "panna cotta": 73,
+    "peking duck": 74,
+    "pho": 75,
+    "pizza": 76,
+    "pork chop": 77,
+    "poutine": 78,
+    "prime rib": 79,
+    "pulled pork sandwich": 80,
+    "ramen": 81,
+    "ravioli": 82,
+    "red velvet cake": 83,
+    "risotto": 84,
+    "samosa": 85,
+    "sashimi": 86,
+    "scallops": 87,
+    "seaweed salad": 88,
+    "shrimp and grits": 89,
+    "spaghetti bolognese": 90,
+    "spaghetti carbonara": 91,
+    "spring rolls": 92,
+    "steak": 93,
+    "strawberry shortcake": 94,
+    "sushi": 95,
+    "tacos": 96,
+    "takoyaki": 97,
+    "tiramisu": 98,
+    "tuna tartare": 99,
+    "waffles": 100
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-food101-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet152-food101-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-food101-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-food101-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/README.md b/resnet152-food101-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..0b33ff65237b0d816bcaa572ae1921797c4a0976
--- /dev/null
+++ b/resnet152-food101-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset food101.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: food101
+    pretrained: true
+test_datasets: null
+train_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: train
+type: transformers
+val_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: validation
+```
+
diff --git a/resnet152-food101-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/config.json b/resnet152-food101-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..002738700083d19b6f2089a9c2d0959b8ee2b0bb
--- /dev/null
+++ b/resnet152-food101-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/config.json
@@ -0,0 +1,245 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "apple pie",
+    "1": "baby back ribs",
+    "2": "baklava",
+    "3": "beef carpaccio",
+    "4": "beef tartare",
+    "5": "beet salad",
+    "6": "beignets",
+    "7": "bibimbap",
+    "8": "bread pudding",
+    "9": "breakfast burrito",
+    "10": "bruschetta",
+    "11": "caesar salad",
+    "12": "cannoli",
+    "13": "caprese salad",
+    "14": "carrot cake",
+    "15": "ceviche",
+    "16": "cheese plate",
+    "17": "cheesecake",
+    "18": "chicken curry",
+    "19": "chicken quesadilla",
+    "20": "chicken wings",
+    "21": "chocolate cake",
+    "22": "chocolate mousse",
+    "23": "churros",
+    "24": "clam chowder",
+    "25": "club sandwich",
+    "26": "crab cakes",
+    "27": "creme brulee",
+    "28": "croque madame",
+    "29": "cup cakes",
+    "30": "deviled eggs",
+    "31": "donuts",
+    "32": "dumplings",
+    "33": "edamame",
+    "34": "eggs benedict",
+    "35": "escargots",
+    "36": "falafel",
+    "37": "filet mignon",
+    "38": "fish and chips",
+    "39": "foie gras",
+    "40": "french fries",
+    "41": "french onion soup",
+    "42": "french toast",
+    "43": "fried calamari",
+    "44": "fried rice",
+    "45": "frozen yogurt",
+    "46": "garlic bread",
+    "47": "gnocchi",
+    "48": "greek salad",
+    "49": "grilled cheese sandwich",
+    "50": "grilled salmon",
+    "51": "guacamole",
+    "52": "gyoza",
+    "53": "hamburger",
+    "54": "hot and sour soup",
+    "55": "hot dog",
+    "56": "huevos rancheros",
+    "57": "hummus",
+    "58": "ice cream",
+    "59": "lasagna",
+    "60": "lobster bisque",
+    "61": "lobster roll sandwich",
+    "62": "macaroni and cheese",
+    "63": "macarons",
+    "64": "miso soup",
+    "65": "mussels",
+    "66": "nachos",
+    "67": "omelette",
+    "68": "onion rings",
+    "69": "oysters",
+    "70": "pad thai",
+    "71": "paella",
+    "72": "pancakes",
+    "73": "panna cotta",
+    "74": "peking duck",
+    "75": "pho",
+    "76": "pizza",
+    "77": "pork chop",
+    "78": "poutine",
+    "79": "prime rib",
+    "80": "pulled pork sandwich",
+    "81": "ramen",
+    "82": "ravioli",
+    "83": "red velvet cake",
+    "84": "risotto",
+    "85": "samosa",
+    "86": "sashimi",
+    "87": "scallops",
+    "88": "seaweed salad",
+    "89": "shrimp and grits",
+    "90": "spaghetti bolognese",
+    "91": "spaghetti carbonara",
+    "92": "spring rolls",
+    "93": "steak",
+    "94": "strawberry shortcake",
+    "95": "sushi",
+    "96": "tacos",
+    "97": "takoyaki",
+    "98": "tiramisu",
+    "99": "tuna tartare",
+    "100": "waffles"
+  },
+  "label2id": {
+    "apple pie": 0,
+    "baby back ribs": 1,
+    "baklava": 2,
+    "beef carpaccio": 3,
+    "beef tartare": 4,
+    "beet salad": 5,
+    "beignets": 6,
+    "bibimbap": 7,
+    "bread pudding": 8,
+    "breakfast burrito": 9,
+    "bruschetta": 10,
+    "caesar salad": 11,
+    "cannoli": 12,
+    "caprese salad": 13,
+    "carrot cake": 14,
+    "ceviche": 15,
+    "cheese plate": 16,
+    "cheesecake": 17,
+    "chicken curry": 18,
+    "chicken quesadilla": 19,
+    "chicken wings": 20,
+    "chocolate cake": 21,
+    "chocolate mousse": 22,
+    "churros": 23,
+    "clam chowder": 24,
+    "club sandwich": 25,
+    "crab cakes": 26,
+    "creme brulee": 27,
+    "croque madame": 28,
+    "cup cakes": 29,
+    "deviled eggs": 30,
+    "donuts": 31,
+    "dumplings": 32,
+    "edamame": 33,
+    "eggs benedict": 34,
+    "escargots": 35,
+    "falafel": 36,
+    "filet mignon": 37,
+    "fish and chips": 38,
+    "foie gras": 39,
+    "french fries": 40,
+    "french onion soup": 41,
+    "french toast": 42,
+    "fried calamari": 43,
+    "fried rice": 44,
+    "frozen yogurt": 45,
+    "garlic bread": 46,
+    "gnocchi": 47,
+    "greek salad": 48,
+    "grilled cheese sandwich": 49,
+    "grilled salmon": 50,
+    "guacamole": 51,
+    "gyoza": 52,
+    "hamburger": 53,
+    "hot and sour soup": 54,
+    "hot dog": 55,
+    "huevos rancheros": 56,
+    "hummus": 57,
+    "ice cream": 58,
+    "lasagna": 59,
+    "lobster bisque": 60,
+    "lobster roll sandwich": 61,
+    "macaroni and cheese": 62,
+    "macarons": 63,
+    "miso soup": 64,
+    "mussels": 65,
+    "nachos": 66,
+    "omelette": 67,
+    "onion rings": 68,
+    "oysters": 69,
+    "pad thai": 70,
+    "paella": 71,
+    "pancakes": 72,
+    "panna cotta": 73,
+    "peking duck": 74,
+    "pho": 75,
+    "pizza": 76,
+    "pork chop": 77,
+    "poutine": 78,
+    "prime rib": 79,
+    "pulled pork sandwich": 80,
+    "ramen": 81,
+    "ravioli": 82,
+    "red velvet cake": 83,
+    "risotto": 84,
+    "samosa": 85,
+    "sashimi": 86,
+    "scallops": 87,
+    "seaweed salad": 88,
+    "shrimp and grits": 89,
+    "spaghetti bolognese": 90,
+    "spaghetti carbonara": 91,
+    "spring rolls": 92,
+    "steak": 93,
+    "strawberry shortcake": 94,
+    "sushi": 95,
+    "tacos": 96,
+    "takoyaki": 97,
+    "tiramisu": 98,
+    "tuna tartare": 99,
+    "waffles": 100
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-food101-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet152-food101-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-food101-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-gtsrb-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/README.md b/resnet152-gtsrb-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..54e220b0826339fe5625e8db446ce69551a7ad4f
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset gtsrb.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: gtsrb
+    pretrained: true
+test_datasets: null
+train_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: train
+type: transformers
+val_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: test
+```
+
diff --git a/resnet152-gtsrb-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/config.json b/resnet152-gtsrb-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..53161b832eb7e51bd11bce461528d4642c58be00
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,129 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "red and white circle 20 kph speed limit",
+    "1": "red and white circle 30 kph speed limit",
+    "2": "red and white circle 50 kph speed limit",
+    "3": "red and white circle 60 kph speed limit",
+    "4": "red and white circle 70 kph speed limit",
+    "5": "red and white circle 80 kph speed limit",
+    "6": "end / de-restriction of 80 kph speed limit",
+    "7": "red and white circle 100 kph speed limit",
+    "8": "red and white circle 120 kph speed limit",
+    "9": "red and white circle red car and black car no passing",
+    "10": "red and white circle red truck and black car no passing",
+    "11": "red and white triangle road intersection warning",
+    "12": "white and yellow diamond priority road",
+    "13": "red and white upside down triangle yield right-of-way",
+    "14": "stop",
+    "15": "empty red and white circle",
+    "16": "red and white circle no truck entry",
+    "17": "red circle with white horizonal stripe no entry",
+    "18": "red and white triangle with exclamation mark warning",
+    "19": "red and white triangle with black left curve approaching warning",
+    "20": "red and white triangle with black right curve approaching warning",
+    "21": "red and white triangle with black double curve approaching warning",
+    "22": "red and white triangle rough / bumpy road warning",
+    "23": "red and white triangle car skidding / slipping warning",
+    "24": "red and white triangle with merging / narrow lanes warning",
+    "25": "red and white triangle with person digging / construction / road work warning",
+    "26": "red and white triangle with traffic light approaching warning",
+    "27": "red and white triangle with person walking warning",
+    "28": "red and white triangle with child and person walking warning",
+    "29": "red and white triangle with bicyle warning",
+    "30": "red and white triangle with snowflake / ice warning",
+    "31": "red and white triangle with deer warning",
+    "32": "white circle with gray strike bar no speed limit",
+    "33": "blue circle with white right turn arrow mandatory",
+    "34": "blue circle with white left turn arrow mandatory",
+    "35": "blue circle with white forward arrow mandatory",
+    "36": "blue circle with white forward or right turn arrow mandatory",
+    "37": "blue circle with white forward or left turn arrow mandatory",
+    "38": "blue circle with white keep right arrow mandatory",
+    "39": "blue circle with white keep left arrow mandatory",
+    "40": "blue circle with white arrows indicating a traffic circle",
+    "41": "white circle with gray strike bar indicating no passing for cars has ended",
+    "42": "white circle with gray strike bar indicating no passing for trucks has ended"
+  },
+  "label2id": {
+    "blue circle with white arrows indicating a traffic circle": 40,
+    "blue circle with white forward arrow mandatory": 35,
+    "blue circle with white forward or left turn arrow mandatory": 37,
+    "blue circle with white forward or right turn arrow mandatory": 36,
+    "blue circle with white keep left arrow mandatory": 39,
+    "blue circle with white keep right arrow mandatory": 38,
+    "blue circle with white left turn arrow mandatory": 34,
+    "blue circle with white right turn arrow mandatory": 33,
+    "empty red and white circle": 15,
+    "end / de-restriction of 80 kph speed limit": 6,
+    "red and white circle 100 kph speed limit": 7,
+    "red and white circle 120 kph speed limit": 8,
+    "red and white circle 20 kph speed limit": 0,
+    "red and white circle 30 kph speed limit": 1,
+    "red and white circle 50 kph speed limit": 2,
+    "red and white circle 60 kph speed limit": 3,
+    "red and white circle 70 kph speed limit": 4,
+    "red and white circle 80 kph speed limit": 5,
+    "red and white circle no truck entry": 16,
+    "red and white circle red car and black car no passing": 9,
+    "red and white circle red truck and black car no passing": 10,
+    "red and white triangle car skidding / slipping warning": 23,
+    "red and white triangle road intersection warning": 11,
+    "red and white triangle rough / bumpy road warning": 22,
+    "red and white triangle with bicyle warning": 29,
+    "red and white triangle with black double curve approaching warning": 21,
+    "red and white triangle with black left curve approaching warning": 19,
+    "red and white triangle with black right curve approaching warning": 20,
+    "red and white triangle with child and person walking warning": 28,
+    "red and white triangle with deer warning": 31,
+    "red and white triangle with exclamation mark warning": 18,
+    "red and white triangle with merging / narrow lanes warning": 24,
+    "red and white triangle with person digging / construction / road work warning": 25,
+    "red and white triangle with person walking warning": 27,
+    "red and white triangle with snowflake / ice warning": 30,
+    "red and white triangle with traffic light approaching warning": 26,
+    "red and white upside down triangle yield right-of-way": 13,
+    "red circle with white horizonal stripe no entry": 17,
+    "stop": 14,
+    "white and yellow diamond priority road": 12,
+    "white circle with gray strike bar indicating no passing for cars has ended": 41,
+    "white circle with gray strike bar indicating no passing for trucks has ended": 42,
+    "white circle with gray strike bar no speed limit": 32
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-gtsrb-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet152-gtsrb-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-gtsrb-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/README.md b/resnet152-gtsrb-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..2d782b0ee317298ebcacf0de14dcda3ef4416d1d
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset gtsrb.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: gtsrb
+    pretrained: true
+test_datasets: null
+train_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: train
+type: transformers
+val_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: test
+```
+
diff --git a/resnet152-gtsrb-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/config.json b/resnet152-gtsrb-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..53161b832eb7e51bd11bce461528d4642c58be00
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,129 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "red and white circle 20 kph speed limit",
+    "1": "red and white circle 30 kph speed limit",
+    "2": "red and white circle 50 kph speed limit",
+    "3": "red and white circle 60 kph speed limit",
+    "4": "red and white circle 70 kph speed limit",
+    "5": "red and white circle 80 kph speed limit",
+    "6": "end / de-restriction of 80 kph speed limit",
+    "7": "red and white circle 100 kph speed limit",
+    "8": "red and white circle 120 kph speed limit",
+    "9": "red and white circle red car and black car no passing",
+    "10": "red and white circle red truck and black car no passing",
+    "11": "red and white triangle road intersection warning",
+    "12": "white and yellow diamond priority road",
+    "13": "red and white upside down triangle yield right-of-way",
+    "14": "stop",
+    "15": "empty red and white circle",
+    "16": "red and white circle no truck entry",
+    "17": "red circle with white horizonal stripe no entry",
+    "18": "red and white triangle with exclamation mark warning",
+    "19": "red and white triangle with black left curve approaching warning",
+    "20": "red and white triangle with black right curve approaching warning",
+    "21": "red and white triangle with black double curve approaching warning",
+    "22": "red and white triangle rough / bumpy road warning",
+    "23": "red and white triangle car skidding / slipping warning",
+    "24": "red and white triangle with merging / narrow lanes warning",
+    "25": "red and white triangle with person digging / construction / road work warning",
+    "26": "red and white triangle with traffic light approaching warning",
+    "27": "red and white triangle with person walking warning",
+    "28": "red and white triangle with child and person walking warning",
+    "29": "red and white triangle with bicyle warning",
+    "30": "red and white triangle with snowflake / ice warning",
+    "31": "red and white triangle with deer warning",
+    "32": "white circle with gray strike bar no speed limit",
+    "33": "blue circle with white right turn arrow mandatory",
+    "34": "blue circle with white left turn arrow mandatory",
+    "35": "blue circle with white forward arrow mandatory",
+    "36": "blue circle with white forward or right turn arrow mandatory",
+    "37": "blue circle with white forward or left turn arrow mandatory",
+    "38": "blue circle with white keep right arrow mandatory",
+    "39": "blue circle with white keep left arrow mandatory",
+    "40": "blue circle with white arrows indicating a traffic circle",
+    "41": "white circle with gray strike bar indicating no passing for cars has ended",
+    "42": "white circle with gray strike bar indicating no passing for trucks has ended"
+  },
+  "label2id": {
+    "blue circle with white arrows indicating a traffic circle": 40,
+    "blue circle with white forward arrow mandatory": 35,
+    "blue circle with white forward or left turn arrow mandatory": 37,
+    "blue circle with white forward or right turn arrow mandatory": 36,
+    "blue circle with white keep left arrow mandatory": 39,
+    "blue circle with white keep right arrow mandatory": 38,
+    "blue circle with white left turn arrow mandatory": 34,
+    "blue circle with white right turn arrow mandatory": 33,
+    "empty red and white circle": 15,
+    "end / de-restriction of 80 kph speed limit": 6,
+    "red and white circle 100 kph speed limit": 7,
+    "red and white circle 120 kph speed limit": 8,
+    "red and white circle 20 kph speed limit": 0,
+    "red and white circle 30 kph speed limit": 1,
+    "red and white circle 50 kph speed limit": 2,
+    "red and white circle 60 kph speed limit": 3,
+    "red and white circle 70 kph speed limit": 4,
+    "red and white circle 80 kph speed limit": 5,
+    "red and white circle no truck entry": 16,
+    "red and white circle red car and black car no passing": 9,
+    "red and white circle red truck and black car no passing": 10,
+    "red and white triangle car skidding / slipping warning": 23,
+    "red and white triangle road intersection warning": 11,
+    "red and white triangle rough / bumpy road warning": 22,
+    "red and white triangle with bicyle warning": 29,
+    "red and white triangle with black double curve approaching warning": 21,
+    "red and white triangle with black left curve approaching warning": 19,
+    "red and white triangle with black right curve approaching warning": 20,
+    "red and white triangle with child and person walking warning": 28,
+    "red and white triangle with deer warning": 31,
+    "red and white triangle with exclamation mark warning": 18,
+    "red and white triangle with merging / narrow lanes warning": 24,
+    "red and white triangle with person digging / construction / road work warning": 25,
+    "red and white triangle with person walking warning": 27,
+    "red and white triangle with snowflake / ice warning": 30,
+    "red and white triangle with traffic light approaching warning": 26,
+    "red and white upside down triangle yield right-of-way": 13,
+    "red circle with white horizonal stripe no entry": 17,
+    "stop": 14,
+    "white and yellow diamond priority road": 12,
+    "white circle with gray strike bar indicating no passing for cars has ended": 41,
+    "white circle with gray strike bar indicating no passing for trucks has ended": 42,
+    "white circle with gray strike bar no speed limit": 32
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-gtsrb-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet152-gtsrb-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-gtsrb-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/README.md b/resnet152-gtsrb-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..80e94c825b47407f20c876236b09d3faff29ddcf
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset gtsrb.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: gtsrb
+    pretrained: true
+test_datasets: null
+train_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: train
+type: transformers
+val_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: test
+```
+
diff --git a/resnet152-gtsrb-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/config.json b/resnet152-gtsrb-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..53161b832eb7e51bd11bce461528d4642c58be00
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/config.json
@@ -0,0 +1,129 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "red and white circle 20 kph speed limit",
+    "1": "red and white circle 30 kph speed limit",
+    "2": "red and white circle 50 kph speed limit",
+    "3": "red and white circle 60 kph speed limit",
+    "4": "red and white circle 70 kph speed limit",
+    "5": "red and white circle 80 kph speed limit",
+    "6": "end / de-restriction of 80 kph speed limit",
+    "7": "red and white circle 100 kph speed limit",
+    "8": "red and white circle 120 kph speed limit",
+    "9": "red and white circle red car and black car no passing",
+    "10": "red and white circle red truck and black car no passing",
+    "11": "red and white triangle road intersection warning",
+    "12": "white and yellow diamond priority road",
+    "13": "red and white upside down triangle yield right-of-way",
+    "14": "stop",
+    "15": "empty red and white circle",
+    "16": "red and white circle no truck entry",
+    "17": "red circle with white horizonal stripe no entry",
+    "18": "red and white triangle with exclamation mark warning",
+    "19": "red and white triangle with black left curve approaching warning",
+    "20": "red and white triangle with black right curve approaching warning",
+    "21": "red and white triangle with black double curve approaching warning",
+    "22": "red and white triangle rough / bumpy road warning",
+    "23": "red and white triangle car skidding / slipping warning",
+    "24": "red and white triangle with merging / narrow lanes warning",
+    "25": "red and white triangle with person digging / construction / road work warning",
+    "26": "red and white triangle with traffic light approaching warning",
+    "27": "red and white triangle with person walking warning",
+    "28": "red and white triangle with child and person walking warning",
+    "29": "red and white triangle with bicyle warning",
+    "30": "red and white triangle with snowflake / ice warning",
+    "31": "red and white triangle with deer warning",
+    "32": "white circle with gray strike bar no speed limit",
+    "33": "blue circle with white right turn arrow mandatory",
+    "34": "blue circle with white left turn arrow mandatory",
+    "35": "blue circle with white forward arrow mandatory",
+    "36": "blue circle with white forward or right turn arrow mandatory",
+    "37": "blue circle with white forward or left turn arrow mandatory",
+    "38": "blue circle with white keep right arrow mandatory",
+    "39": "blue circle with white keep left arrow mandatory",
+    "40": "blue circle with white arrows indicating a traffic circle",
+    "41": "white circle with gray strike bar indicating no passing for cars has ended",
+    "42": "white circle with gray strike bar indicating no passing for trucks has ended"
+  },
+  "label2id": {
+    "blue circle with white arrows indicating a traffic circle": 40,
+    "blue circle with white forward arrow mandatory": 35,
+    "blue circle with white forward or left turn arrow mandatory": 37,
+    "blue circle with white forward or right turn arrow mandatory": 36,
+    "blue circle with white keep left arrow mandatory": 39,
+    "blue circle with white keep right arrow mandatory": 38,
+    "blue circle with white left turn arrow mandatory": 34,
+    "blue circle with white right turn arrow mandatory": 33,
+    "empty red and white circle": 15,
+    "end / de-restriction of 80 kph speed limit": 6,
+    "red and white circle 100 kph speed limit": 7,
+    "red and white circle 120 kph speed limit": 8,
+    "red and white circle 20 kph speed limit": 0,
+    "red and white circle 30 kph speed limit": 1,
+    "red and white circle 50 kph speed limit": 2,
+    "red and white circle 60 kph speed limit": 3,
+    "red and white circle 70 kph speed limit": 4,
+    "red and white circle 80 kph speed limit": 5,
+    "red and white circle no truck entry": 16,
+    "red and white circle red car and black car no passing": 9,
+    "red and white circle red truck and black car no passing": 10,
+    "red and white triangle car skidding / slipping warning": 23,
+    "red and white triangle road intersection warning": 11,
+    "red and white triangle rough / bumpy road warning": 22,
+    "red and white triangle with bicyle warning": 29,
+    "red and white triangle with black double curve approaching warning": 21,
+    "red and white triangle with black left curve approaching warning": 19,
+    "red and white triangle with black right curve approaching warning": 20,
+    "red and white triangle with child and person walking warning": 28,
+    "red and white triangle with deer warning": 31,
+    "red and white triangle with exclamation mark warning": 18,
+    "red and white triangle with merging / narrow lanes warning": 24,
+    "red and white triangle with person digging / construction / road work warning": 25,
+    "red and white triangle with person walking warning": 27,
+    "red and white triangle with snowflake / ice warning": 30,
+    "red and white triangle with traffic light approaching warning": 26,
+    "red and white upside down triangle yield right-of-way": 13,
+    "red circle with white horizonal stripe no entry": 17,
+    "stop": 14,
+    "white and yellow diamond priority road": 12,
+    "white circle with gray strike bar indicating no passing for cars has ended": 41,
+    "white circle with gray strike bar indicating no passing for trucks has ended": 42,
+    "white circle with gray strike bar no speed limit": 32
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-gtsrb-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet152-gtsrb-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-gtsrb-batch_size_256_lr_0.001_training_data_ratio_1.0-1000/README.md b/resnet152-gtsrb-batch_size_256_lr_0.001_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..46c42244cbd378d072fde177b21d95a79d9e4e21
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_256_lr_0.001_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset gtsrb.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: gtsrb
+    pretrained: true
+test_datasets: null
+train_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: train
+type: transformers
+val_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: test
+```
+
diff --git a/resnet152-gtsrb-batch_size_256_lr_0.001_training_data_ratio_1.0-1000/config.json b/resnet152-gtsrb-batch_size_256_lr_0.001_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..53161b832eb7e51bd11bce461528d4642c58be00
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_256_lr_0.001_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,129 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "red and white circle 20 kph speed limit",
+    "1": "red and white circle 30 kph speed limit",
+    "2": "red and white circle 50 kph speed limit",
+    "3": "red and white circle 60 kph speed limit",
+    "4": "red and white circle 70 kph speed limit",
+    "5": "red and white circle 80 kph speed limit",
+    "6": "end / de-restriction of 80 kph speed limit",
+    "7": "red and white circle 100 kph speed limit",
+    "8": "red and white circle 120 kph speed limit",
+    "9": "red and white circle red car and black car no passing",
+    "10": "red and white circle red truck and black car no passing",
+    "11": "red and white triangle road intersection warning",
+    "12": "white and yellow diamond priority road",
+    "13": "red and white upside down triangle yield right-of-way",
+    "14": "stop",
+    "15": "empty red and white circle",
+    "16": "red and white circle no truck entry",
+    "17": "red circle with white horizonal stripe no entry",
+    "18": "red and white triangle with exclamation mark warning",
+    "19": "red and white triangle with black left curve approaching warning",
+    "20": "red and white triangle with black right curve approaching warning",
+    "21": "red and white triangle with black double curve approaching warning",
+    "22": "red and white triangle rough / bumpy road warning",
+    "23": "red and white triangle car skidding / slipping warning",
+    "24": "red and white triangle with merging / narrow lanes warning",
+    "25": "red and white triangle with person digging / construction / road work warning",
+    "26": "red and white triangle with traffic light approaching warning",
+    "27": "red and white triangle with person walking warning",
+    "28": "red and white triangle with child and person walking warning",
+    "29": "red and white triangle with bicyle warning",
+    "30": "red and white triangle with snowflake / ice warning",
+    "31": "red and white triangle with deer warning",
+    "32": "white circle with gray strike bar no speed limit",
+    "33": "blue circle with white right turn arrow mandatory",
+    "34": "blue circle with white left turn arrow mandatory",
+    "35": "blue circle with white forward arrow mandatory",
+    "36": "blue circle with white forward or right turn arrow mandatory",
+    "37": "blue circle with white forward or left turn arrow mandatory",
+    "38": "blue circle with white keep right arrow mandatory",
+    "39": "blue circle with white keep left arrow mandatory",
+    "40": "blue circle with white arrows indicating a traffic circle",
+    "41": "white circle with gray strike bar indicating no passing for cars has ended",
+    "42": "white circle with gray strike bar indicating no passing for trucks has ended"
+  },
+  "label2id": {
+    "blue circle with white arrows indicating a traffic circle": 40,
+    "blue circle with white forward arrow mandatory": 35,
+    "blue circle with white forward or left turn arrow mandatory": 37,
+    "blue circle with white forward or right turn arrow mandatory": 36,
+    "blue circle with white keep left arrow mandatory": 39,
+    "blue circle with white keep right arrow mandatory": 38,
+    "blue circle with white left turn arrow mandatory": 34,
+    "blue circle with white right turn arrow mandatory": 33,
+    "empty red and white circle": 15,
+    "end / de-restriction of 80 kph speed limit": 6,
+    "red and white circle 100 kph speed limit": 7,
+    "red and white circle 120 kph speed limit": 8,
+    "red and white circle 20 kph speed limit": 0,
+    "red and white circle 30 kph speed limit": 1,
+    "red and white circle 50 kph speed limit": 2,
+    "red and white circle 60 kph speed limit": 3,
+    "red and white circle 70 kph speed limit": 4,
+    "red and white circle 80 kph speed limit": 5,
+    "red and white circle no truck entry": 16,
+    "red and white circle red car and black car no passing": 9,
+    "red and white circle red truck and black car no passing": 10,
+    "red and white triangle car skidding / slipping warning": 23,
+    "red and white triangle road intersection warning": 11,
+    "red and white triangle rough / bumpy road warning": 22,
+    "red and white triangle with bicyle warning": 29,
+    "red and white triangle with black double curve approaching warning": 21,
+    "red and white triangle with black left curve approaching warning": 19,
+    "red and white triangle with black right curve approaching warning": 20,
+    "red and white triangle with child and person walking warning": 28,
+    "red and white triangle with deer warning": 31,
+    "red and white triangle with exclamation mark warning": 18,
+    "red and white triangle with merging / narrow lanes warning": 24,
+    "red and white triangle with person digging / construction / road work warning": 25,
+    "red and white triangle with person walking warning": 27,
+    "red and white triangle with snowflake / ice warning": 30,
+    "red and white triangle with traffic light approaching warning": 26,
+    "red and white upside down triangle yield right-of-way": 13,
+    "red circle with white horizonal stripe no entry": 17,
+    "stop": 14,
+    "white and yellow diamond priority road": 12,
+    "white circle with gray strike bar indicating no passing for cars has ended": 41,
+    "white circle with gray strike bar indicating no passing for trucks has ended": 42,
+    "white circle with gray strike bar no speed limit": 32
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-gtsrb-batch_size_256_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet152-gtsrb-batch_size_256_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_256_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/README.md b/resnet152-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..16d28159ac14063a0985426b28837a4a815af4c0
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset gtsrb.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: gtsrb
+    pretrained: true
+test_datasets: null
+train_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: train
+type: transformers
+val_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: test
+```
+
diff --git a/resnet152-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/config.json b/resnet152-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..53161b832eb7e51bd11bce461528d4642c58be00
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,129 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "red and white circle 20 kph speed limit",
+    "1": "red and white circle 30 kph speed limit",
+    "2": "red and white circle 50 kph speed limit",
+    "3": "red and white circle 60 kph speed limit",
+    "4": "red and white circle 70 kph speed limit",
+    "5": "red and white circle 80 kph speed limit",
+    "6": "end / de-restriction of 80 kph speed limit",
+    "7": "red and white circle 100 kph speed limit",
+    "8": "red and white circle 120 kph speed limit",
+    "9": "red and white circle red car and black car no passing",
+    "10": "red and white circle red truck and black car no passing",
+    "11": "red and white triangle road intersection warning",
+    "12": "white and yellow diamond priority road",
+    "13": "red and white upside down triangle yield right-of-way",
+    "14": "stop",
+    "15": "empty red and white circle",
+    "16": "red and white circle no truck entry",
+    "17": "red circle with white horizonal stripe no entry",
+    "18": "red and white triangle with exclamation mark warning",
+    "19": "red and white triangle with black left curve approaching warning",
+    "20": "red and white triangle with black right curve approaching warning",
+    "21": "red and white triangle with black double curve approaching warning",
+    "22": "red and white triangle rough / bumpy road warning",
+    "23": "red and white triangle car skidding / slipping warning",
+    "24": "red and white triangle with merging / narrow lanes warning",
+    "25": "red and white triangle with person digging / construction / road work warning",
+    "26": "red and white triangle with traffic light approaching warning",
+    "27": "red and white triangle with person walking warning",
+    "28": "red and white triangle with child and person walking warning",
+    "29": "red and white triangle with bicyle warning",
+    "30": "red and white triangle with snowflake / ice warning",
+    "31": "red and white triangle with deer warning",
+    "32": "white circle with gray strike bar no speed limit",
+    "33": "blue circle with white right turn arrow mandatory",
+    "34": "blue circle with white left turn arrow mandatory",
+    "35": "blue circle with white forward arrow mandatory",
+    "36": "blue circle with white forward or right turn arrow mandatory",
+    "37": "blue circle with white forward or left turn arrow mandatory",
+    "38": "blue circle with white keep right arrow mandatory",
+    "39": "blue circle with white keep left arrow mandatory",
+    "40": "blue circle with white arrows indicating a traffic circle",
+    "41": "white circle with gray strike bar indicating no passing for cars has ended",
+    "42": "white circle with gray strike bar indicating no passing for trucks has ended"
+  },
+  "label2id": {
+    "blue circle with white arrows indicating a traffic circle": 40,
+    "blue circle with white forward arrow mandatory": 35,
+    "blue circle with white forward or left turn arrow mandatory": 37,
+    "blue circle with white forward or right turn arrow mandatory": 36,
+    "blue circle with white keep left arrow mandatory": 39,
+    "blue circle with white keep right arrow mandatory": 38,
+    "blue circle with white left turn arrow mandatory": 34,
+    "blue circle with white right turn arrow mandatory": 33,
+    "empty red and white circle": 15,
+    "end / de-restriction of 80 kph speed limit": 6,
+    "red and white circle 100 kph speed limit": 7,
+    "red and white circle 120 kph speed limit": 8,
+    "red and white circle 20 kph speed limit": 0,
+    "red and white circle 30 kph speed limit": 1,
+    "red and white circle 50 kph speed limit": 2,
+    "red and white circle 60 kph speed limit": 3,
+    "red and white circle 70 kph speed limit": 4,
+    "red and white circle 80 kph speed limit": 5,
+    "red and white circle no truck entry": 16,
+    "red and white circle red car and black car no passing": 9,
+    "red and white circle red truck and black car no passing": 10,
+    "red and white triangle car skidding / slipping warning": 23,
+    "red and white triangle road intersection warning": 11,
+    "red and white triangle rough / bumpy road warning": 22,
+    "red and white triangle with bicyle warning": 29,
+    "red and white triangle with black double curve approaching warning": 21,
+    "red and white triangle with black left curve approaching warning": 19,
+    "red and white triangle with black right curve approaching warning": 20,
+    "red and white triangle with child and person walking warning": 28,
+    "red and white triangle with deer warning": 31,
+    "red and white triangle with exclamation mark warning": 18,
+    "red and white triangle with merging / narrow lanes warning": 24,
+    "red and white triangle with person digging / construction / road work warning": 25,
+    "red and white triangle with person walking warning": 27,
+    "red and white triangle with snowflake / ice warning": 30,
+    "red and white triangle with traffic light approaching warning": 26,
+    "red and white upside down triangle yield right-of-way": 13,
+    "red circle with white horizonal stripe no entry": 17,
+    "stop": 14,
+    "white and yellow diamond priority road": 12,
+    "white circle with gray strike bar indicating no passing for cars has ended": 41,
+    "white circle with gray strike bar indicating no passing for trucks has ended": 42,
+    "white circle with gray strike bar no speed limit": 32
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet152-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/README.md b/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..c21b6b8daa1ee0a58c2e77507a7a2cbdbd3d0a58
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset gtsrb.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: gtsrb
+    pretrained: true
+test_datasets: null
+train_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: train
+type: transformers
+val_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: test
+```
+
diff --git a/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/config.json b/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..53161b832eb7e51bd11bce461528d4642c58be00
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,129 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "red and white circle 20 kph speed limit",
+    "1": "red and white circle 30 kph speed limit",
+    "2": "red and white circle 50 kph speed limit",
+    "3": "red and white circle 60 kph speed limit",
+    "4": "red and white circle 70 kph speed limit",
+    "5": "red and white circle 80 kph speed limit",
+    "6": "end / de-restriction of 80 kph speed limit",
+    "7": "red and white circle 100 kph speed limit",
+    "8": "red and white circle 120 kph speed limit",
+    "9": "red and white circle red car and black car no passing",
+    "10": "red and white circle red truck and black car no passing",
+    "11": "red and white triangle road intersection warning",
+    "12": "white and yellow diamond priority road",
+    "13": "red and white upside down triangle yield right-of-way",
+    "14": "stop",
+    "15": "empty red and white circle",
+    "16": "red and white circle no truck entry",
+    "17": "red circle with white horizonal stripe no entry",
+    "18": "red and white triangle with exclamation mark warning",
+    "19": "red and white triangle with black left curve approaching warning",
+    "20": "red and white triangle with black right curve approaching warning",
+    "21": "red and white triangle with black double curve approaching warning",
+    "22": "red and white triangle rough / bumpy road warning",
+    "23": "red and white triangle car skidding / slipping warning",
+    "24": "red and white triangle with merging / narrow lanes warning",
+    "25": "red and white triangle with person digging / construction / road work warning",
+    "26": "red and white triangle with traffic light approaching warning",
+    "27": "red and white triangle with person walking warning",
+    "28": "red and white triangle with child and person walking warning",
+    "29": "red and white triangle with bicyle warning",
+    "30": "red and white triangle with snowflake / ice warning",
+    "31": "red and white triangle with deer warning",
+    "32": "white circle with gray strike bar no speed limit",
+    "33": "blue circle with white right turn arrow mandatory",
+    "34": "blue circle with white left turn arrow mandatory",
+    "35": "blue circle with white forward arrow mandatory",
+    "36": "blue circle with white forward or right turn arrow mandatory",
+    "37": "blue circle with white forward or left turn arrow mandatory",
+    "38": "blue circle with white keep right arrow mandatory",
+    "39": "blue circle with white keep left arrow mandatory",
+    "40": "blue circle with white arrows indicating a traffic circle",
+    "41": "white circle with gray strike bar indicating no passing for cars has ended",
+    "42": "white circle with gray strike bar indicating no passing for trucks has ended"
+  },
+  "label2id": {
+    "blue circle with white arrows indicating a traffic circle": 40,
+    "blue circle with white forward arrow mandatory": 35,
+    "blue circle with white forward or left turn arrow mandatory": 37,
+    "blue circle with white forward or right turn arrow mandatory": 36,
+    "blue circle with white keep left arrow mandatory": 39,
+    "blue circle with white keep right arrow mandatory": 38,
+    "blue circle with white left turn arrow mandatory": 34,
+    "blue circle with white right turn arrow mandatory": 33,
+    "empty red and white circle": 15,
+    "end / de-restriction of 80 kph speed limit": 6,
+    "red and white circle 100 kph speed limit": 7,
+    "red and white circle 120 kph speed limit": 8,
+    "red and white circle 20 kph speed limit": 0,
+    "red and white circle 30 kph speed limit": 1,
+    "red and white circle 50 kph speed limit": 2,
+    "red and white circle 60 kph speed limit": 3,
+    "red and white circle 70 kph speed limit": 4,
+    "red and white circle 80 kph speed limit": 5,
+    "red and white circle no truck entry": 16,
+    "red and white circle red car and black car no passing": 9,
+    "red and white circle red truck and black car no passing": 10,
+    "red and white triangle car skidding / slipping warning": 23,
+    "red and white triangle road intersection warning": 11,
+    "red and white triangle rough / bumpy road warning": 22,
+    "red and white triangle with bicyle warning": 29,
+    "red and white triangle with black double curve approaching warning": 21,
+    "red and white triangle with black left curve approaching warning": 19,
+    "red and white triangle with black right curve approaching warning": 20,
+    "red and white triangle with child and person walking warning": 28,
+    "red and white triangle with deer warning": 31,
+    "red and white triangle with exclamation mark warning": 18,
+    "red and white triangle with merging / narrow lanes warning": 24,
+    "red and white triangle with person digging / construction / road work warning": 25,
+    "red and white triangle with person walking warning": 27,
+    "red and white triangle with snowflake / ice warning": 30,
+    "red and white triangle with traffic light approaching warning": 26,
+    "red and white upside down triangle yield right-of-way": 13,
+    "red circle with white horizonal stripe no entry": 17,
+    "stop": 14,
+    "white and yellow diamond priority road": 12,
+    "white circle with gray strike bar indicating no passing for cars has ended": 41,
+    "white circle with gray strike bar indicating no passing for trucks has ended": 42,
+    "white circle with gray strike bar no speed limit": 32
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/README.md b/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..4d44f60f2716eb75762585d5422186a2d4b43b34
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset gtsrb.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: gtsrb
+    pretrained: true
+test_datasets: null
+train_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: train
+type: transformers
+val_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: test
+```
+
diff --git a/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/config.json b/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..53161b832eb7e51bd11bce461528d4642c58be00
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,129 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "red and white circle 20 kph speed limit",
+    "1": "red and white circle 30 kph speed limit",
+    "2": "red and white circle 50 kph speed limit",
+    "3": "red and white circle 60 kph speed limit",
+    "4": "red and white circle 70 kph speed limit",
+    "5": "red and white circle 80 kph speed limit",
+    "6": "end / de-restriction of 80 kph speed limit",
+    "7": "red and white circle 100 kph speed limit",
+    "8": "red and white circle 120 kph speed limit",
+    "9": "red and white circle red car and black car no passing",
+    "10": "red and white circle red truck and black car no passing",
+    "11": "red and white triangle road intersection warning",
+    "12": "white and yellow diamond priority road",
+    "13": "red and white upside down triangle yield right-of-way",
+    "14": "stop",
+    "15": "empty red and white circle",
+    "16": "red and white circle no truck entry",
+    "17": "red circle with white horizonal stripe no entry",
+    "18": "red and white triangle with exclamation mark warning",
+    "19": "red and white triangle with black left curve approaching warning",
+    "20": "red and white triangle with black right curve approaching warning",
+    "21": "red and white triangle with black double curve approaching warning",
+    "22": "red and white triangle rough / bumpy road warning",
+    "23": "red and white triangle car skidding / slipping warning",
+    "24": "red and white triangle with merging / narrow lanes warning",
+    "25": "red and white triangle with person digging / construction / road work warning",
+    "26": "red and white triangle with traffic light approaching warning",
+    "27": "red and white triangle with person walking warning",
+    "28": "red and white triangle with child and person walking warning",
+    "29": "red and white triangle with bicyle warning",
+    "30": "red and white triangle with snowflake / ice warning",
+    "31": "red and white triangle with deer warning",
+    "32": "white circle with gray strike bar no speed limit",
+    "33": "blue circle with white right turn arrow mandatory",
+    "34": "blue circle with white left turn arrow mandatory",
+    "35": "blue circle with white forward arrow mandatory",
+    "36": "blue circle with white forward or right turn arrow mandatory",
+    "37": "blue circle with white forward or left turn arrow mandatory",
+    "38": "blue circle with white keep right arrow mandatory",
+    "39": "blue circle with white keep left arrow mandatory",
+    "40": "blue circle with white arrows indicating a traffic circle",
+    "41": "white circle with gray strike bar indicating no passing for cars has ended",
+    "42": "white circle with gray strike bar indicating no passing for trucks has ended"
+  },
+  "label2id": {
+    "blue circle with white arrows indicating a traffic circle": 40,
+    "blue circle with white forward arrow mandatory": 35,
+    "blue circle with white forward or left turn arrow mandatory": 37,
+    "blue circle with white forward or right turn arrow mandatory": 36,
+    "blue circle with white keep left arrow mandatory": 39,
+    "blue circle with white keep right arrow mandatory": 38,
+    "blue circle with white left turn arrow mandatory": 34,
+    "blue circle with white right turn arrow mandatory": 33,
+    "empty red and white circle": 15,
+    "end / de-restriction of 80 kph speed limit": 6,
+    "red and white circle 100 kph speed limit": 7,
+    "red and white circle 120 kph speed limit": 8,
+    "red and white circle 20 kph speed limit": 0,
+    "red and white circle 30 kph speed limit": 1,
+    "red and white circle 50 kph speed limit": 2,
+    "red and white circle 60 kph speed limit": 3,
+    "red and white circle 70 kph speed limit": 4,
+    "red and white circle 80 kph speed limit": 5,
+    "red and white circle no truck entry": 16,
+    "red and white circle red car and black car no passing": 9,
+    "red and white circle red truck and black car no passing": 10,
+    "red and white triangle car skidding / slipping warning": 23,
+    "red and white triangle road intersection warning": 11,
+    "red and white triangle rough / bumpy road warning": 22,
+    "red and white triangle with bicyle warning": 29,
+    "red and white triangle with black double curve approaching warning": 21,
+    "red and white triangle with black left curve approaching warning": 19,
+    "red and white triangle with black right curve approaching warning": 20,
+    "red and white triangle with child and person walking warning": 28,
+    "red and white triangle with deer warning": 31,
+    "red and white triangle with exclamation mark warning": 18,
+    "red and white triangle with merging / narrow lanes warning": 24,
+    "red and white triangle with person digging / construction / road work warning": 25,
+    "red and white triangle with person walking warning": 27,
+    "red and white triangle with snowflake / ice warning": 30,
+    "red and white triangle with traffic light approaching warning": 26,
+    "red and white upside down triangle yield right-of-way": 13,
+    "red circle with white horizonal stripe no entry": 17,
+    "stop": 14,
+    "white and yellow diamond priority road": 12,
+    "white circle with gray strike bar indicating no passing for cars has ended": 41,
+    "white circle with gray strike bar indicating no passing for trucks has ended": 42,
+    "white circle with gray strike bar no speed limit": 32
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/README.md b/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..4d44f60f2716eb75762585d5422186a2d4b43b34
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset gtsrb.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: gtsrb
+    pretrained: true
+test_datasets: null
+train_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: train
+type: transformers
+val_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: test
+```
+
diff --git a/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/config.json b/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..53161b832eb7e51bd11bce461528d4642c58be00
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,129 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "red and white circle 20 kph speed limit",
+    "1": "red and white circle 30 kph speed limit",
+    "2": "red and white circle 50 kph speed limit",
+    "3": "red and white circle 60 kph speed limit",
+    "4": "red and white circle 70 kph speed limit",
+    "5": "red and white circle 80 kph speed limit",
+    "6": "end / de-restriction of 80 kph speed limit",
+    "7": "red and white circle 100 kph speed limit",
+    "8": "red and white circle 120 kph speed limit",
+    "9": "red and white circle red car and black car no passing",
+    "10": "red and white circle red truck and black car no passing",
+    "11": "red and white triangle road intersection warning",
+    "12": "white and yellow diamond priority road",
+    "13": "red and white upside down triangle yield right-of-way",
+    "14": "stop",
+    "15": "empty red and white circle",
+    "16": "red and white circle no truck entry",
+    "17": "red circle with white horizonal stripe no entry",
+    "18": "red and white triangle with exclamation mark warning",
+    "19": "red and white triangle with black left curve approaching warning",
+    "20": "red and white triangle with black right curve approaching warning",
+    "21": "red and white triangle with black double curve approaching warning",
+    "22": "red and white triangle rough / bumpy road warning",
+    "23": "red and white triangle car skidding / slipping warning",
+    "24": "red and white triangle with merging / narrow lanes warning",
+    "25": "red and white triangle with person digging / construction / road work warning",
+    "26": "red and white triangle with traffic light approaching warning",
+    "27": "red and white triangle with person walking warning",
+    "28": "red and white triangle with child and person walking warning",
+    "29": "red and white triangle with bicyle warning",
+    "30": "red and white triangle with snowflake / ice warning",
+    "31": "red and white triangle with deer warning",
+    "32": "white circle with gray strike bar no speed limit",
+    "33": "blue circle with white right turn arrow mandatory",
+    "34": "blue circle with white left turn arrow mandatory",
+    "35": "blue circle with white forward arrow mandatory",
+    "36": "blue circle with white forward or right turn arrow mandatory",
+    "37": "blue circle with white forward or left turn arrow mandatory",
+    "38": "blue circle with white keep right arrow mandatory",
+    "39": "blue circle with white keep left arrow mandatory",
+    "40": "blue circle with white arrows indicating a traffic circle",
+    "41": "white circle with gray strike bar indicating no passing for cars has ended",
+    "42": "white circle with gray strike bar indicating no passing for trucks has ended"
+  },
+  "label2id": {
+    "blue circle with white arrows indicating a traffic circle": 40,
+    "blue circle with white forward arrow mandatory": 35,
+    "blue circle with white forward or left turn arrow mandatory": 37,
+    "blue circle with white forward or right turn arrow mandatory": 36,
+    "blue circle with white keep left arrow mandatory": 39,
+    "blue circle with white keep right arrow mandatory": 38,
+    "blue circle with white left turn arrow mandatory": 34,
+    "blue circle with white right turn arrow mandatory": 33,
+    "empty red and white circle": 15,
+    "end / de-restriction of 80 kph speed limit": 6,
+    "red and white circle 100 kph speed limit": 7,
+    "red and white circle 120 kph speed limit": 8,
+    "red and white circle 20 kph speed limit": 0,
+    "red and white circle 30 kph speed limit": 1,
+    "red and white circle 50 kph speed limit": 2,
+    "red and white circle 60 kph speed limit": 3,
+    "red and white circle 70 kph speed limit": 4,
+    "red and white circle 80 kph speed limit": 5,
+    "red and white circle no truck entry": 16,
+    "red and white circle red car and black car no passing": 9,
+    "red and white circle red truck and black car no passing": 10,
+    "red and white triangle car skidding / slipping warning": 23,
+    "red and white triangle road intersection warning": 11,
+    "red and white triangle rough / bumpy road warning": 22,
+    "red and white triangle with bicyle warning": 29,
+    "red and white triangle with black double curve approaching warning": 21,
+    "red and white triangle with black left curve approaching warning": 19,
+    "red and white triangle with black right curve approaching warning": 20,
+    "red and white triangle with child and person walking warning": 28,
+    "red and white triangle with deer warning": 31,
+    "red and white triangle with exclamation mark warning": 18,
+    "red and white triangle with merging / narrow lanes warning": 24,
+    "red and white triangle with person digging / construction / road work warning": 25,
+    "red and white triangle with person walking warning": 27,
+    "red and white triangle with snowflake / ice warning": 30,
+    "red and white triangle with traffic light approaching warning": 26,
+    "red and white upside down triangle yield right-of-way": 13,
+    "red circle with white horizonal stripe no entry": 17,
+    "stop": 14,
+    "white and yellow diamond priority road": 12,
+    "white circle with gray strike bar indicating no passing for cars has ended": 41,
+    "white circle with gray strike bar indicating no passing for trucks has ended": 42,
+    "white circle with gray strike bar no speed limit": 32
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/README.md b/resnet152-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..a39e299d867f4b259bf762dcd31b3224f849c735
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset gtsrb.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: gtsrb
+    pretrained: true
+test_datasets: null
+train_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: train
+type: transformers
+val_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: test
+```
+
diff --git a/resnet152-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/config.json b/resnet152-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..53161b832eb7e51bd11bce461528d4642c58be00
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,129 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "red and white circle 20 kph speed limit",
+    "1": "red and white circle 30 kph speed limit",
+    "2": "red and white circle 50 kph speed limit",
+    "3": "red and white circle 60 kph speed limit",
+    "4": "red and white circle 70 kph speed limit",
+    "5": "red and white circle 80 kph speed limit",
+    "6": "end / de-restriction of 80 kph speed limit",
+    "7": "red and white circle 100 kph speed limit",
+    "8": "red and white circle 120 kph speed limit",
+    "9": "red and white circle red car and black car no passing",
+    "10": "red and white circle red truck and black car no passing",
+    "11": "red and white triangle road intersection warning",
+    "12": "white and yellow diamond priority road",
+    "13": "red and white upside down triangle yield right-of-way",
+    "14": "stop",
+    "15": "empty red and white circle",
+    "16": "red and white circle no truck entry",
+    "17": "red circle with white horizonal stripe no entry",
+    "18": "red and white triangle with exclamation mark warning",
+    "19": "red and white triangle with black left curve approaching warning",
+    "20": "red and white triangle with black right curve approaching warning",
+    "21": "red and white triangle with black double curve approaching warning",
+    "22": "red and white triangle rough / bumpy road warning",
+    "23": "red and white triangle car skidding / slipping warning",
+    "24": "red and white triangle with merging / narrow lanes warning",
+    "25": "red and white triangle with person digging / construction / road work warning",
+    "26": "red and white triangle with traffic light approaching warning",
+    "27": "red and white triangle with person walking warning",
+    "28": "red and white triangle with child and person walking warning",
+    "29": "red and white triangle with bicyle warning",
+    "30": "red and white triangle with snowflake / ice warning",
+    "31": "red and white triangle with deer warning",
+    "32": "white circle with gray strike bar no speed limit",
+    "33": "blue circle with white right turn arrow mandatory",
+    "34": "blue circle with white left turn arrow mandatory",
+    "35": "blue circle with white forward arrow mandatory",
+    "36": "blue circle with white forward or right turn arrow mandatory",
+    "37": "blue circle with white forward or left turn arrow mandatory",
+    "38": "blue circle with white keep right arrow mandatory",
+    "39": "blue circle with white keep left arrow mandatory",
+    "40": "blue circle with white arrows indicating a traffic circle",
+    "41": "white circle with gray strike bar indicating no passing for cars has ended",
+    "42": "white circle with gray strike bar indicating no passing for trucks has ended"
+  },
+  "label2id": {
+    "blue circle with white arrows indicating a traffic circle": 40,
+    "blue circle with white forward arrow mandatory": 35,
+    "blue circle with white forward or left turn arrow mandatory": 37,
+    "blue circle with white forward or right turn arrow mandatory": 36,
+    "blue circle with white keep left arrow mandatory": 39,
+    "blue circle with white keep right arrow mandatory": 38,
+    "blue circle with white left turn arrow mandatory": 34,
+    "blue circle with white right turn arrow mandatory": 33,
+    "empty red and white circle": 15,
+    "end / de-restriction of 80 kph speed limit": 6,
+    "red and white circle 100 kph speed limit": 7,
+    "red and white circle 120 kph speed limit": 8,
+    "red and white circle 20 kph speed limit": 0,
+    "red and white circle 30 kph speed limit": 1,
+    "red and white circle 50 kph speed limit": 2,
+    "red and white circle 60 kph speed limit": 3,
+    "red and white circle 70 kph speed limit": 4,
+    "red and white circle 80 kph speed limit": 5,
+    "red and white circle no truck entry": 16,
+    "red and white circle red car and black car no passing": 9,
+    "red and white circle red truck and black car no passing": 10,
+    "red and white triangle car skidding / slipping warning": 23,
+    "red and white triangle road intersection warning": 11,
+    "red and white triangle rough / bumpy road warning": 22,
+    "red and white triangle with bicyle warning": 29,
+    "red and white triangle with black double curve approaching warning": 21,
+    "red and white triangle with black left curve approaching warning": 19,
+    "red and white triangle with black right curve approaching warning": 20,
+    "red and white triangle with child and person walking warning": 28,
+    "red and white triangle with deer warning": 31,
+    "red and white triangle with exclamation mark warning": 18,
+    "red and white triangle with merging / narrow lanes warning": 24,
+    "red and white triangle with person digging / construction / road work warning": 25,
+    "red and white triangle with person walking warning": 27,
+    "red and white triangle with snowflake / ice warning": 30,
+    "red and white triangle with traffic light approaching warning": 26,
+    "red and white upside down triangle yield right-of-way": 13,
+    "red circle with white horizonal stripe no entry": 17,
+    "stop": 14,
+    "white and yellow diamond priority road": 12,
+    "white circle with gray strike bar indicating no passing for cars has ended": 41,
+    "white circle with gray strike bar indicating no passing for trucks has ended": 42,
+    "white circle with gray strike bar no speed limit": 32
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet152-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-kmnist-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/README.md b/resnet152-kmnist-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..15fe64fba741cffe2ba9a1834c4ee5da05f642dc
--- /dev/null
+++ b/resnet152-kmnist-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset kmnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: kmnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: train
+type: transformers
+val_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: test
+```
+
diff --git a/resnet152-kmnist-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/config.json b/resnet152-kmnist-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..55c0a9dcaa76aba329cf2d4fb9ec5d866be9da8a
--- /dev/null
+++ b/resnet152-kmnist-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "\u304a",
+    "1": "\u304d",
+    "2": "\u3059",
+    "3": "\u3064",
+    "4": "\u306a",
+    "5": "\u306f",
+    "6": "\u307e",
+    "7": "\u3084",
+    "8": "\u308c",
+    "9": "\u3092"
+  },
+  "label2id": {
+    "\u304a": 0,
+    "\u304d": 1,
+    "\u3059": 2,
+    "\u3064": 3,
+    "\u306a": 4,
+    "\u306f": 5,
+    "\u307e": 6,
+    "\u3084": 7,
+    "\u308c": 8,
+    "\u3092": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-kmnist-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet152-kmnist-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-kmnist-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/README.md b/resnet152-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..9a935f5970e1b54f77121298f98d724a4ce3f886
--- /dev/null
+++ b/resnet152-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset kmnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: kmnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: train
+type: transformers
+val_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: test
+```
+
diff --git a/resnet152-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/config.json b/resnet152-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..55c0a9dcaa76aba329cf2d4fb9ec5d866be9da8a
--- /dev/null
+++ b/resnet152-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "\u304a",
+    "1": "\u304d",
+    "2": "\u3059",
+    "3": "\u3064",
+    "4": "\u306a",
+    "5": "\u306f",
+    "6": "\u307e",
+    "7": "\u3084",
+    "8": "\u308c",
+    "9": "\u3092"
+  },
+  "label2id": {
+    "\u304a": 0,
+    "\u304d": 1,
+    "\u3059": 2,
+    "\u3064": 3,
+    "\u306a": 4,
+    "\u306f": 5,
+    "\u307e": 6,
+    "\u3084": 7,
+    "\u308c": 8,
+    "\u3092": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet152-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-kmnist-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/README.md b/resnet152-kmnist-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..32cb5f82e9eec887acf3ab0a44e5a40941e85557
--- /dev/null
+++ b/resnet152-kmnist-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset kmnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: kmnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: train
+type: transformers
+val_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: test
+```
+
diff --git a/resnet152-kmnist-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/config.json b/resnet152-kmnist-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..55c0a9dcaa76aba329cf2d4fb9ec5d866be9da8a
--- /dev/null
+++ b/resnet152-kmnist-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "\u304a",
+    "1": "\u304d",
+    "2": "\u3059",
+    "3": "\u3064",
+    "4": "\u306a",
+    "5": "\u306f",
+    "6": "\u307e",
+    "7": "\u3084",
+    "8": "\u308c",
+    "9": "\u3092"
+  },
+  "label2id": {
+    "\u304a": 0,
+    "\u304d": 1,
+    "\u3059": 2,
+    "\u3064": 3,
+    "\u306a": 4,
+    "\u306f": 5,
+    "\u307e": 6,
+    "\u3084": 7,
+    "\u308c": 8,
+    "\u3092": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-kmnist-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet152-kmnist-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-kmnist-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/README.md b/resnet152-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..0b3997d5567c37e7f4d1aaff6c80b3903471d417
--- /dev/null
+++ b/resnet152-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset kmnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: kmnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: train
+type: transformers
+val_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: test
+```
+
diff --git a/resnet152-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/config.json b/resnet152-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..55c0a9dcaa76aba329cf2d4fb9ec5d866be9da8a
--- /dev/null
+++ b/resnet152-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "\u304a",
+    "1": "\u304d",
+    "2": "\u3059",
+    "3": "\u3064",
+    "4": "\u306a",
+    "5": "\u306f",
+    "6": "\u307e",
+    "7": "\u3084",
+    "8": "\u308c",
+    "9": "\u3092"
+  },
+  "label2id": {
+    "\u304a": 0,
+    "\u304d": 1,
+    "\u3059": 2,
+    "\u3064": 3,
+    "\u306a": 4,
+    "\u306f": 5,
+    "\u307e": 6,
+    "\u3084": 7,
+    "\u308c": 8,
+    "\u3092": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet152-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/README.md b/resnet152-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..0b3997d5567c37e7f4d1aaff6c80b3903471d417
--- /dev/null
+++ b/resnet152-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset kmnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: kmnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: train
+type: transformers
+val_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: test
+```
+
diff --git a/resnet152-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/config.json b/resnet152-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..55c0a9dcaa76aba329cf2d4fb9ec5d866be9da8a
--- /dev/null
+++ b/resnet152-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "\u304a",
+    "1": "\u304d",
+    "2": "\u3059",
+    "3": "\u3064",
+    "4": "\u306a",
+    "5": "\u306f",
+    "6": "\u307e",
+    "7": "\u3084",
+    "8": "\u308c",
+    "9": "\u3092"
+  },
+  "label2id": {
+    "\u304a": 0,
+    "\u304d": 1,
+    "\u3059": 2,
+    "\u3064": 3,
+    "\u306a": 4,
+    "\u306f": 5,
+    "\u307e": 6,
+    "\u3084": 7,
+    "\u308c": 8,
+    "\u3092": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet152-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/README.md b/resnet152-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..9a572d00727c0d13dda10becd6627f77bb078215
--- /dev/null
+++ b/resnet152-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: train
+type: transformers
+val_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: test
+```
+
diff --git a/resnet152-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/config.json b/resnet152-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..499ddc3e4e5dc0456a3110b1e6f22201afc1936e
--- /dev/null
+++ b/resnet152-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet152-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-mnist-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/README.md b/resnet152-mnist-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..b9ccd75309b5813728dd3c2664fa32cd4f0d66fc
--- /dev/null
+++ b/resnet152-mnist-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: train
+type: transformers
+val_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: test
+```
+
diff --git a/resnet152-mnist-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/config.json b/resnet152-mnist-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..499ddc3e4e5dc0456a3110b1e6f22201afc1936e
--- /dev/null
+++ b/resnet152-mnist-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-mnist-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet152-mnist-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-mnist-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/README.md b/resnet152-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..d9457c198fe08cd829fdebf0dcfe951a0a3db28a
--- /dev/null
+++ b/resnet152-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford-iiit-pet.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: oxford-iiit-pet
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford-iiit-pet:
+    _target_: datasets.load_dataset
+    path: timm/oxford-iiit-pet
+    split: train
+type: transformers
+val_datasets:
+  oxford-iiit-pet:
+    _target_: datasets.load_dataset
+    path: timm/oxford-iiit-pet
+    split: test
+```
+
diff --git a/resnet152-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/config.json b/resnet152-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..6e9072520d9ab1e64883a84e11a3a69f3f2a85ee
--- /dev/null
+++ b/resnet152-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,117 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "abyssinian",
+    "1": "american_bulldog",
+    "2": "american_pit_bull_terrier",
+    "3": "basset_hound",
+    "4": "beagle",
+    "5": "bengal",
+    "6": "birman",
+    "7": "bombay",
+    "8": "boxer",
+    "9": "british_shorthair",
+    "10": "chihuahua",
+    "11": "egyptian_mau",
+    "12": "english_cocker_spaniel",
+    "13": "english_setter",
+    "14": "german_shorthaired",
+    "15": "great_pyrenees",
+    "16": "havanese",
+    "17": "japanese_chin",
+    "18": "keeshond",
+    "19": "leonberger",
+    "20": "maine_coon",
+    "21": "miniature_pinscher",
+    "22": "newfoundland",
+    "23": "persian",
+    "24": "pomeranian",
+    "25": "pug",
+    "26": "ragdoll",
+    "27": "russian_blue",
+    "28": "saint_bernard",
+    "29": "samoyed",
+    "30": "scottish_terrier",
+    "31": "shiba_inu",
+    "32": "siamese",
+    "33": "sphynx",
+    "34": "staffordshire_bull_terrier",
+    "35": "wheaten_terrier",
+    "36": "yorkshire_terrier"
+  },
+  "label2id": {
+    "abyssinian": 0,
+    "american_bulldog": 1,
+    "american_pit_bull_terrier": 2,
+    "basset_hound": 3,
+    "beagle": 4,
+    "bengal": 5,
+    "birman": 6,
+    "bombay": 7,
+    "boxer": 8,
+    "british_shorthair": 9,
+    "chihuahua": 10,
+    "egyptian_mau": 11,
+    "english_cocker_spaniel": 12,
+    "english_setter": 13,
+    "german_shorthaired": 14,
+    "great_pyrenees": 15,
+    "havanese": 16,
+    "japanese_chin": 17,
+    "keeshond": 18,
+    "leonberger": 19,
+    "maine_coon": 20,
+    "miniature_pinscher": 21,
+    "newfoundland": 22,
+    "persian": 23,
+    "pomeranian": 24,
+    "pug": 25,
+    "ragdoll": 26,
+    "russian_blue": 27,
+    "saint_bernard": 28,
+    "samoyed": 29,
+    "scottish_terrier": 30,
+    "shiba_inu": 31,
+    "siamese": 32,
+    "sphynx": 33,
+    "staffordshire_bull_terrier": 34,
+    "wheaten_terrier": 35,
+    "yorkshire_terrier": 36
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet152-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/README.md b/resnet152-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..7fd252b1de8836bb8c78a962857fbf8f705485df
--- /dev/null
+++ b/resnet152-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford_flowers102.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: oxford_flowers102
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: train
+type: transformers
+val_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: test
+```
+
diff --git a/resnet152-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/config.json b/resnet152-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..73d4c5807d169cb2e901ab29de6ec9f57efd9347
--- /dev/null
+++ b/resnet152-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,247 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "pink primrose",
+    "1": "hard-leaved pocket orchid",
+    "2": "canterbury bells",
+    "3": "sweet pea",
+    "4": "english marigold",
+    "5": "tiger lily",
+    "6": "moon orchid",
+    "7": "bird of paradise",
+    "8": "monkshood",
+    "9": "globe thistle",
+    "10": "snapdragon",
+    "11": "colt's foot",
+    "12": "king protea",
+    "13": "spear thistle",
+    "14": "yellow iris",
+    "15": "globe-flower",
+    "16": "purple coneflower",
+    "17": "peruvian lily",
+    "18": "balloon flower",
+    "19": "giant white arum lily",
+    "20": "fire lily",
+    "21": "pincushion flower",
+    "22": "fritillary",
+    "23": "red ginger",
+    "24": "grape hyacinth",
+    "25": "corn poppy",
+    "26": "prince of wales feathers",
+    "27": "stemless gentian",
+    "28": "artichoke",
+    "29": "sweet william",
+    "30": "carnation",
+    "31": "garden phlox",
+    "32": "love in the mist",
+    "33": "mexican aster",
+    "34": "alpine sea holly",
+    "35": "ruby-lipped cattleya",
+    "36": "cape flower",
+    "37": "great masterwort",
+    "38": "siam tulip",
+    "39": "lenten rose",
+    "40": "barbeton daisy",
+    "41": "daffodil",
+    "42": "sword lily",
+    "43": "poinsettia",
+    "44": "bolero deep blue",
+    "45": "wallflower",
+    "46": "marigold",
+    "47": "buttercup",
+    "48": "oxeye daisy",
+    "49": "common dandelion",
+    "50": "petunia",
+    "51": "wild pansy",
+    "52": "primula",
+    "53": "sunflower",
+    "54": "pelargonium",
+    "55": "bishop of llandaff",
+    "56": "gaura",
+    "57": "geranium",
+    "58": "orange dahlia",
+    "59": "pink-yellow dahlia?",
+    "60": "cautleya spicata",
+    "61": "japanese anemone",
+    "62": "black-eyed susan",
+    "63": "silverbush",
+    "64": "californian poppy",
+    "65": "osteospermum",
+    "66": "spring crocus",
+    "67": "bearded iris",
+    "68": "windflower",
+    "69": "tree poppy",
+    "70": "gazania",
+    "71": "azalea",
+    "72": "water lily",
+    "73": "rose",
+    "74": "thorn apple",
+    "75": "morning glory",
+    "76": "passion flower",
+    "77": "lotus",
+    "78": "toad lily",
+    "79": "anthurium",
+    "80": "frangipani",
+    "81": "clematis",
+    "82": "hibiscus",
+    "83": "columbine",
+    "84": "desert-rose",
+    "85": "tree mallow",
+    "86": "magnolia",
+    "87": "cyclamen",
+    "88": "watercress",
+    "89": "canna lily",
+    "90": "hippeastrum",
+    "91": "bee balm",
+    "92": "ball moss",
+    "93": "foxglove",
+    "94": "bougainvillea",
+    "95": "camellia",
+    "96": "mallow",
+    "97": "mexican petunia",
+    "98": "bromelia",
+    "99": "blanket flower",
+    "100": "trumpet creeper",
+    "101": "blackberry lily"
+  },
+  "label2id": {
+    "alpine sea holly": 34,
+    "anthurium": 79,
+    "artichoke": 28,
+    "azalea": 71,
+    "ball moss": 92,
+    "balloon flower": 18,
+    "barbeton daisy": 40,
+    "bearded iris": 67,
+    "bee balm": 91,
+    "bird of paradise": 7,
+    "bishop of llandaff": 55,
+    "black-eyed susan": 62,
+    "blackberry lily": 101,
+    "blanket flower": 99,
+    "bolero deep blue": 44,
+    "bougainvillea": 94,
+    "bromelia": 98,
+    "buttercup": 47,
+    "californian poppy": 64,
+    "camellia": 95,
+    "canna lily": 89,
+    "canterbury bells": 2,
+    "cape flower": 36,
+    "carnation": 30,
+    "cautleya spicata": 60,
+    "clematis": 81,
+    "colt's foot": 11,
+    "columbine": 83,
+    "common dandelion": 49,
+    "corn poppy": 25,
+    "cyclamen": 87,
+    "daffodil": 41,
+    "desert-rose": 84,
+    "english marigold": 4,
+    "fire lily": 20,
+    "foxglove": 93,
+    "frangipani": 80,
+    "fritillary": 22,
+    "garden phlox": 31,
+    "gaura": 56,
+    "gazania": 70,
+    "geranium": 57,
+    "giant white arum lily": 19,
+    "globe thistle": 9,
+    "globe-flower": 15,
+    "grape hyacinth": 24,
+    "great masterwort": 37,
+    "hard-leaved pocket orchid": 1,
+    "hibiscus": 82,
+    "hippeastrum": 90,
+    "japanese anemone": 61,
+    "king protea": 12,
+    "lenten rose": 39,
+    "lotus": 77,
+    "love in the mist": 32,
+    "magnolia": 86,
+    "mallow": 96,
+    "marigold": 46,
+    "mexican aster": 33,
+    "mexican petunia": 97,
+    "monkshood": 8,
+    "moon orchid": 6,
+    "morning glory": 75,
+    "orange dahlia": 58,
+    "osteospermum": 65,
+    "oxeye daisy": 48,
+    "passion flower": 76,
+    "pelargonium": 54,
+    "peruvian lily": 17,
+    "petunia": 50,
+    "pincushion flower": 21,
+    "pink primrose": 0,
+    "pink-yellow dahlia?": 59,
+    "poinsettia": 43,
+    "primula": 52,
+    "prince of wales feathers": 26,
+    "purple coneflower": 16,
+    "red ginger": 23,
+    "rose": 73,
+    "ruby-lipped cattleya": 35,
+    "siam tulip": 38,
+    "silverbush": 63,
+    "snapdragon": 10,
+    "spear thistle": 13,
+    "spring crocus": 66,
+    "stemless gentian": 27,
+    "sunflower": 53,
+    "sweet pea": 3,
+    "sweet william": 29,
+    "sword lily": 42,
+    "thorn apple": 74,
+    "tiger lily": 5,
+    "toad lily": 78,
+    "tree mallow": 85,
+    "tree poppy": 69,
+    "trumpet creeper": 100,
+    "wallflower": 45,
+    "water lily": 72,
+    "watercress": 88,
+    "wild pansy": 51,
+    "windflower": 68,
+    "yellow iris": 14
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet152-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/README.md b/resnet152-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..3060ceffc421b8c4933556e95e4b3bb7ef8b2b1f
--- /dev/null
+++ b/resnet152-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford_flowers102.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: oxford_flowers102
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: train
+type: transformers
+val_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: test
+```
+
diff --git a/resnet152-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/config.json b/resnet152-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..73d4c5807d169cb2e901ab29de6ec9f57efd9347
--- /dev/null
+++ b/resnet152-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,247 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "pink primrose",
+    "1": "hard-leaved pocket orchid",
+    "2": "canterbury bells",
+    "3": "sweet pea",
+    "4": "english marigold",
+    "5": "tiger lily",
+    "6": "moon orchid",
+    "7": "bird of paradise",
+    "8": "monkshood",
+    "9": "globe thistle",
+    "10": "snapdragon",
+    "11": "colt's foot",
+    "12": "king protea",
+    "13": "spear thistle",
+    "14": "yellow iris",
+    "15": "globe-flower",
+    "16": "purple coneflower",
+    "17": "peruvian lily",
+    "18": "balloon flower",
+    "19": "giant white arum lily",
+    "20": "fire lily",
+    "21": "pincushion flower",
+    "22": "fritillary",
+    "23": "red ginger",
+    "24": "grape hyacinth",
+    "25": "corn poppy",
+    "26": "prince of wales feathers",
+    "27": "stemless gentian",
+    "28": "artichoke",
+    "29": "sweet william",
+    "30": "carnation",
+    "31": "garden phlox",
+    "32": "love in the mist",
+    "33": "mexican aster",
+    "34": "alpine sea holly",
+    "35": "ruby-lipped cattleya",
+    "36": "cape flower",
+    "37": "great masterwort",
+    "38": "siam tulip",
+    "39": "lenten rose",
+    "40": "barbeton daisy",
+    "41": "daffodil",
+    "42": "sword lily",
+    "43": "poinsettia",
+    "44": "bolero deep blue",
+    "45": "wallflower",
+    "46": "marigold",
+    "47": "buttercup",
+    "48": "oxeye daisy",
+    "49": "common dandelion",
+    "50": "petunia",
+    "51": "wild pansy",
+    "52": "primula",
+    "53": "sunflower",
+    "54": "pelargonium",
+    "55": "bishop of llandaff",
+    "56": "gaura",
+    "57": "geranium",
+    "58": "orange dahlia",
+    "59": "pink-yellow dahlia?",
+    "60": "cautleya spicata",
+    "61": "japanese anemone",
+    "62": "black-eyed susan",
+    "63": "silverbush",
+    "64": "californian poppy",
+    "65": "osteospermum",
+    "66": "spring crocus",
+    "67": "bearded iris",
+    "68": "windflower",
+    "69": "tree poppy",
+    "70": "gazania",
+    "71": "azalea",
+    "72": "water lily",
+    "73": "rose",
+    "74": "thorn apple",
+    "75": "morning glory",
+    "76": "passion flower",
+    "77": "lotus",
+    "78": "toad lily",
+    "79": "anthurium",
+    "80": "frangipani",
+    "81": "clematis",
+    "82": "hibiscus",
+    "83": "columbine",
+    "84": "desert-rose",
+    "85": "tree mallow",
+    "86": "magnolia",
+    "87": "cyclamen",
+    "88": "watercress",
+    "89": "canna lily",
+    "90": "hippeastrum",
+    "91": "bee balm",
+    "92": "ball moss",
+    "93": "foxglove",
+    "94": "bougainvillea",
+    "95": "camellia",
+    "96": "mallow",
+    "97": "mexican petunia",
+    "98": "bromelia",
+    "99": "blanket flower",
+    "100": "trumpet creeper",
+    "101": "blackberry lily"
+  },
+  "label2id": {
+    "alpine sea holly": 34,
+    "anthurium": 79,
+    "artichoke": 28,
+    "azalea": 71,
+    "ball moss": 92,
+    "balloon flower": 18,
+    "barbeton daisy": 40,
+    "bearded iris": 67,
+    "bee balm": 91,
+    "bird of paradise": 7,
+    "bishop of llandaff": 55,
+    "black-eyed susan": 62,
+    "blackberry lily": 101,
+    "blanket flower": 99,
+    "bolero deep blue": 44,
+    "bougainvillea": 94,
+    "bromelia": 98,
+    "buttercup": 47,
+    "californian poppy": 64,
+    "camellia": 95,
+    "canna lily": 89,
+    "canterbury bells": 2,
+    "cape flower": 36,
+    "carnation": 30,
+    "cautleya spicata": 60,
+    "clematis": 81,
+    "colt's foot": 11,
+    "columbine": 83,
+    "common dandelion": 49,
+    "corn poppy": 25,
+    "cyclamen": 87,
+    "daffodil": 41,
+    "desert-rose": 84,
+    "english marigold": 4,
+    "fire lily": 20,
+    "foxglove": 93,
+    "frangipani": 80,
+    "fritillary": 22,
+    "garden phlox": 31,
+    "gaura": 56,
+    "gazania": 70,
+    "geranium": 57,
+    "giant white arum lily": 19,
+    "globe thistle": 9,
+    "globe-flower": 15,
+    "grape hyacinth": 24,
+    "great masterwort": 37,
+    "hard-leaved pocket orchid": 1,
+    "hibiscus": 82,
+    "hippeastrum": 90,
+    "japanese anemone": 61,
+    "king protea": 12,
+    "lenten rose": 39,
+    "lotus": 77,
+    "love in the mist": 32,
+    "magnolia": 86,
+    "mallow": 96,
+    "marigold": 46,
+    "mexican aster": 33,
+    "mexican petunia": 97,
+    "monkshood": 8,
+    "moon orchid": 6,
+    "morning glory": 75,
+    "orange dahlia": 58,
+    "osteospermum": 65,
+    "oxeye daisy": 48,
+    "passion flower": 76,
+    "pelargonium": 54,
+    "peruvian lily": 17,
+    "petunia": 50,
+    "pincushion flower": 21,
+    "pink primrose": 0,
+    "pink-yellow dahlia?": 59,
+    "poinsettia": 43,
+    "primula": 52,
+    "prince of wales feathers": 26,
+    "purple coneflower": 16,
+    "red ginger": 23,
+    "rose": 73,
+    "ruby-lipped cattleya": 35,
+    "siam tulip": 38,
+    "silverbush": 63,
+    "snapdragon": 10,
+    "spear thistle": 13,
+    "spring crocus": 66,
+    "stemless gentian": 27,
+    "sunflower": 53,
+    "sweet pea": 3,
+    "sweet william": 29,
+    "sword lily": 42,
+    "thorn apple": 74,
+    "tiger lily": 5,
+    "toad lily": 78,
+    "tree mallow": 85,
+    "tree poppy": 69,
+    "trumpet creeper": 100,
+    "wallflower": 45,
+    "water lily": 72,
+    "watercress": 88,
+    "wild pansy": 51,
+    "windflower": 68,
+    "yellow iris": 14
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet152-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/README.md b/resnet152-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..227c796b4a5388c3a5e39990b92db6b163cf1298
--- /dev/null
+++ b/resnet152-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford_flowers102.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: oxford_flowers102
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: train
+type: transformers
+val_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: test
+```
+
diff --git a/resnet152-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/config.json b/resnet152-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..73d4c5807d169cb2e901ab29de6ec9f57efd9347
--- /dev/null
+++ b/resnet152-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,247 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "pink primrose",
+    "1": "hard-leaved pocket orchid",
+    "2": "canterbury bells",
+    "3": "sweet pea",
+    "4": "english marigold",
+    "5": "tiger lily",
+    "6": "moon orchid",
+    "7": "bird of paradise",
+    "8": "monkshood",
+    "9": "globe thistle",
+    "10": "snapdragon",
+    "11": "colt's foot",
+    "12": "king protea",
+    "13": "spear thistle",
+    "14": "yellow iris",
+    "15": "globe-flower",
+    "16": "purple coneflower",
+    "17": "peruvian lily",
+    "18": "balloon flower",
+    "19": "giant white arum lily",
+    "20": "fire lily",
+    "21": "pincushion flower",
+    "22": "fritillary",
+    "23": "red ginger",
+    "24": "grape hyacinth",
+    "25": "corn poppy",
+    "26": "prince of wales feathers",
+    "27": "stemless gentian",
+    "28": "artichoke",
+    "29": "sweet william",
+    "30": "carnation",
+    "31": "garden phlox",
+    "32": "love in the mist",
+    "33": "mexican aster",
+    "34": "alpine sea holly",
+    "35": "ruby-lipped cattleya",
+    "36": "cape flower",
+    "37": "great masterwort",
+    "38": "siam tulip",
+    "39": "lenten rose",
+    "40": "barbeton daisy",
+    "41": "daffodil",
+    "42": "sword lily",
+    "43": "poinsettia",
+    "44": "bolero deep blue",
+    "45": "wallflower",
+    "46": "marigold",
+    "47": "buttercup",
+    "48": "oxeye daisy",
+    "49": "common dandelion",
+    "50": "petunia",
+    "51": "wild pansy",
+    "52": "primula",
+    "53": "sunflower",
+    "54": "pelargonium",
+    "55": "bishop of llandaff",
+    "56": "gaura",
+    "57": "geranium",
+    "58": "orange dahlia",
+    "59": "pink-yellow dahlia?",
+    "60": "cautleya spicata",
+    "61": "japanese anemone",
+    "62": "black-eyed susan",
+    "63": "silverbush",
+    "64": "californian poppy",
+    "65": "osteospermum",
+    "66": "spring crocus",
+    "67": "bearded iris",
+    "68": "windflower",
+    "69": "tree poppy",
+    "70": "gazania",
+    "71": "azalea",
+    "72": "water lily",
+    "73": "rose",
+    "74": "thorn apple",
+    "75": "morning glory",
+    "76": "passion flower",
+    "77": "lotus",
+    "78": "toad lily",
+    "79": "anthurium",
+    "80": "frangipani",
+    "81": "clematis",
+    "82": "hibiscus",
+    "83": "columbine",
+    "84": "desert-rose",
+    "85": "tree mallow",
+    "86": "magnolia",
+    "87": "cyclamen",
+    "88": "watercress",
+    "89": "canna lily",
+    "90": "hippeastrum",
+    "91": "bee balm",
+    "92": "ball moss",
+    "93": "foxglove",
+    "94": "bougainvillea",
+    "95": "camellia",
+    "96": "mallow",
+    "97": "mexican petunia",
+    "98": "bromelia",
+    "99": "blanket flower",
+    "100": "trumpet creeper",
+    "101": "blackberry lily"
+  },
+  "label2id": {
+    "alpine sea holly": 34,
+    "anthurium": 79,
+    "artichoke": 28,
+    "azalea": 71,
+    "ball moss": 92,
+    "balloon flower": 18,
+    "barbeton daisy": 40,
+    "bearded iris": 67,
+    "bee balm": 91,
+    "bird of paradise": 7,
+    "bishop of llandaff": 55,
+    "black-eyed susan": 62,
+    "blackberry lily": 101,
+    "blanket flower": 99,
+    "bolero deep blue": 44,
+    "bougainvillea": 94,
+    "bromelia": 98,
+    "buttercup": 47,
+    "californian poppy": 64,
+    "camellia": 95,
+    "canna lily": 89,
+    "canterbury bells": 2,
+    "cape flower": 36,
+    "carnation": 30,
+    "cautleya spicata": 60,
+    "clematis": 81,
+    "colt's foot": 11,
+    "columbine": 83,
+    "common dandelion": 49,
+    "corn poppy": 25,
+    "cyclamen": 87,
+    "daffodil": 41,
+    "desert-rose": 84,
+    "english marigold": 4,
+    "fire lily": 20,
+    "foxglove": 93,
+    "frangipani": 80,
+    "fritillary": 22,
+    "garden phlox": 31,
+    "gaura": 56,
+    "gazania": 70,
+    "geranium": 57,
+    "giant white arum lily": 19,
+    "globe thistle": 9,
+    "globe-flower": 15,
+    "grape hyacinth": 24,
+    "great masterwort": 37,
+    "hard-leaved pocket orchid": 1,
+    "hibiscus": 82,
+    "hippeastrum": 90,
+    "japanese anemone": 61,
+    "king protea": 12,
+    "lenten rose": 39,
+    "lotus": 77,
+    "love in the mist": 32,
+    "magnolia": 86,
+    "mallow": 96,
+    "marigold": 46,
+    "mexican aster": 33,
+    "mexican petunia": 97,
+    "monkshood": 8,
+    "moon orchid": 6,
+    "morning glory": 75,
+    "orange dahlia": 58,
+    "osteospermum": 65,
+    "oxeye daisy": 48,
+    "passion flower": 76,
+    "pelargonium": 54,
+    "peruvian lily": 17,
+    "petunia": 50,
+    "pincushion flower": 21,
+    "pink primrose": 0,
+    "pink-yellow dahlia?": 59,
+    "poinsettia": 43,
+    "primula": 52,
+    "prince of wales feathers": 26,
+    "purple coneflower": 16,
+    "red ginger": 23,
+    "rose": 73,
+    "ruby-lipped cattleya": 35,
+    "siam tulip": 38,
+    "silverbush": 63,
+    "snapdragon": 10,
+    "spear thistle": 13,
+    "spring crocus": 66,
+    "stemless gentian": 27,
+    "sunflower": 53,
+    "sweet pea": 3,
+    "sweet william": 29,
+    "sword lily": 42,
+    "thorn apple": 74,
+    "tiger lily": 5,
+    "toad lily": 78,
+    "tree mallow": 85,
+    "tree poppy": 69,
+    "trumpet creeper": 100,
+    "wallflower": 45,
+    "water lily": 72,
+    "watercress": 88,
+    "wild pansy": 51,
+    "windflower": 68,
+    "yellow iris": 14
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet152-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/README.md b/resnet152-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..4eddf1f4a4c3924d59fe6ecce762e485b7fb150f
--- /dev/null
+++ b/resnet152-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford_flowers102.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: oxford_flowers102
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: train
+type: transformers
+val_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: test
+```
+
diff --git a/resnet152-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/config.json b/resnet152-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..73d4c5807d169cb2e901ab29de6ec9f57efd9347
--- /dev/null
+++ b/resnet152-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,247 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "pink primrose",
+    "1": "hard-leaved pocket orchid",
+    "2": "canterbury bells",
+    "3": "sweet pea",
+    "4": "english marigold",
+    "5": "tiger lily",
+    "6": "moon orchid",
+    "7": "bird of paradise",
+    "8": "monkshood",
+    "9": "globe thistle",
+    "10": "snapdragon",
+    "11": "colt's foot",
+    "12": "king protea",
+    "13": "spear thistle",
+    "14": "yellow iris",
+    "15": "globe-flower",
+    "16": "purple coneflower",
+    "17": "peruvian lily",
+    "18": "balloon flower",
+    "19": "giant white arum lily",
+    "20": "fire lily",
+    "21": "pincushion flower",
+    "22": "fritillary",
+    "23": "red ginger",
+    "24": "grape hyacinth",
+    "25": "corn poppy",
+    "26": "prince of wales feathers",
+    "27": "stemless gentian",
+    "28": "artichoke",
+    "29": "sweet william",
+    "30": "carnation",
+    "31": "garden phlox",
+    "32": "love in the mist",
+    "33": "mexican aster",
+    "34": "alpine sea holly",
+    "35": "ruby-lipped cattleya",
+    "36": "cape flower",
+    "37": "great masterwort",
+    "38": "siam tulip",
+    "39": "lenten rose",
+    "40": "barbeton daisy",
+    "41": "daffodil",
+    "42": "sword lily",
+    "43": "poinsettia",
+    "44": "bolero deep blue",
+    "45": "wallflower",
+    "46": "marigold",
+    "47": "buttercup",
+    "48": "oxeye daisy",
+    "49": "common dandelion",
+    "50": "petunia",
+    "51": "wild pansy",
+    "52": "primula",
+    "53": "sunflower",
+    "54": "pelargonium",
+    "55": "bishop of llandaff",
+    "56": "gaura",
+    "57": "geranium",
+    "58": "orange dahlia",
+    "59": "pink-yellow dahlia?",
+    "60": "cautleya spicata",
+    "61": "japanese anemone",
+    "62": "black-eyed susan",
+    "63": "silverbush",
+    "64": "californian poppy",
+    "65": "osteospermum",
+    "66": "spring crocus",
+    "67": "bearded iris",
+    "68": "windflower",
+    "69": "tree poppy",
+    "70": "gazania",
+    "71": "azalea",
+    "72": "water lily",
+    "73": "rose",
+    "74": "thorn apple",
+    "75": "morning glory",
+    "76": "passion flower",
+    "77": "lotus",
+    "78": "toad lily",
+    "79": "anthurium",
+    "80": "frangipani",
+    "81": "clematis",
+    "82": "hibiscus",
+    "83": "columbine",
+    "84": "desert-rose",
+    "85": "tree mallow",
+    "86": "magnolia",
+    "87": "cyclamen",
+    "88": "watercress",
+    "89": "canna lily",
+    "90": "hippeastrum",
+    "91": "bee balm",
+    "92": "ball moss",
+    "93": "foxglove",
+    "94": "bougainvillea",
+    "95": "camellia",
+    "96": "mallow",
+    "97": "mexican petunia",
+    "98": "bromelia",
+    "99": "blanket flower",
+    "100": "trumpet creeper",
+    "101": "blackberry lily"
+  },
+  "label2id": {
+    "alpine sea holly": 34,
+    "anthurium": 79,
+    "artichoke": 28,
+    "azalea": 71,
+    "ball moss": 92,
+    "balloon flower": 18,
+    "barbeton daisy": 40,
+    "bearded iris": 67,
+    "bee balm": 91,
+    "bird of paradise": 7,
+    "bishop of llandaff": 55,
+    "black-eyed susan": 62,
+    "blackberry lily": 101,
+    "blanket flower": 99,
+    "bolero deep blue": 44,
+    "bougainvillea": 94,
+    "bromelia": 98,
+    "buttercup": 47,
+    "californian poppy": 64,
+    "camellia": 95,
+    "canna lily": 89,
+    "canterbury bells": 2,
+    "cape flower": 36,
+    "carnation": 30,
+    "cautleya spicata": 60,
+    "clematis": 81,
+    "colt's foot": 11,
+    "columbine": 83,
+    "common dandelion": 49,
+    "corn poppy": 25,
+    "cyclamen": 87,
+    "daffodil": 41,
+    "desert-rose": 84,
+    "english marigold": 4,
+    "fire lily": 20,
+    "foxglove": 93,
+    "frangipani": 80,
+    "fritillary": 22,
+    "garden phlox": 31,
+    "gaura": 56,
+    "gazania": 70,
+    "geranium": 57,
+    "giant white arum lily": 19,
+    "globe thistle": 9,
+    "globe-flower": 15,
+    "grape hyacinth": 24,
+    "great masterwort": 37,
+    "hard-leaved pocket orchid": 1,
+    "hibiscus": 82,
+    "hippeastrum": 90,
+    "japanese anemone": 61,
+    "king protea": 12,
+    "lenten rose": 39,
+    "lotus": 77,
+    "love in the mist": 32,
+    "magnolia": 86,
+    "mallow": 96,
+    "marigold": 46,
+    "mexican aster": 33,
+    "mexican petunia": 97,
+    "monkshood": 8,
+    "moon orchid": 6,
+    "morning glory": 75,
+    "orange dahlia": 58,
+    "osteospermum": 65,
+    "oxeye daisy": 48,
+    "passion flower": 76,
+    "pelargonium": 54,
+    "peruvian lily": 17,
+    "petunia": 50,
+    "pincushion flower": 21,
+    "pink primrose": 0,
+    "pink-yellow dahlia?": 59,
+    "poinsettia": 43,
+    "primula": 52,
+    "prince of wales feathers": 26,
+    "purple coneflower": 16,
+    "red ginger": 23,
+    "rose": 73,
+    "ruby-lipped cattleya": 35,
+    "siam tulip": 38,
+    "silverbush": 63,
+    "snapdragon": 10,
+    "spear thistle": 13,
+    "spring crocus": 66,
+    "stemless gentian": 27,
+    "sunflower": 53,
+    "sweet pea": 3,
+    "sweet william": 29,
+    "sword lily": 42,
+    "thorn apple": 74,
+    "tiger lily": 5,
+    "toad lily": 78,
+    "tree mallow": 85,
+    "tree poppy": 69,
+    "trumpet creeper": 100,
+    "wallflower": 45,
+    "water lily": 72,
+    "watercress": 88,
+    "wild pansy": 51,
+    "windflower": 68,
+    "yellow iris": 14
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet152-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/README.md b/resnet152-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..1ad9f84cb23c1d21c5aaff088068e902bc3bc845
--- /dev/null
+++ b/resnet152-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford_flowers102.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: oxford_flowers102
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: train
+type: transformers
+val_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: test
+```
+
diff --git a/resnet152-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/config.json b/resnet152-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..73d4c5807d169cb2e901ab29de6ec9f57efd9347
--- /dev/null
+++ b/resnet152-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,247 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "pink primrose",
+    "1": "hard-leaved pocket orchid",
+    "2": "canterbury bells",
+    "3": "sweet pea",
+    "4": "english marigold",
+    "5": "tiger lily",
+    "6": "moon orchid",
+    "7": "bird of paradise",
+    "8": "monkshood",
+    "9": "globe thistle",
+    "10": "snapdragon",
+    "11": "colt's foot",
+    "12": "king protea",
+    "13": "spear thistle",
+    "14": "yellow iris",
+    "15": "globe-flower",
+    "16": "purple coneflower",
+    "17": "peruvian lily",
+    "18": "balloon flower",
+    "19": "giant white arum lily",
+    "20": "fire lily",
+    "21": "pincushion flower",
+    "22": "fritillary",
+    "23": "red ginger",
+    "24": "grape hyacinth",
+    "25": "corn poppy",
+    "26": "prince of wales feathers",
+    "27": "stemless gentian",
+    "28": "artichoke",
+    "29": "sweet william",
+    "30": "carnation",
+    "31": "garden phlox",
+    "32": "love in the mist",
+    "33": "mexican aster",
+    "34": "alpine sea holly",
+    "35": "ruby-lipped cattleya",
+    "36": "cape flower",
+    "37": "great masterwort",
+    "38": "siam tulip",
+    "39": "lenten rose",
+    "40": "barbeton daisy",
+    "41": "daffodil",
+    "42": "sword lily",
+    "43": "poinsettia",
+    "44": "bolero deep blue",
+    "45": "wallflower",
+    "46": "marigold",
+    "47": "buttercup",
+    "48": "oxeye daisy",
+    "49": "common dandelion",
+    "50": "petunia",
+    "51": "wild pansy",
+    "52": "primula",
+    "53": "sunflower",
+    "54": "pelargonium",
+    "55": "bishop of llandaff",
+    "56": "gaura",
+    "57": "geranium",
+    "58": "orange dahlia",
+    "59": "pink-yellow dahlia?",
+    "60": "cautleya spicata",
+    "61": "japanese anemone",
+    "62": "black-eyed susan",
+    "63": "silverbush",
+    "64": "californian poppy",
+    "65": "osteospermum",
+    "66": "spring crocus",
+    "67": "bearded iris",
+    "68": "windflower",
+    "69": "tree poppy",
+    "70": "gazania",
+    "71": "azalea",
+    "72": "water lily",
+    "73": "rose",
+    "74": "thorn apple",
+    "75": "morning glory",
+    "76": "passion flower",
+    "77": "lotus",
+    "78": "toad lily",
+    "79": "anthurium",
+    "80": "frangipani",
+    "81": "clematis",
+    "82": "hibiscus",
+    "83": "columbine",
+    "84": "desert-rose",
+    "85": "tree mallow",
+    "86": "magnolia",
+    "87": "cyclamen",
+    "88": "watercress",
+    "89": "canna lily",
+    "90": "hippeastrum",
+    "91": "bee balm",
+    "92": "ball moss",
+    "93": "foxglove",
+    "94": "bougainvillea",
+    "95": "camellia",
+    "96": "mallow",
+    "97": "mexican petunia",
+    "98": "bromelia",
+    "99": "blanket flower",
+    "100": "trumpet creeper",
+    "101": "blackberry lily"
+  },
+  "label2id": {
+    "alpine sea holly": 34,
+    "anthurium": 79,
+    "artichoke": 28,
+    "azalea": 71,
+    "ball moss": 92,
+    "balloon flower": 18,
+    "barbeton daisy": 40,
+    "bearded iris": 67,
+    "bee balm": 91,
+    "bird of paradise": 7,
+    "bishop of llandaff": 55,
+    "black-eyed susan": 62,
+    "blackberry lily": 101,
+    "blanket flower": 99,
+    "bolero deep blue": 44,
+    "bougainvillea": 94,
+    "bromelia": 98,
+    "buttercup": 47,
+    "californian poppy": 64,
+    "camellia": 95,
+    "canna lily": 89,
+    "canterbury bells": 2,
+    "cape flower": 36,
+    "carnation": 30,
+    "cautleya spicata": 60,
+    "clematis": 81,
+    "colt's foot": 11,
+    "columbine": 83,
+    "common dandelion": 49,
+    "corn poppy": 25,
+    "cyclamen": 87,
+    "daffodil": 41,
+    "desert-rose": 84,
+    "english marigold": 4,
+    "fire lily": 20,
+    "foxglove": 93,
+    "frangipani": 80,
+    "fritillary": 22,
+    "garden phlox": 31,
+    "gaura": 56,
+    "gazania": 70,
+    "geranium": 57,
+    "giant white arum lily": 19,
+    "globe thistle": 9,
+    "globe-flower": 15,
+    "grape hyacinth": 24,
+    "great masterwort": 37,
+    "hard-leaved pocket orchid": 1,
+    "hibiscus": 82,
+    "hippeastrum": 90,
+    "japanese anemone": 61,
+    "king protea": 12,
+    "lenten rose": 39,
+    "lotus": 77,
+    "love in the mist": 32,
+    "magnolia": 86,
+    "mallow": 96,
+    "marigold": 46,
+    "mexican aster": 33,
+    "mexican petunia": 97,
+    "monkshood": 8,
+    "moon orchid": 6,
+    "morning glory": 75,
+    "orange dahlia": 58,
+    "osteospermum": 65,
+    "oxeye daisy": 48,
+    "passion flower": 76,
+    "pelargonium": 54,
+    "peruvian lily": 17,
+    "petunia": 50,
+    "pincushion flower": 21,
+    "pink primrose": 0,
+    "pink-yellow dahlia?": 59,
+    "poinsettia": 43,
+    "primula": 52,
+    "prince of wales feathers": 26,
+    "purple coneflower": 16,
+    "red ginger": 23,
+    "rose": 73,
+    "ruby-lipped cattleya": 35,
+    "siam tulip": 38,
+    "silverbush": 63,
+    "snapdragon": 10,
+    "spear thistle": 13,
+    "spring crocus": 66,
+    "stemless gentian": 27,
+    "sunflower": 53,
+    "sweet pea": 3,
+    "sweet william": 29,
+    "sword lily": 42,
+    "thorn apple": 74,
+    "tiger lily": 5,
+    "toad lily": 78,
+    "tree mallow": 85,
+    "tree poppy": 69,
+    "trumpet creeper": 100,
+    "wallflower": 45,
+    "water lily": 72,
+    "watercress": 88,
+    "wild pansy": 51,
+    "windflower": 68,
+    "yellow iris": 14
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet152-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-pcam-batch_size_128_lr_0.005_training_data_ratio_0.5-4000/README.md b/resnet152-pcam-batch_size_128_lr_0.005_training_data_ratio_0.5-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..c26d17cee74b5f717861d4e640271104e8d2a1a7
--- /dev/null
+++ b/resnet152-pcam-batch_size_128_lr_0.005_training_data_ratio_0.5-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset pcam.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: pcam
+    pretrained: true
+test_datasets: null
+train_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: train
+type: transformers
+val_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: test
+```
+
diff --git a/resnet152-pcam-batch_size_128_lr_0.005_training_data_ratio_0.5-4000/config.json b/resnet152-pcam-batch_size_128_lr_0.005_training_data_ratio_0.5-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..3cb201dc7dfa380d2b50c3d20326ba2521864600
--- /dev/null
+++ b/resnet152-pcam-batch_size_128_lr_0.005_training_data_ratio_0.5-4000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "lymph node",
+    "1": "lymph node containing metastatic tumor tissue"
+  },
+  "label2id": {
+    "lymph node": 0,
+    "lymph node containing metastatic tumor tissue": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-pcam-batch_size_128_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet152-pcam-batch_size_128_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-pcam-batch_size_128_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-pcam-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/README.md b/resnet152-pcam-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..4e73f9d54127c67c17706acc4a9d96a69578a582
--- /dev/null
+++ b/resnet152-pcam-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset pcam.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: pcam
+    pretrained: true
+test_datasets: null
+train_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: train
+type: transformers
+val_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: test
+```
+
diff --git a/resnet152-pcam-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/config.json b/resnet152-pcam-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..3cb201dc7dfa380d2b50c3d20326ba2521864600
--- /dev/null
+++ b/resnet152-pcam-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "lymph node",
+    "1": "lymph node containing metastatic tumor tissue"
+  },
+  "label2id": {
+    "lymph node": 0,
+    "lymph node containing metastatic tumor tissue": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-pcam-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet152-pcam-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-pcam-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-pcam-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/README.md b/resnet152-pcam-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..0c09f71619efb156540f80b0c3e7947cc1d3205e
--- /dev/null
+++ b/resnet152-pcam-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset pcam.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: pcam
+    pretrained: true
+test_datasets: null
+train_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: train
+type: transformers
+val_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: test
+```
+
diff --git a/resnet152-pcam-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/config.json b/resnet152-pcam-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..3cb201dc7dfa380d2b50c3d20326ba2521864600
--- /dev/null
+++ b/resnet152-pcam-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "lymph node",
+    "1": "lymph node containing metastatic tumor tissue"
+  },
+  "label2id": {
+    "lymph node": 0,
+    "lymph node containing metastatic tumor tissue": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-pcam-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet152-pcam-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-pcam-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-pcam-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/README.md b/resnet152-pcam-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..4a8f27afadedd391912daf598206390af6a80056
--- /dev/null
+++ b/resnet152-pcam-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset pcam.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: pcam
+    pretrained: true
+test_datasets: null
+train_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: train
+type: transformers
+val_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: test
+```
+
diff --git a/resnet152-pcam-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/config.json b/resnet152-pcam-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..3cb201dc7dfa380d2b50c3d20326ba2521864600
--- /dev/null
+++ b/resnet152-pcam-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "lymph node",
+    "1": "lymph node containing metastatic tumor tissue"
+  },
+  "label2id": {
+    "lymph node": 0,
+    "lymph node containing metastatic tumor tissue": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-pcam-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet152-pcam-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-pcam-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-pcam-batch_size_64_lr_0.001_training_data_ratio_0.8-4000/README.md b/resnet152-pcam-batch_size_64_lr_0.001_training_data_ratio_0.8-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..bc43eb80a669546f0830d78728027aa43cc9323a
--- /dev/null
+++ b/resnet152-pcam-batch_size_64_lr_0.001_training_data_ratio_0.8-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset pcam.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: pcam
+    pretrained: true
+test_datasets: null
+train_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: train
+type: transformers
+val_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: test
+```
+
diff --git a/resnet152-pcam-batch_size_64_lr_0.001_training_data_ratio_0.8-4000/config.json b/resnet152-pcam-batch_size_64_lr_0.001_training_data_ratio_0.8-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..3cb201dc7dfa380d2b50c3d20326ba2521864600
--- /dev/null
+++ b/resnet152-pcam-batch_size_64_lr_0.001_training_data_ratio_0.8-4000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "lymph node",
+    "1": "lymph node containing metastatic tumor tissue"
+  },
+  "label2id": {
+    "lymph node": 0,
+    "lymph node containing metastatic tumor tissue": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-pcam-batch_size_64_lr_0.001_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet152-pcam-batch_size_64_lr_0.001_training_data_ratio_0.8-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-pcam-batch_size_64_lr_0.001_training_data_ratio_0.8-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/README.md b/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..f3637a04ddadfb8a1d4295226c7d962913809bc4
--- /dev/null
+++ b/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset rendered-sst2.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: rendered-sst2
+    pretrained: true
+test_datasets: null
+train_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: train
+type: transformers
+val_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: test
+```
+
diff --git a/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/config.json b/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..054ed535def906c22cb0ab0c6b25c9c88b195f06
--- /dev/null
+++ b/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "negative",
+    "1": "positive"
+  },
+  "label2id": {
+    "negative": 0,
+    "positive": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/README.md b/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..f3637a04ddadfb8a1d4295226c7d962913809bc4
--- /dev/null
+++ b/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset rendered-sst2.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: rendered-sst2
+    pretrained: true
+test_datasets: null
+train_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: train
+type: transformers
+val_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: test
+```
+
diff --git a/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/config.json b/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..054ed535def906c22cb0ab0c6b25c9c88b195f06
--- /dev/null
+++ b/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "negative",
+    "1": "positive"
+  },
+  "label2id": {
+    "negative": 0,
+    "positive": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/README.md b/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..f3637a04ddadfb8a1d4295226c7d962913809bc4
--- /dev/null
+++ b/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset rendered-sst2.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: rendered-sst2
+    pretrained: true
+test_datasets: null
+train_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: train
+type: transformers
+val_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: test
+```
+
diff --git a/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/config.json b/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..054ed535def906c22cb0ab0c6b25c9c88b195f06
--- /dev/null
+++ b/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "negative",
+    "1": "positive"
+  },
+  "label2id": {
+    "negative": 0,
+    "positive": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/README.md b/resnet152-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..94ef42dfe24512275d02f6cdae5bb03965beb4a8
--- /dev/null
+++ b/resnet152-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset rendered-sst2.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: rendered-sst2
+    pretrained: true
+test_datasets: null
+train_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: train
+type: transformers
+val_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: test
+```
+
diff --git a/resnet152-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/config.json b/resnet152-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..054ed535def906c22cb0ab0c6b25c9c88b195f06
--- /dev/null
+++ b/resnet152-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "negative",
+    "1": "positive"
+  },
+  "label2id": {
+    "negative": 0,
+    "positive": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet152-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/README.md b/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..94ef42dfe24512275d02f6cdae5bb03965beb4a8
--- /dev/null
+++ b/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset rendered-sst2.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: rendered-sst2
+    pretrained: true
+test_datasets: null
+train_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: train
+type: transformers
+val_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: test
+```
+
diff --git a/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/config.json b/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..054ed535def906c22cb0ab0c6b25c9c88b195f06
--- /dev/null
+++ b/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "negative",
+    "1": "positive"
+  },
+  "label2id": {
+    "negative": 0,
+    "positive": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/README.md b/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..7b6b6ca74c92052c1fa790fc2826cf9b22442966
--- /dev/null
+++ b/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset rendered-sst2.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: rendered-sst2
+    pretrained: true
+test_datasets: null
+train_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: train
+type: transformers
+val_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: test
+```
+
diff --git a/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/config.json b/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..054ed535def906c22cb0ab0c6b25c9c88b195f06
--- /dev/null
+++ b/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "negative",
+    "1": "positive"
+  },
+  "label2id": {
+    "negative": 0,
+    "positive": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/README.md b/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..7b6b6ca74c92052c1fa790fc2826cf9b22442966
--- /dev/null
+++ b/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset rendered-sst2.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: rendered-sst2
+    pretrained: true
+test_datasets: null
+train_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: train
+type: transformers
+val_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: test
+```
+
diff --git a/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/config.json b/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..054ed535def906c22cb0ab0c6b25c9c88b195f06
--- /dev/null
+++ b/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "negative",
+    "1": "positive"
+  },
+  "label2id": {
+    "negative": 0,
+    "positive": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-rendered-sst2-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/README.md b/resnet152-rendered-sst2-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..1f1288931833712cbf527596d3e05d6c99a949e1
--- /dev/null
+++ b/resnet152-rendered-sst2-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset rendered-sst2.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: rendered-sst2
+    pretrained: true
+test_datasets: null
+train_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: train
+type: transformers
+val_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: test
+```
+
diff --git a/resnet152-rendered-sst2-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/config.json b/resnet152-rendered-sst2-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..054ed535def906c22cb0ab0c6b25c9c88b195f06
--- /dev/null
+++ b/resnet152-rendered-sst2-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "negative",
+    "1": "positive"
+  },
+  "label2id": {
+    "negative": 0,
+    "positive": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-rendered-sst2-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet152-rendered-sst2-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-rendered-sst2-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/README.md b/resnet152-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..c72c8f027bf9d6ff5204a3179bc1e8e24f37927b
--- /dev/null
+++ b/resnet152-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset resisc45.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: resisc45
+    pretrained: true
+test_datasets: null
+train_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: train
+type: transformers
+val_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: test
+```
+
diff --git a/resnet152-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/config.json b/resnet152-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1ccd6b3d4942b65d4b1b5d4a4f27c0403ba41898
--- /dev/null
+++ b/resnet152-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,133 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "airport",
+    "2": "baseball diamond",
+    "3": "basketball court",
+    "4": "beach",
+    "5": "bridge",
+    "6": "chaparral",
+    "7": "church",
+    "8": "circular farmland",
+    "9": "cloud",
+    "10": "commercial area",
+    "11": "dense residential",
+    "12": "desert",
+    "13": "forest",
+    "14": "freeway",
+    "15": "golf course",
+    "16": "ground track field",
+    "17": "harbor",
+    "18": "industrial area",
+    "19": "intersection",
+    "20": "island",
+    "21": "lake",
+    "22": "meadow",
+    "23": "medium residential",
+    "24": "mobile home park",
+    "25": "mountain",
+    "26": "overpass",
+    "27": "palace",
+    "28": "parking lot",
+    "29": "railway",
+    "30": "railway station",
+    "31": "rectangular farmland",
+    "32": "river",
+    "33": "roundabout",
+    "34": "runway",
+    "35": "sea ice",
+    "36": "ship",
+    "37": "snowberg",
+    "38": "sparse residential",
+    "39": "stadium",
+    "40": "storage tank",
+    "41": "tennis court",
+    "42": "terrace",
+    "43": "thermal power station",
+    "44": "wetland"
+  },
+  "label2id": {
+    "airplane": 0,
+    "airport": 1,
+    "baseball diamond": 2,
+    "basketball court": 3,
+    "beach": 4,
+    "bridge": 5,
+    "chaparral": 6,
+    "church": 7,
+    "circular farmland": 8,
+    "cloud": 9,
+    "commercial area": 10,
+    "dense residential": 11,
+    "desert": 12,
+    "forest": 13,
+    "freeway": 14,
+    "golf course": 15,
+    "ground track field": 16,
+    "harbor": 17,
+    "industrial area": 18,
+    "intersection": 19,
+    "island": 20,
+    "lake": 21,
+    "meadow": 22,
+    "medium residential": 23,
+    "mobile home park": 24,
+    "mountain": 25,
+    "overpass": 26,
+    "palace": 27,
+    "parking lot": 28,
+    "railway": 29,
+    "railway station": 30,
+    "rectangular farmland": 31,
+    "river": 32,
+    "roundabout": 33,
+    "runway": 34,
+    "sea ice": 35,
+    "ship": 36,
+    "snowberg": 37,
+    "sparse residential": 38,
+    "stadium": 39,
+    "storage tank": 40,
+    "tennis court": 41,
+    "terrace": 42,
+    "thermal power station": 43,
+    "wetland": 44
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet152-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-resisc45-batch_size_64_lr_0.01_training_data_ratio_0.8-2000/README.md b/resnet152-resisc45-batch_size_64_lr_0.01_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..f478f26bfe4ed04460db29f64c648c137604b5fa
--- /dev/null
+++ b/resnet152-resisc45-batch_size_64_lr_0.01_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset resisc45.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: resisc45
+    pretrained: true
+test_datasets: null
+train_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: train
+type: transformers
+val_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: test
+```
+
diff --git a/resnet152-resisc45-batch_size_64_lr_0.01_training_data_ratio_0.8-2000/config.json b/resnet152-resisc45-batch_size_64_lr_0.01_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1ccd6b3d4942b65d4b1b5d4a4f27c0403ba41898
--- /dev/null
+++ b/resnet152-resisc45-batch_size_64_lr_0.01_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,133 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "airport",
+    "2": "baseball diamond",
+    "3": "basketball court",
+    "4": "beach",
+    "5": "bridge",
+    "6": "chaparral",
+    "7": "church",
+    "8": "circular farmland",
+    "9": "cloud",
+    "10": "commercial area",
+    "11": "dense residential",
+    "12": "desert",
+    "13": "forest",
+    "14": "freeway",
+    "15": "golf course",
+    "16": "ground track field",
+    "17": "harbor",
+    "18": "industrial area",
+    "19": "intersection",
+    "20": "island",
+    "21": "lake",
+    "22": "meadow",
+    "23": "medium residential",
+    "24": "mobile home park",
+    "25": "mountain",
+    "26": "overpass",
+    "27": "palace",
+    "28": "parking lot",
+    "29": "railway",
+    "30": "railway station",
+    "31": "rectangular farmland",
+    "32": "river",
+    "33": "roundabout",
+    "34": "runway",
+    "35": "sea ice",
+    "36": "ship",
+    "37": "snowberg",
+    "38": "sparse residential",
+    "39": "stadium",
+    "40": "storage tank",
+    "41": "tennis court",
+    "42": "terrace",
+    "43": "thermal power station",
+    "44": "wetland"
+  },
+  "label2id": {
+    "airplane": 0,
+    "airport": 1,
+    "baseball diamond": 2,
+    "basketball court": 3,
+    "beach": 4,
+    "bridge": 5,
+    "chaparral": 6,
+    "church": 7,
+    "circular farmland": 8,
+    "cloud": 9,
+    "commercial area": 10,
+    "dense residential": 11,
+    "desert": 12,
+    "forest": 13,
+    "freeway": 14,
+    "golf course": 15,
+    "ground track field": 16,
+    "harbor": 17,
+    "industrial area": 18,
+    "intersection": 19,
+    "island": 20,
+    "lake": 21,
+    "meadow": 22,
+    "medium residential": 23,
+    "mobile home park": 24,
+    "mountain": 25,
+    "overpass": 26,
+    "palace": 27,
+    "parking lot": 28,
+    "railway": 29,
+    "railway station": 30,
+    "rectangular farmland": 31,
+    "river": 32,
+    "roundabout": 33,
+    "runway": 34,
+    "sea ice": 35,
+    "ship": 36,
+    "snowberg": 37,
+    "sparse residential": 38,
+    "stadium": 39,
+    "storage tank": 40,
+    "tennis court": 41,
+    "terrace": 42,
+    "thermal power station": 43,
+    "wetland": 44
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-resisc45-batch_size_64_lr_0.01_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet152-resisc45-batch_size_64_lr_0.01_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-resisc45-batch_size_64_lr_0.01_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-stanford-cars-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/README.md b/resnet152-stanford-cars-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..4f6c52ec036a241fab5a330ba4a09c21e7bad407
--- /dev/null
+++ b/resnet152-stanford-cars-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stanford-cars.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: stanford-cars
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: train
+type: transformers
+val_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: test
+```
+
diff --git a/resnet152-stanford-cars-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/config.json b/resnet152-stanford-cars-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1e0f59991da08604f363224d408031555ecd60f4
--- /dev/null
+++ b/resnet152-stanford-cars-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,435 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "AM General Hummer SUV 2000",
+    "1": "Acura RL Sedan 2012",
+    "2": "Acura TL Sedan 2012",
+    "3": "Acura TL Type-S 2008",
+    "4": "Acura TSX Sedan 2012",
+    "5": "Acura Integra Type R 2001",
+    "6": "Acura ZDX Hatchback 2012",
+    "7": "Aston Martin V8 Vantage Convertible 2012",
+    "8": "Aston Martin V8 Vantage Coupe 2012",
+    "9": "Aston Martin Virage Convertible 2012",
+    "10": "Aston Martin Virage Coupe 2012",
+    "11": "Audi RS 4 Convertible 2008",
+    "12": "Audi A5 Coupe 2012",
+    "13": "Audi TTS Coupe 2012",
+    "14": "Audi R8 Coupe 2012",
+    "15": "Audi V8 Sedan 1994",
+    "16": "Audi 100 Sedan 1994",
+    "17": "Audi 100 Wagon 1994",
+    "18": "Audi TT Hatchback 2011",
+    "19": "Audi S6 Sedan 2011",
+    "20": "Audi S5 Convertible 2012",
+    "21": "Audi S5 Coupe 2012",
+    "22": "Audi S4 Sedan 2012",
+    "23": "Audi S4 Sedan 2007",
+    "24": "Audi TT RS Coupe 2012",
+    "25": "BMW ActiveHybrid 5 Sedan 2012",
+    "26": "BMW 1 Series Convertible 2012",
+    "27": "BMW 1 Series Coupe 2012",
+    "28": "BMW 3 Series Sedan 2012",
+    "29": "BMW 3 Series Wagon 2012",
+    "30": "BMW 6 Series Convertible 2007",
+    "31": "BMW X5 SUV 2007",
+    "32": "BMW X6 SUV 2012",
+    "33": "BMW M3 Coupe 2012",
+    "34": "BMW M5 Sedan 2010",
+    "35": "BMW M6 Convertible 2010",
+    "36": "BMW X3 SUV 2012",
+    "37": "BMW Z4 Convertible 2012",
+    "38": "Bentley Continental Supersports Conv. Convertible 2012",
+    "39": "Bentley Arnage Sedan 2009",
+    "40": "Bentley Mulsanne Sedan 2011",
+    "41": "Bentley Continental GT Coupe 2012",
+    "42": "Bentley Continental GT Coupe 2007",
+    "43": "Bentley Continental Flying Spur Sedan 2007",
+    "44": "Bugatti Veyron 16.4 Convertible 2009",
+    "45": "Bugatti Veyron 16.4 Coupe 2009",
+    "46": "Buick Regal GS 2012",
+    "47": "Buick Rainier SUV 2007",
+    "48": "Buick Verano Sedan 2012",
+    "49": "Buick Enclave SUV 2012",
+    "50": "Cadillac CTS-V Sedan 2012",
+    "51": "Cadillac SRX SUV 2012",
+    "52": "Cadillac Escalade EXT Crew Cab 2007",
+    "53": "Chevrolet Silverado 1500 Hybrid Crew Cab 2012",
+    "54": "Chevrolet Corvette Convertible 2012",
+    "55": "Chevrolet Corvette ZR1 2012",
+    "56": "Chevrolet Corvette Ron Fellows Edition Z06 2007",
+    "57": "Chevrolet Traverse SUV 2012",
+    "58": "Chevrolet Camaro Convertible 2012",
+    "59": "Chevrolet HHR SS 2010",
+    "60": "Chevrolet Impala Sedan 2007",
+    "61": "Chevrolet Tahoe Hybrid SUV 2012",
+    "62": "Chevrolet Sonic Sedan 2012",
+    "63": "Chevrolet Express Cargo Van 2007",
+    "64": "Chevrolet Avalanche Crew Cab 2012",
+    "65": "Chevrolet Cobalt SS 2010",
+    "66": "Chevrolet Malibu Hybrid Sedan 2010",
+    "67": "Chevrolet TrailBlazer SS 2009",
+    "68": "Chevrolet Silverado 2500HD Regular Cab 2012",
+    "69": "Chevrolet Silverado 1500 Classic Extended Cab 2007",
+    "70": "Chevrolet Express Van 2007",
+    "71": "Chevrolet Monte Carlo Coupe 2007",
+    "72": "Chevrolet Malibu Sedan 2007",
+    "73": "Chevrolet Silverado 1500 Extended Cab 2012",
+    "74": "Chevrolet Silverado 1500 Regular Cab 2012",
+    "75": "Chrysler Aspen SUV 2009",
+    "76": "Chrysler Sebring Convertible 2010",
+    "77": "Chrysler Town and Country Minivan 2012",
+    "78": "Chrysler 300 SRT-8 2010",
+    "79": "Chrysler Crossfire Convertible 2008",
+    "80": "Chrysler PT Cruiser Convertible 2008",
+    "81": "Daewoo Nubira Wagon 2002",
+    "82": "Dodge Caliber Wagon 2012",
+    "83": "Dodge Caliber Wagon 2007",
+    "84": "Dodge Caravan Minivan 1997",
+    "85": "Dodge Ram Pickup 3500 Crew Cab 2010",
+    "86": "Dodge Ram Pickup 3500 Quad Cab 2009",
+    "87": "Dodge Sprinter Cargo Van 2009",
+    "88": "Dodge Journey SUV 2012",
+    "89": "Dodge Dakota Crew Cab 2010",
+    "90": "Dodge Dakota Club Cab 2007",
+    "91": "Dodge Magnum Wagon 2008",
+    "92": "Dodge Challenger SRT8 2011",
+    "93": "Dodge Durango SUV 2012",
+    "94": "Dodge Durango SUV 2007",
+    "95": "Dodge Charger Sedan 2012",
+    "96": "Dodge Charger SRT-8 2009",
+    "97": "Eagle Talon Hatchback 1998",
+    "98": "FIAT 500 Abarth 2012",
+    "99": "FIAT 500 Convertible 2012",
+    "100": "Ferrari FF Coupe 2012",
+    "101": "Ferrari California Convertible 2012",
+    "102": "Ferrari 458 Italia Convertible 2012",
+    "103": "Ferrari 458 Italia Coupe 2012",
+    "104": "Fisker Karma Sedan 2012",
+    "105": "Ford F-450 Super Duty Crew Cab 2012",
+    "106": "Ford Mustang Convertible 2007",
+    "107": "Ford Freestar Minivan 2007",
+    "108": "Ford Expedition EL SUV 2009",
+    "109": "Ford Edge SUV 2012",
+    "110": "Ford Ranger SuperCab 2011",
+    "111": "Ford GT Coupe 2006",
+    "112": "Ford F-150 Regular Cab 2012",
+    "113": "Ford F-150 Regular Cab 2007",
+    "114": "Ford Focus Sedan 2007",
+    "115": "Ford E-Series Wagon Van 2012",
+    "116": "Ford Fiesta Sedan 2012",
+    "117": "GMC Terrain SUV 2012",
+    "118": "GMC Savana Van 2012",
+    "119": "GMC Yukon Hybrid SUV 2012",
+    "120": "GMC Acadia SUV 2012",
+    "121": "GMC Canyon Extended Cab 2012",
+    "122": "Geo Metro Convertible 1993",
+    "123": "HUMMER H3T Crew Cab 2010",
+    "124": "HUMMER H2 SUT Crew Cab 2009",
+    "125": "Honda Odyssey Minivan 2012",
+    "126": "Honda Odyssey Minivan 2007",
+    "127": "Honda Accord Coupe 2012",
+    "128": "Honda Accord Sedan 2012",
+    "129": "Hyundai Veloster Hatchback 2012",
+    "130": "Hyundai Santa Fe SUV 2012",
+    "131": "Hyundai Tucson SUV 2012",
+    "132": "Hyundai Veracruz SUV 2012",
+    "133": "Hyundai Sonata Hybrid Sedan 2012",
+    "134": "Hyundai Elantra Sedan 2007",
+    "135": "Hyundai Accent Sedan 2012",
+    "136": "Hyundai Genesis Sedan 2012",
+    "137": "Hyundai Sonata Sedan 2012",
+    "138": "Hyundai Elantra Touring Hatchback 2012",
+    "139": "Hyundai Azera Sedan 2012",
+    "140": "Infiniti G Coupe IPL 2012",
+    "141": "Infiniti QX56 SUV 2011",
+    "142": "Isuzu Ascender SUV 2008",
+    "143": "Jaguar XK XKR 2012",
+    "144": "Jeep Patriot SUV 2012",
+    "145": "Jeep Wrangler SUV 2012",
+    "146": "Jeep Liberty SUV 2012",
+    "147": "Jeep Grand Cherokee SUV 2012",
+    "148": "Jeep Compass SUV 2012",
+    "149": "Lamborghini Reventon Coupe 2008",
+    "150": "Lamborghini Aventador Coupe 2012",
+    "151": "Lamborghini Gallardo LP 570-4 Superleggera 2012",
+    "152": "Lamborghini Diablo Coupe 2001",
+    "153": "Land Rover Range Rover SUV 2012",
+    "154": "Land Rover LR2 SUV 2012",
+    "155": "Lincoln Town Car Sedan 2011",
+    "156": "MINI Cooper Roadster Convertible 2012",
+    "157": "Maybach Landaulet Convertible 2012",
+    "158": "Mazda Tribute SUV 2011",
+    "159": "McLaren MP4-12C Coupe 2012",
+    "160": "Mercedes-Benz 300-Class Convertible 1993",
+    "161": "Mercedes-Benz C-Class Sedan 2012",
+    "162": "Mercedes-Benz SL-Class Coupe 2009",
+    "163": "Mercedes-Benz E-Class Sedan 2012",
+    "164": "Mercedes-Benz S-Class Sedan 2012",
+    "165": "Mercedes-Benz Sprinter Van 2012",
+    "166": "Mitsubishi Lancer Sedan 2012",
+    "167": "Nissan Leaf Hatchback 2012",
+    "168": "Nissan NV Passenger Van 2012",
+    "169": "Nissan Juke Hatchback 2012",
+    "170": "Nissan 240SX Coupe 1998",
+    "171": "Plymouth Neon Coupe 1999",
+    "172": "Porsche Panamera Sedan 2012",
+    "173": "Ram C/V Cargo Van Minivan 2012",
+    "174": "Rolls-Royce Phantom Drophead Coupe Convertible 2012",
+    "175": "Rolls-Royce Ghost Sedan 2012",
+    "176": "Rolls-Royce Phantom Sedan 2012",
+    "177": "Scion xD Hatchback 2012",
+    "178": "Spyker C8 Convertible 2009",
+    "179": "Spyker C8 Coupe 2009",
+    "180": "Suzuki Aerio Sedan 2007",
+    "181": "Suzuki Kizashi Sedan 2012",
+    "182": "Suzuki SX4 Hatchback 2012",
+    "183": "Suzuki SX4 Sedan 2012",
+    "184": "Tesla Model S Sedan 2012",
+    "185": "Toyota Sequoia SUV 2012",
+    "186": "Toyota Camry Sedan 2012",
+    "187": "Toyota Corolla Sedan 2012",
+    "188": "Toyota 4Runner SUV 2012",
+    "189": "Volkswagen Golf Hatchback 2012",
+    "190": "Volkswagen Golf Hatchback 1991",
+    "191": "Volkswagen Beetle Hatchback 2012",
+    "192": "Volvo C30 Hatchback 2012",
+    "193": "Volvo 240 Sedan 1993",
+    "194": "Volvo XC90 SUV 2007",
+    "195": "smart fortwo Convertible 2012"
+  },
+  "label2id": {
+    "AM General Hummer SUV 2000": 0,
+    "Acura Integra Type R 2001": 5,
+    "Acura RL Sedan 2012": 1,
+    "Acura TL Sedan 2012": 2,
+    "Acura TL Type-S 2008": 3,
+    "Acura TSX Sedan 2012": 4,
+    "Acura ZDX Hatchback 2012": 6,
+    "Aston Martin V8 Vantage Convertible 2012": 7,
+    "Aston Martin V8 Vantage Coupe 2012": 8,
+    "Aston Martin Virage Convertible 2012": 9,
+    "Aston Martin Virage Coupe 2012": 10,
+    "Audi 100 Sedan 1994": 16,
+    "Audi 100 Wagon 1994": 17,
+    "Audi A5 Coupe 2012": 12,
+    "Audi R8 Coupe 2012": 14,
+    "Audi RS 4 Convertible 2008": 11,
+    "Audi S4 Sedan 2007": 23,
+    "Audi S4 Sedan 2012": 22,
+    "Audi S5 Convertible 2012": 20,
+    "Audi S5 Coupe 2012": 21,
+    "Audi S6 Sedan 2011": 19,
+    "Audi TT Hatchback 2011": 18,
+    "Audi TT RS Coupe 2012": 24,
+    "Audi TTS Coupe 2012": 13,
+    "Audi V8 Sedan 1994": 15,
+    "BMW 1 Series Convertible 2012": 26,
+    "BMW 1 Series Coupe 2012": 27,
+    "BMW 3 Series Sedan 2012": 28,
+    "BMW 3 Series Wagon 2012": 29,
+    "BMW 6 Series Convertible 2007": 30,
+    "BMW ActiveHybrid 5 Sedan 2012": 25,
+    "BMW M3 Coupe 2012": 33,
+    "BMW M5 Sedan 2010": 34,
+    "BMW M6 Convertible 2010": 35,
+    "BMW X3 SUV 2012": 36,
+    "BMW X5 SUV 2007": 31,
+    "BMW X6 SUV 2012": 32,
+    "BMW Z4 Convertible 2012": 37,
+    "Bentley Arnage Sedan 2009": 39,
+    "Bentley Continental Flying Spur Sedan 2007": 43,
+    "Bentley Continental GT Coupe 2007": 42,
+    "Bentley Continental GT Coupe 2012": 41,
+    "Bentley Continental Supersports Conv. Convertible 2012": 38,
+    "Bentley Mulsanne Sedan 2011": 40,
+    "Bugatti Veyron 16.4 Convertible 2009": 44,
+    "Bugatti Veyron 16.4 Coupe 2009": 45,
+    "Buick Enclave SUV 2012": 49,
+    "Buick Rainier SUV 2007": 47,
+    "Buick Regal GS 2012": 46,
+    "Buick Verano Sedan 2012": 48,
+    "Cadillac CTS-V Sedan 2012": 50,
+    "Cadillac Escalade EXT Crew Cab 2007": 52,
+    "Cadillac SRX SUV 2012": 51,
+    "Chevrolet Avalanche Crew Cab 2012": 64,
+    "Chevrolet Camaro Convertible 2012": 58,
+    "Chevrolet Cobalt SS 2010": 65,
+    "Chevrolet Corvette Convertible 2012": 54,
+    "Chevrolet Corvette Ron Fellows Edition Z06 2007": 56,
+    "Chevrolet Corvette ZR1 2012": 55,
+    "Chevrolet Express Cargo Van 2007": 63,
+    "Chevrolet Express Van 2007": 70,
+    "Chevrolet HHR SS 2010": 59,
+    "Chevrolet Impala Sedan 2007": 60,
+    "Chevrolet Malibu Hybrid Sedan 2010": 66,
+    "Chevrolet Malibu Sedan 2007": 72,
+    "Chevrolet Monte Carlo Coupe 2007": 71,
+    "Chevrolet Silverado 1500 Classic Extended Cab 2007": 69,
+    "Chevrolet Silverado 1500 Extended Cab 2012": 73,
+    "Chevrolet Silverado 1500 Hybrid Crew Cab 2012": 53,
+    "Chevrolet Silverado 1500 Regular Cab 2012": 74,
+    "Chevrolet Silverado 2500HD Regular Cab 2012": 68,
+    "Chevrolet Sonic Sedan 2012": 62,
+    "Chevrolet Tahoe Hybrid SUV 2012": 61,
+    "Chevrolet TrailBlazer SS 2009": 67,
+    "Chevrolet Traverse SUV 2012": 57,
+    "Chrysler 300 SRT-8 2010": 78,
+    "Chrysler Aspen SUV 2009": 75,
+    "Chrysler Crossfire Convertible 2008": 79,
+    "Chrysler PT Cruiser Convertible 2008": 80,
+    "Chrysler Sebring Convertible 2010": 76,
+    "Chrysler Town and Country Minivan 2012": 77,
+    "Daewoo Nubira Wagon 2002": 81,
+    "Dodge Caliber Wagon 2007": 83,
+    "Dodge Caliber Wagon 2012": 82,
+    "Dodge Caravan Minivan 1997": 84,
+    "Dodge Challenger SRT8 2011": 92,
+    "Dodge Charger SRT-8 2009": 96,
+    "Dodge Charger Sedan 2012": 95,
+    "Dodge Dakota Club Cab 2007": 90,
+    "Dodge Dakota Crew Cab 2010": 89,
+    "Dodge Durango SUV 2007": 94,
+    "Dodge Durango SUV 2012": 93,
+    "Dodge Journey SUV 2012": 88,
+    "Dodge Magnum Wagon 2008": 91,
+    "Dodge Ram Pickup 3500 Crew Cab 2010": 85,
+    "Dodge Ram Pickup 3500 Quad Cab 2009": 86,
+    "Dodge Sprinter Cargo Van 2009": 87,
+    "Eagle Talon Hatchback 1998": 97,
+    "FIAT 500 Abarth 2012": 98,
+    "FIAT 500 Convertible 2012": 99,
+    "Ferrari 458 Italia Convertible 2012": 102,
+    "Ferrari 458 Italia Coupe 2012": 103,
+    "Ferrari California Convertible 2012": 101,
+    "Ferrari FF Coupe 2012": 100,
+    "Fisker Karma Sedan 2012": 104,
+    "Ford E-Series Wagon Van 2012": 115,
+    "Ford Edge SUV 2012": 109,
+    "Ford Expedition EL SUV 2009": 108,
+    "Ford F-150 Regular Cab 2007": 113,
+    "Ford F-150 Regular Cab 2012": 112,
+    "Ford F-450 Super Duty Crew Cab 2012": 105,
+    "Ford Fiesta Sedan 2012": 116,
+    "Ford Focus Sedan 2007": 114,
+    "Ford Freestar Minivan 2007": 107,
+    "Ford GT Coupe 2006": 111,
+    "Ford Mustang Convertible 2007": 106,
+    "Ford Ranger SuperCab 2011": 110,
+    "GMC Acadia SUV 2012": 120,
+    "GMC Canyon Extended Cab 2012": 121,
+    "GMC Savana Van 2012": 118,
+    "GMC Terrain SUV 2012": 117,
+    "GMC Yukon Hybrid SUV 2012": 119,
+    "Geo Metro Convertible 1993": 122,
+    "HUMMER H2 SUT Crew Cab 2009": 124,
+    "HUMMER H3T Crew Cab 2010": 123,
+    "Honda Accord Coupe 2012": 127,
+    "Honda Accord Sedan 2012": 128,
+    "Honda Odyssey Minivan 2007": 126,
+    "Honda Odyssey Minivan 2012": 125,
+    "Hyundai Accent Sedan 2012": 135,
+    "Hyundai Azera Sedan 2012": 139,
+    "Hyundai Elantra Sedan 2007": 134,
+    "Hyundai Elantra Touring Hatchback 2012": 138,
+    "Hyundai Genesis Sedan 2012": 136,
+    "Hyundai Santa Fe SUV 2012": 130,
+    "Hyundai Sonata Hybrid Sedan 2012": 133,
+    "Hyundai Sonata Sedan 2012": 137,
+    "Hyundai Tucson SUV 2012": 131,
+    "Hyundai Veloster Hatchback 2012": 129,
+    "Hyundai Veracruz SUV 2012": 132,
+    "Infiniti G Coupe IPL 2012": 140,
+    "Infiniti QX56 SUV 2011": 141,
+    "Isuzu Ascender SUV 2008": 142,
+    "Jaguar XK XKR 2012": 143,
+    "Jeep Compass SUV 2012": 148,
+    "Jeep Grand Cherokee SUV 2012": 147,
+    "Jeep Liberty SUV 2012": 146,
+    "Jeep Patriot SUV 2012": 144,
+    "Jeep Wrangler SUV 2012": 145,
+    "Lamborghini Aventador Coupe 2012": 150,
+    "Lamborghini Diablo Coupe 2001": 152,
+    "Lamborghini Gallardo LP 570-4 Superleggera 2012": 151,
+    "Lamborghini Reventon Coupe 2008": 149,
+    "Land Rover LR2 SUV 2012": 154,
+    "Land Rover Range Rover SUV 2012": 153,
+    "Lincoln Town Car Sedan 2011": 155,
+    "MINI Cooper Roadster Convertible 2012": 156,
+    "Maybach Landaulet Convertible 2012": 157,
+    "Mazda Tribute SUV 2011": 158,
+    "McLaren MP4-12C Coupe 2012": 159,
+    "Mercedes-Benz 300-Class Convertible 1993": 160,
+    "Mercedes-Benz C-Class Sedan 2012": 161,
+    "Mercedes-Benz E-Class Sedan 2012": 163,
+    "Mercedes-Benz S-Class Sedan 2012": 164,
+    "Mercedes-Benz SL-Class Coupe 2009": 162,
+    "Mercedes-Benz Sprinter Van 2012": 165,
+    "Mitsubishi Lancer Sedan 2012": 166,
+    "Nissan 240SX Coupe 1998": 170,
+    "Nissan Juke Hatchback 2012": 169,
+    "Nissan Leaf Hatchback 2012": 167,
+    "Nissan NV Passenger Van 2012": 168,
+    "Plymouth Neon Coupe 1999": 171,
+    "Porsche Panamera Sedan 2012": 172,
+    "Ram C/V Cargo Van Minivan 2012": 173,
+    "Rolls-Royce Ghost Sedan 2012": 175,
+    "Rolls-Royce Phantom Drophead Coupe Convertible 2012": 174,
+    "Rolls-Royce Phantom Sedan 2012": 176,
+    "Scion xD Hatchback 2012": 177,
+    "Spyker C8 Convertible 2009": 178,
+    "Spyker C8 Coupe 2009": 179,
+    "Suzuki Aerio Sedan 2007": 180,
+    "Suzuki Kizashi Sedan 2012": 181,
+    "Suzuki SX4 Hatchback 2012": 182,
+    "Suzuki SX4 Sedan 2012": 183,
+    "Tesla Model S Sedan 2012": 184,
+    "Toyota 4Runner SUV 2012": 188,
+    "Toyota Camry Sedan 2012": 186,
+    "Toyota Corolla Sedan 2012": 187,
+    "Toyota Sequoia SUV 2012": 185,
+    "Volkswagen Beetle Hatchback 2012": 191,
+    "Volkswagen Golf Hatchback 1991": 190,
+    "Volkswagen Golf Hatchback 2012": 189,
+    "Volvo 240 Sedan 1993": 193,
+    "Volvo C30 Hatchback 2012": 192,
+    "Volvo XC90 SUV 2007": 194,
+    "smart fortwo Convertible 2012": 195
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-stanford-cars-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet152-stanford-cars-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-stanford-cars-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-stanford-cars-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/README.md b/resnet152-stanford-cars-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..5fcd0be4c4e150ec23aef531f2d95e876d51b5d5
--- /dev/null
+++ b/resnet152-stanford-cars-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stanford-cars.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: stanford-cars
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: train
+type: transformers
+val_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: test
+```
+
diff --git a/resnet152-stanford-cars-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/config.json b/resnet152-stanford-cars-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1e0f59991da08604f363224d408031555ecd60f4
--- /dev/null
+++ b/resnet152-stanford-cars-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,435 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "AM General Hummer SUV 2000",
+    "1": "Acura RL Sedan 2012",
+    "2": "Acura TL Sedan 2012",
+    "3": "Acura TL Type-S 2008",
+    "4": "Acura TSX Sedan 2012",
+    "5": "Acura Integra Type R 2001",
+    "6": "Acura ZDX Hatchback 2012",
+    "7": "Aston Martin V8 Vantage Convertible 2012",
+    "8": "Aston Martin V8 Vantage Coupe 2012",
+    "9": "Aston Martin Virage Convertible 2012",
+    "10": "Aston Martin Virage Coupe 2012",
+    "11": "Audi RS 4 Convertible 2008",
+    "12": "Audi A5 Coupe 2012",
+    "13": "Audi TTS Coupe 2012",
+    "14": "Audi R8 Coupe 2012",
+    "15": "Audi V8 Sedan 1994",
+    "16": "Audi 100 Sedan 1994",
+    "17": "Audi 100 Wagon 1994",
+    "18": "Audi TT Hatchback 2011",
+    "19": "Audi S6 Sedan 2011",
+    "20": "Audi S5 Convertible 2012",
+    "21": "Audi S5 Coupe 2012",
+    "22": "Audi S4 Sedan 2012",
+    "23": "Audi S4 Sedan 2007",
+    "24": "Audi TT RS Coupe 2012",
+    "25": "BMW ActiveHybrid 5 Sedan 2012",
+    "26": "BMW 1 Series Convertible 2012",
+    "27": "BMW 1 Series Coupe 2012",
+    "28": "BMW 3 Series Sedan 2012",
+    "29": "BMW 3 Series Wagon 2012",
+    "30": "BMW 6 Series Convertible 2007",
+    "31": "BMW X5 SUV 2007",
+    "32": "BMW X6 SUV 2012",
+    "33": "BMW M3 Coupe 2012",
+    "34": "BMW M5 Sedan 2010",
+    "35": "BMW M6 Convertible 2010",
+    "36": "BMW X3 SUV 2012",
+    "37": "BMW Z4 Convertible 2012",
+    "38": "Bentley Continental Supersports Conv. Convertible 2012",
+    "39": "Bentley Arnage Sedan 2009",
+    "40": "Bentley Mulsanne Sedan 2011",
+    "41": "Bentley Continental GT Coupe 2012",
+    "42": "Bentley Continental GT Coupe 2007",
+    "43": "Bentley Continental Flying Spur Sedan 2007",
+    "44": "Bugatti Veyron 16.4 Convertible 2009",
+    "45": "Bugatti Veyron 16.4 Coupe 2009",
+    "46": "Buick Regal GS 2012",
+    "47": "Buick Rainier SUV 2007",
+    "48": "Buick Verano Sedan 2012",
+    "49": "Buick Enclave SUV 2012",
+    "50": "Cadillac CTS-V Sedan 2012",
+    "51": "Cadillac SRX SUV 2012",
+    "52": "Cadillac Escalade EXT Crew Cab 2007",
+    "53": "Chevrolet Silverado 1500 Hybrid Crew Cab 2012",
+    "54": "Chevrolet Corvette Convertible 2012",
+    "55": "Chevrolet Corvette ZR1 2012",
+    "56": "Chevrolet Corvette Ron Fellows Edition Z06 2007",
+    "57": "Chevrolet Traverse SUV 2012",
+    "58": "Chevrolet Camaro Convertible 2012",
+    "59": "Chevrolet HHR SS 2010",
+    "60": "Chevrolet Impala Sedan 2007",
+    "61": "Chevrolet Tahoe Hybrid SUV 2012",
+    "62": "Chevrolet Sonic Sedan 2012",
+    "63": "Chevrolet Express Cargo Van 2007",
+    "64": "Chevrolet Avalanche Crew Cab 2012",
+    "65": "Chevrolet Cobalt SS 2010",
+    "66": "Chevrolet Malibu Hybrid Sedan 2010",
+    "67": "Chevrolet TrailBlazer SS 2009",
+    "68": "Chevrolet Silverado 2500HD Regular Cab 2012",
+    "69": "Chevrolet Silverado 1500 Classic Extended Cab 2007",
+    "70": "Chevrolet Express Van 2007",
+    "71": "Chevrolet Monte Carlo Coupe 2007",
+    "72": "Chevrolet Malibu Sedan 2007",
+    "73": "Chevrolet Silverado 1500 Extended Cab 2012",
+    "74": "Chevrolet Silverado 1500 Regular Cab 2012",
+    "75": "Chrysler Aspen SUV 2009",
+    "76": "Chrysler Sebring Convertible 2010",
+    "77": "Chrysler Town and Country Minivan 2012",
+    "78": "Chrysler 300 SRT-8 2010",
+    "79": "Chrysler Crossfire Convertible 2008",
+    "80": "Chrysler PT Cruiser Convertible 2008",
+    "81": "Daewoo Nubira Wagon 2002",
+    "82": "Dodge Caliber Wagon 2012",
+    "83": "Dodge Caliber Wagon 2007",
+    "84": "Dodge Caravan Minivan 1997",
+    "85": "Dodge Ram Pickup 3500 Crew Cab 2010",
+    "86": "Dodge Ram Pickup 3500 Quad Cab 2009",
+    "87": "Dodge Sprinter Cargo Van 2009",
+    "88": "Dodge Journey SUV 2012",
+    "89": "Dodge Dakota Crew Cab 2010",
+    "90": "Dodge Dakota Club Cab 2007",
+    "91": "Dodge Magnum Wagon 2008",
+    "92": "Dodge Challenger SRT8 2011",
+    "93": "Dodge Durango SUV 2012",
+    "94": "Dodge Durango SUV 2007",
+    "95": "Dodge Charger Sedan 2012",
+    "96": "Dodge Charger SRT-8 2009",
+    "97": "Eagle Talon Hatchback 1998",
+    "98": "FIAT 500 Abarth 2012",
+    "99": "FIAT 500 Convertible 2012",
+    "100": "Ferrari FF Coupe 2012",
+    "101": "Ferrari California Convertible 2012",
+    "102": "Ferrari 458 Italia Convertible 2012",
+    "103": "Ferrari 458 Italia Coupe 2012",
+    "104": "Fisker Karma Sedan 2012",
+    "105": "Ford F-450 Super Duty Crew Cab 2012",
+    "106": "Ford Mustang Convertible 2007",
+    "107": "Ford Freestar Minivan 2007",
+    "108": "Ford Expedition EL SUV 2009",
+    "109": "Ford Edge SUV 2012",
+    "110": "Ford Ranger SuperCab 2011",
+    "111": "Ford GT Coupe 2006",
+    "112": "Ford F-150 Regular Cab 2012",
+    "113": "Ford F-150 Regular Cab 2007",
+    "114": "Ford Focus Sedan 2007",
+    "115": "Ford E-Series Wagon Van 2012",
+    "116": "Ford Fiesta Sedan 2012",
+    "117": "GMC Terrain SUV 2012",
+    "118": "GMC Savana Van 2012",
+    "119": "GMC Yukon Hybrid SUV 2012",
+    "120": "GMC Acadia SUV 2012",
+    "121": "GMC Canyon Extended Cab 2012",
+    "122": "Geo Metro Convertible 1993",
+    "123": "HUMMER H3T Crew Cab 2010",
+    "124": "HUMMER H2 SUT Crew Cab 2009",
+    "125": "Honda Odyssey Minivan 2012",
+    "126": "Honda Odyssey Minivan 2007",
+    "127": "Honda Accord Coupe 2012",
+    "128": "Honda Accord Sedan 2012",
+    "129": "Hyundai Veloster Hatchback 2012",
+    "130": "Hyundai Santa Fe SUV 2012",
+    "131": "Hyundai Tucson SUV 2012",
+    "132": "Hyundai Veracruz SUV 2012",
+    "133": "Hyundai Sonata Hybrid Sedan 2012",
+    "134": "Hyundai Elantra Sedan 2007",
+    "135": "Hyundai Accent Sedan 2012",
+    "136": "Hyundai Genesis Sedan 2012",
+    "137": "Hyundai Sonata Sedan 2012",
+    "138": "Hyundai Elantra Touring Hatchback 2012",
+    "139": "Hyundai Azera Sedan 2012",
+    "140": "Infiniti G Coupe IPL 2012",
+    "141": "Infiniti QX56 SUV 2011",
+    "142": "Isuzu Ascender SUV 2008",
+    "143": "Jaguar XK XKR 2012",
+    "144": "Jeep Patriot SUV 2012",
+    "145": "Jeep Wrangler SUV 2012",
+    "146": "Jeep Liberty SUV 2012",
+    "147": "Jeep Grand Cherokee SUV 2012",
+    "148": "Jeep Compass SUV 2012",
+    "149": "Lamborghini Reventon Coupe 2008",
+    "150": "Lamborghini Aventador Coupe 2012",
+    "151": "Lamborghini Gallardo LP 570-4 Superleggera 2012",
+    "152": "Lamborghini Diablo Coupe 2001",
+    "153": "Land Rover Range Rover SUV 2012",
+    "154": "Land Rover LR2 SUV 2012",
+    "155": "Lincoln Town Car Sedan 2011",
+    "156": "MINI Cooper Roadster Convertible 2012",
+    "157": "Maybach Landaulet Convertible 2012",
+    "158": "Mazda Tribute SUV 2011",
+    "159": "McLaren MP4-12C Coupe 2012",
+    "160": "Mercedes-Benz 300-Class Convertible 1993",
+    "161": "Mercedes-Benz C-Class Sedan 2012",
+    "162": "Mercedes-Benz SL-Class Coupe 2009",
+    "163": "Mercedes-Benz E-Class Sedan 2012",
+    "164": "Mercedes-Benz S-Class Sedan 2012",
+    "165": "Mercedes-Benz Sprinter Van 2012",
+    "166": "Mitsubishi Lancer Sedan 2012",
+    "167": "Nissan Leaf Hatchback 2012",
+    "168": "Nissan NV Passenger Van 2012",
+    "169": "Nissan Juke Hatchback 2012",
+    "170": "Nissan 240SX Coupe 1998",
+    "171": "Plymouth Neon Coupe 1999",
+    "172": "Porsche Panamera Sedan 2012",
+    "173": "Ram C/V Cargo Van Minivan 2012",
+    "174": "Rolls-Royce Phantom Drophead Coupe Convertible 2012",
+    "175": "Rolls-Royce Ghost Sedan 2012",
+    "176": "Rolls-Royce Phantom Sedan 2012",
+    "177": "Scion xD Hatchback 2012",
+    "178": "Spyker C8 Convertible 2009",
+    "179": "Spyker C8 Coupe 2009",
+    "180": "Suzuki Aerio Sedan 2007",
+    "181": "Suzuki Kizashi Sedan 2012",
+    "182": "Suzuki SX4 Hatchback 2012",
+    "183": "Suzuki SX4 Sedan 2012",
+    "184": "Tesla Model S Sedan 2012",
+    "185": "Toyota Sequoia SUV 2012",
+    "186": "Toyota Camry Sedan 2012",
+    "187": "Toyota Corolla Sedan 2012",
+    "188": "Toyota 4Runner SUV 2012",
+    "189": "Volkswagen Golf Hatchback 2012",
+    "190": "Volkswagen Golf Hatchback 1991",
+    "191": "Volkswagen Beetle Hatchback 2012",
+    "192": "Volvo C30 Hatchback 2012",
+    "193": "Volvo 240 Sedan 1993",
+    "194": "Volvo XC90 SUV 2007",
+    "195": "smart fortwo Convertible 2012"
+  },
+  "label2id": {
+    "AM General Hummer SUV 2000": 0,
+    "Acura Integra Type R 2001": 5,
+    "Acura RL Sedan 2012": 1,
+    "Acura TL Sedan 2012": 2,
+    "Acura TL Type-S 2008": 3,
+    "Acura TSX Sedan 2012": 4,
+    "Acura ZDX Hatchback 2012": 6,
+    "Aston Martin V8 Vantage Convertible 2012": 7,
+    "Aston Martin V8 Vantage Coupe 2012": 8,
+    "Aston Martin Virage Convertible 2012": 9,
+    "Aston Martin Virage Coupe 2012": 10,
+    "Audi 100 Sedan 1994": 16,
+    "Audi 100 Wagon 1994": 17,
+    "Audi A5 Coupe 2012": 12,
+    "Audi R8 Coupe 2012": 14,
+    "Audi RS 4 Convertible 2008": 11,
+    "Audi S4 Sedan 2007": 23,
+    "Audi S4 Sedan 2012": 22,
+    "Audi S5 Convertible 2012": 20,
+    "Audi S5 Coupe 2012": 21,
+    "Audi S6 Sedan 2011": 19,
+    "Audi TT Hatchback 2011": 18,
+    "Audi TT RS Coupe 2012": 24,
+    "Audi TTS Coupe 2012": 13,
+    "Audi V8 Sedan 1994": 15,
+    "BMW 1 Series Convertible 2012": 26,
+    "BMW 1 Series Coupe 2012": 27,
+    "BMW 3 Series Sedan 2012": 28,
+    "BMW 3 Series Wagon 2012": 29,
+    "BMW 6 Series Convertible 2007": 30,
+    "BMW ActiveHybrid 5 Sedan 2012": 25,
+    "BMW M3 Coupe 2012": 33,
+    "BMW M5 Sedan 2010": 34,
+    "BMW M6 Convertible 2010": 35,
+    "BMW X3 SUV 2012": 36,
+    "BMW X5 SUV 2007": 31,
+    "BMW X6 SUV 2012": 32,
+    "BMW Z4 Convertible 2012": 37,
+    "Bentley Arnage Sedan 2009": 39,
+    "Bentley Continental Flying Spur Sedan 2007": 43,
+    "Bentley Continental GT Coupe 2007": 42,
+    "Bentley Continental GT Coupe 2012": 41,
+    "Bentley Continental Supersports Conv. Convertible 2012": 38,
+    "Bentley Mulsanne Sedan 2011": 40,
+    "Bugatti Veyron 16.4 Convertible 2009": 44,
+    "Bugatti Veyron 16.4 Coupe 2009": 45,
+    "Buick Enclave SUV 2012": 49,
+    "Buick Rainier SUV 2007": 47,
+    "Buick Regal GS 2012": 46,
+    "Buick Verano Sedan 2012": 48,
+    "Cadillac CTS-V Sedan 2012": 50,
+    "Cadillac Escalade EXT Crew Cab 2007": 52,
+    "Cadillac SRX SUV 2012": 51,
+    "Chevrolet Avalanche Crew Cab 2012": 64,
+    "Chevrolet Camaro Convertible 2012": 58,
+    "Chevrolet Cobalt SS 2010": 65,
+    "Chevrolet Corvette Convertible 2012": 54,
+    "Chevrolet Corvette Ron Fellows Edition Z06 2007": 56,
+    "Chevrolet Corvette ZR1 2012": 55,
+    "Chevrolet Express Cargo Van 2007": 63,
+    "Chevrolet Express Van 2007": 70,
+    "Chevrolet HHR SS 2010": 59,
+    "Chevrolet Impala Sedan 2007": 60,
+    "Chevrolet Malibu Hybrid Sedan 2010": 66,
+    "Chevrolet Malibu Sedan 2007": 72,
+    "Chevrolet Monte Carlo Coupe 2007": 71,
+    "Chevrolet Silverado 1500 Classic Extended Cab 2007": 69,
+    "Chevrolet Silverado 1500 Extended Cab 2012": 73,
+    "Chevrolet Silverado 1500 Hybrid Crew Cab 2012": 53,
+    "Chevrolet Silverado 1500 Regular Cab 2012": 74,
+    "Chevrolet Silverado 2500HD Regular Cab 2012": 68,
+    "Chevrolet Sonic Sedan 2012": 62,
+    "Chevrolet Tahoe Hybrid SUV 2012": 61,
+    "Chevrolet TrailBlazer SS 2009": 67,
+    "Chevrolet Traverse SUV 2012": 57,
+    "Chrysler 300 SRT-8 2010": 78,
+    "Chrysler Aspen SUV 2009": 75,
+    "Chrysler Crossfire Convertible 2008": 79,
+    "Chrysler PT Cruiser Convertible 2008": 80,
+    "Chrysler Sebring Convertible 2010": 76,
+    "Chrysler Town and Country Minivan 2012": 77,
+    "Daewoo Nubira Wagon 2002": 81,
+    "Dodge Caliber Wagon 2007": 83,
+    "Dodge Caliber Wagon 2012": 82,
+    "Dodge Caravan Minivan 1997": 84,
+    "Dodge Challenger SRT8 2011": 92,
+    "Dodge Charger SRT-8 2009": 96,
+    "Dodge Charger Sedan 2012": 95,
+    "Dodge Dakota Club Cab 2007": 90,
+    "Dodge Dakota Crew Cab 2010": 89,
+    "Dodge Durango SUV 2007": 94,
+    "Dodge Durango SUV 2012": 93,
+    "Dodge Journey SUV 2012": 88,
+    "Dodge Magnum Wagon 2008": 91,
+    "Dodge Ram Pickup 3500 Crew Cab 2010": 85,
+    "Dodge Ram Pickup 3500 Quad Cab 2009": 86,
+    "Dodge Sprinter Cargo Van 2009": 87,
+    "Eagle Talon Hatchback 1998": 97,
+    "FIAT 500 Abarth 2012": 98,
+    "FIAT 500 Convertible 2012": 99,
+    "Ferrari 458 Italia Convertible 2012": 102,
+    "Ferrari 458 Italia Coupe 2012": 103,
+    "Ferrari California Convertible 2012": 101,
+    "Ferrari FF Coupe 2012": 100,
+    "Fisker Karma Sedan 2012": 104,
+    "Ford E-Series Wagon Van 2012": 115,
+    "Ford Edge SUV 2012": 109,
+    "Ford Expedition EL SUV 2009": 108,
+    "Ford F-150 Regular Cab 2007": 113,
+    "Ford F-150 Regular Cab 2012": 112,
+    "Ford F-450 Super Duty Crew Cab 2012": 105,
+    "Ford Fiesta Sedan 2012": 116,
+    "Ford Focus Sedan 2007": 114,
+    "Ford Freestar Minivan 2007": 107,
+    "Ford GT Coupe 2006": 111,
+    "Ford Mustang Convertible 2007": 106,
+    "Ford Ranger SuperCab 2011": 110,
+    "GMC Acadia SUV 2012": 120,
+    "GMC Canyon Extended Cab 2012": 121,
+    "GMC Savana Van 2012": 118,
+    "GMC Terrain SUV 2012": 117,
+    "GMC Yukon Hybrid SUV 2012": 119,
+    "Geo Metro Convertible 1993": 122,
+    "HUMMER H2 SUT Crew Cab 2009": 124,
+    "HUMMER H3T Crew Cab 2010": 123,
+    "Honda Accord Coupe 2012": 127,
+    "Honda Accord Sedan 2012": 128,
+    "Honda Odyssey Minivan 2007": 126,
+    "Honda Odyssey Minivan 2012": 125,
+    "Hyundai Accent Sedan 2012": 135,
+    "Hyundai Azera Sedan 2012": 139,
+    "Hyundai Elantra Sedan 2007": 134,
+    "Hyundai Elantra Touring Hatchback 2012": 138,
+    "Hyundai Genesis Sedan 2012": 136,
+    "Hyundai Santa Fe SUV 2012": 130,
+    "Hyundai Sonata Hybrid Sedan 2012": 133,
+    "Hyundai Sonata Sedan 2012": 137,
+    "Hyundai Tucson SUV 2012": 131,
+    "Hyundai Veloster Hatchback 2012": 129,
+    "Hyundai Veracruz SUV 2012": 132,
+    "Infiniti G Coupe IPL 2012": 140,
+    "Infiniti QX56 SUV 2011": 141,
+    "Isuzu Ascender SUV 2008": 142,
+    "Jaguar XK XKR 2012": 143,
+    "Jeep Compass SUV 2012": 148,
+    "Jeep Grand Cherokee SUV 2012": 147,
+    "Jeep Liberty SUV 2012": 146,
+    "Jeep Patriot SUV 2012": 144,
+    "Jeep Wrangler SUV 2012": 145,
+    "Lamborghini Aventador Coupe 2012": 150,
+    "Lamborghini Diablo Coupe 2001": 152,
+    "Lamborghini Gallardo LP 570-4 Superleggera 2012": 151,
+    "Lamborghini Reventon Coupe 2008": 149,
+    "Land Rover LR2 SUV 2012": 154,
+    "Land Rover Range Rover SUV 2012": 153,
+    "Lincoln Town Car Sedan 2011": 155,
+    "MINI Cooper Roadster Convertible 2012": 156,
+    "Maybach Landaulet Convertible 2012": 157,
+    "Mazda Tribute SUV 2011": 158,
+    "McLaren MP4-12C Coupe 2012": 159,
+    "Mercedes-Benz 300-Class Convertible 1993": 160,
+    "Mercedes-Benz C-Class Sedan 2012": 161,
+    "Mercedes-Benz E-Class Sedan 2012": 163,
+    "Mercedes-Benz S-Class Sedan 2012": 164,
+    "Mercedes-Benz SL-Class Coupe 2009": 162,
+    "Mercedes-Benz Sprinter Van 2012": 165,
+    "Mitsubishi Lancer Sedan 2012": 166,
+    "Nissan 240SX Coupe 1998": 170,
+    "Nissan Juke Hatchback 2012": 169,
+    "Nissan Leaf Hatchback 2012": 167,
+    "Nissan NV Passenger Van 2012": 168,
+    "Plymouth Neon Coupe 1999": 171,
+    "Porsche Panamera Sedan 2012": 172,
+    "Ram C/V Cargo Van Minivan 2012": 173,
+    "Rolls-Royce Ghost Sedan 2012": 175,
+    "Rolls-Royce Phantom Drophead Coupe Convertible 2012": 174,
+    "Rolls-Royce Phantom Sedan 2012": 176,
+    "Scion xD Hatchback 2012": 177,
+    "Spyker C8 Convertible 2009": 178,
+    "Spyker C8 Coupe 2009": 179,
+    "Suzuki Aerio Sedan 2007": 180,
+    "Suzuki Kizashi Sedan 2012": 181,
+    "Suzuki SX4 Hatchback 2012": 182,
+    "Suzuki SX4 Sedan 2012": 183,
+    "Tesla Model S Sedan 2012": 184,
+    "Toyota 4Runner SUV 2012": 188,
+    "Toyota Camry Sedan 2012": 186,
+    "Toyota Corolla Sedan 2012": 187,
+    "Toyota Sequoia SUV 2012": 185,
+    "Volkswagen Beetle Hatchback 2012": 191,
+    "Volkswagen Golf Hatchback 1991": 190,
+    "Volkswagen Golf Hatchback 2012": 189,
+    "Volvo 240 Sedan 1993": 193,
+    "Volvo C30 Hatchback 2012": 192,
+    "Volvo XC90 SUV 2007": 194,
+    "smart fortwo Convertible 2012": 195
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-stanford-cars-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet152-stanford-cars-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-stanford-cars-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-stanford-cars-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/README.md b/resnet152-stanford-cars-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e21805c7ff136f487586145e67608d3d23bcd1d4
--- /dev/null
+++ b/resnet152-stanford-cars-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stanford-cars.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: stanford-cars
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: train
+type: transformers
+val_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: test
+```
+
diff --git a/resnet152-stanford-cars-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/config.json b/resnet152-stanford-cars-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1e0f59991da08604f363224d408031555ecd60f4
--- /dev/null
+++ b/resnet152-stanford-cars-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,435 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "AM General Hummer SUV 2000",
+    "1": "Acura RL Sedan 2012",
+    "2": "Acura TL Sedan 2012",
+    "3": "Acura TL Type-S 2008",
+    "4": "Acura TSX Sedan 2012",
+    "5": "Acura Integra Type R 2001",
+    "6": "Acura ZDX Hatchback 2012",
+    "7": "Aston Martin V8 Vantage Convertible 2012",
+    "8": "Aston Martin V8 Vantage Coupe 2012",
+    "9": "Aston Martin Virage Convertible 2012",
+    "10": "Aston Martin Virage Coupe 2012",
+    "11": "Audi RS 4 Convertible 2008",
+    "12": "Audi A5 Coupe 2012",
+    "13": "Audi TTS Coupe 2012",
+    "14": "Audi R8 Coupe 2012",
+    "15": "Audi V8 Sedan 1994",
+    "16": "Audi 100 Sedan 1994",
+    "17": "Audi 100 Wagon 1994",
+    "18": "Audi TT Hatchback 2011",
+    "19": "Audi S6 Sedan 2011",
+    "20": "Audi S5 Convertible 2012",
+    "21": "Audi S5 Coupe 2012",
+    "22": "Audi S4 Sedan 2012",
+    "23": "Audi S4 Sedan 2007",
+    "24": "Audi TT RS Coupe 2012",
+    "25": "BMW ActiveHybrid 5 Sedan 2012",
+    "26": "BMW 1 Series Convertible 2012",
+    "27": "BMW 1 Series Coupe 2012",
+    "28": "BMW 3 Series Sedan 2012",
+    "29": "BMW 3 Series Wagon 2012",
+    "30": "BMW 6 Series Convertible 2007",
+    "31": "BMW X5 SUV 2007",
+    "32": "BMW X6 SUV 2012",
+    "33": "BMW M3 Coupe 2012",
+    "34": "BMW M5 Sedan 2010",
+    "35": "BMW M6 Convertible 2010",
+    "36": "BMW X3 SUV 2012",
+    "37": "BMW Z4 Convertible 2012",
+    "38": "Bentley Continental Supersports Conv. Convertible 2012",
+    "39": "Bentley Arnage Sedan 2009",
+    "40": "Bentley Mulsanne Sedan 2011",
+    "41": "Bentley Continental GT Coupe 2012",
+    "42": "Bentley Continental GT Coupe 2007",
+    "43": "Bentley Continental Flying Spur Sedan 2007",
+    "44": "Bugatti Veyron 16.4 Convertible 2009",
+    "45": "Bugatti Veyron 16.4 Coupe 2009",
+    "46": "Buick Regal GS 2012",
+    "47": "Buick Rainier SUV 2007",
+    "48": "Buick Verano Sedan 2012",
+    "49": "Buick Enclave SUV 2012",
+    "50": "Cadillac CTS-V Sedan 2012",
+    "51": "Cadillac SRX SUV 2012",
+    "52": "Cadillac Escalade EXT Crew Cab 2007",
+    "53": "Chevrolet Silverado 1500 Hybrid Crew Cab 2012",
+    "54": "Chevrolet Corvette Convertible 2012",
+    "55": "Chevrolet Corvette ZR1 2012",
+    "56": "Chevrolet Corvette Ron Fellows Edition Z06 2007",
+    "57": "Chevrolet Traverse SUV 2012",
+    "58": "Chevrolet Camaro Convertible 2012",
+    "59": "Chevrolet HHR SS 2010",
+    "60": "Chevrolet Impala Sedan 2007",
+    "61": "Chevrolet Tahoe Hybrid SUV 2012",
+    "62": "Chevrolet Sonic Sedan 2012",
+    "63": "Chevrolet Express Cargo Van 2007",
+    "64": "Chevrolet Avalanche Crew Cab 2012",
+    "65": "Chevrolet Cobalt SS 2010",
+    "66": "Chevrolet Malibu Hybrid Sedan 2010",
+    "67": "Chevrolet TrailBlazer SS 2009",
+    "68": "Chevrolet Silverado 2500HD Regular Cab 2012",
+    "69": "Chevrolet Silverado 1500 Classic Extended Cab 2007",
+    "70": "Chevrolet Express Van 2007",
+    "71": "Chevrolet Monte Carlo Coupe 2007",
+    "72": "Chevrolet Malibu Sedan 2007",
+    "73": "Chevrolet Silverado 1500 Extended Cab 2012",
+    "74": "Chevrolet Silverado 1500 Regular Cab 2012",
+    "75": "Chrysler Aspen SUV 2009",
+    "76": "Chrysler Sebring Convertible 2010",
+    "77": "Chrysler Town and Country Minivan 2012",
+    "78": "Chrysler 300 SRT-8 2010",
+    "79": "Chrysler Crossfire Convertible 2008",
+    "80": "Chrysler PT Cruiser Convertible 2008",
+    "81": "Daewoo Nubira Wagon 2002",
+    "82": "Dodge Caliber Wagon 2012",
+    "83": "Dodge Caliber Wagon 2007",
+    "84": "Dodge Caravan Minivan 1997",
+    "85": "Dodge Ram Pickup 3500 Crew Cab 2010",
+    "86": "Dodge Ram Pickup 3500 Quad Cab 2009",
+    "87": "Dodge Sprinter Cargo Van 2009",
+    "88": "Dodge Journey SUV 2012",
+    "89": "Dodge Dakota Crew Cab 2010",
+    "90": "Dodge Dakota Club Cab 2007",
+    "91": "Dodge Magnum Wagon 2008",
+    "92": "Dodge Challenger SRT8 2011",
+    "93": "Dodge Durango SUV 2012",
+    "94": "Dodge Durango SUV 2007",
+    "95": "Dodge Charger Sedan 2012",
+    "96": "Dodge Charger SRT-8 2009",
+    "97": "Eagle Talon Hatchback 1998",
+    "98": "FIAT 500 Abarth 2012",
+    "99": "FIAT 500 Convertible 2012",
+    "100": "Ferrari FF Coupe 2012",
+    "101": "Ferrari California Convertible 2012",
+    "102": "Ferrari 458 Italia Convertible 2012",
+    "103": "Ferrari 458 Italia Coupe 2012",
+    "104": "Fisker Karma Sedan 2012",
+    "105": "Ford F-450 Super Duty Crew Cab 2012",
+    "106": "Ford Mustang Convertible 2007",
+    "107": "Ford Freestar Minivan 2007",
+    "108": "Ford Expedition EL SUV 2009",
+    "109": "Ford Edge SUV 2012",
+    "110": "Ford Ranger SuperCab 2011",
+    "111": "Ford GT Coupe 2006",
+    "112": "Ford F-150 Regular Cab 2012",
+    "113": "Ford F-150 Regular Cab 2007",
+    "114": "Ford Focus Sedan 2007",
+    "115": "Ford E-Series Wagon Van 2012",
+    "116": "Ford Fiesta Sedan 2012",
+    "117": "GMC Terrain SUV 2012",
+    "118": "GMC Savana Van 2012",
+    "119": "GMC Yukon Hybrid SUV 2012",
+    "120": "GMC Acadia SUV 2012",
+    "121": "GMC Canyon Extended Cab 2012",
+    "122": "Geo Metro Convertible 1993",
+    "123": "HUMMER H3T Crew Cab 2010",
+    "124": "HUMMER H2 SUT Crew Cab 2009",
+    "125": "Honda Odyssey Minivan 2012",
+    "126": "Honda Odyssey Minivan 2007",
+    "127": "Honda Accord Coupe 2012",
+    "128": "Honda Accord Sedan 2012",
+    "129": "Hyundai Veloster Hatchback 2012",
+    "130": "Hyundai Santa Fe SUV 2012",
+    "131": "Hyundai Tucson SUV 2012",
+    "132": "Hyundai Veracruz SUV 2012",
+    "133": "Hyundai Sonata Hybrid Sedan 2012",
+    "134": "Hyundai Elantra Sedan 2007",
+    "135": "Hyundai Accent Sedan 2012",
+    "136": "Hyundai Genesis Sedan 2012",
+    "137": "Hyundai Sonata Sedan 2012",
+    "138": "Hyundai Elantra Touring Hatchback 2012",
+    "139": "Hyundai Azera Sedan 2012",
+    "140": "Infiniti G Coupe IPL 2012",
+    "141": "Infiniti QX56 SUV 2011",
+    "142": "Isuzu Ascender SUV 2008",
+    "143": "Jaguar XK XKR 2012",
+    "144": "Jeep Patriot SUV 2012",
+    "145": "Jeep Wrangler SUV 2012",
+    "146": "Jeep Liberty SUV 2012",
+    "147": "Jeep Grand Cherokee SUV 2012",
+    "148": "Jeep Compass SUV 2012",
+    "149": "Lamborghini Reventon Coupe 2008",
+    "150": "Lamborghini Aventador Coupe 2012",
+    "151": "Lamborghini Gallardo LP 570-4 Superleggera 2012",
+    "152": "Lamborghini Diablo Coupe 2001",
+    "153": "Land Rover Range Rover SUV 2012",
+    "154": "Land Rover LR2 SUV 2012",
+    "155": "Lincoln Town Car Sedan 2011",
+    "156": "MINI Cooper Roadster Convertible 2012",
+    "157": "Maybach Landaulet Convertible 2012",
+    "158": "Mazda Tribute SUV 2011",
+    "159": "McLaren MP4-12C Coupe 2012",
+    "160": "Mercedes-Benz 300-Class Convertible 1993",
+    "161": "Mercedes-Benz C-Class Sedan 2012",
+    "162": "Mercedes-Benz SL-Class Coupe 2009",
+    "163": "Mercedes-Benz E-Class Sedan 2012",
+    "164": "Mercedes-Benz S-Class Sedan 2012",
+    "165": "Mercedes-Benz Sprinter Van 2012",
+    "166": "Mitsubishi Lancer Sedan 2012",
+    "167": "Nissan Leaf Hatchback 2012",
+    "168": "Nissan NV Passenger Van 2012",
+    "169": "Nissan Juke Hatchback 2012",
+    "170": "Nissan 240SX Coupe 1998",
+    "171": "Plymouth Neon Coupe 1999",
+    "172": "Porsche Panamera Sedan 2012",
+    "173": "Ram C/V Cargo Van Minivan 2012",
+    "174": "Rolls-Royce Phantom Drophead Coupe Convertible 2012",
+    "175": "Rolls-Royce Ghost Sedan 2012",
+    "176": "Rolls-Royce Phantom Sedan 2012",
+    "177": "Scion xD Hatchback 2012",
+    "178": "Spyker C8 Convertible 2009",
+    "179": "Spyker C8 Coupe 2009",
+    "180": "Suzuki Aerio Sedan 2007",
+    "181": "Suzuki Kizashi Sedan 2012",
+    "182": "Suzuki SX4 Hatchback 2012",
+    "183": "Suzuki SX4 Sedan 2012",
+    "184": "Tesla Model S Sedan 2012",
+    "185": "Toyota Sequoia SUV 2012",
+    "186": "Toyota Camry Sedan 2012",
+    "187": "Toyota Corolla Sedan 2012",
+    "188": "Toyota 4Runner SUV 2012",
+    "189": "Volkswagen Golf Hatchback 2012",
+    "190": "Volkswagen Golf Hatchback 1991",
+    "191": "Volkswagen Beetle Hatchback 2012",
+    "192": "Volvo C30 Hatchback 2012",
+    "193": "Volvo 240 Sedan 1993",
+    "194": "Volvo XC90 SUV 2007",
+    "195": "smart fortwo Convertible 2012"
+  },
+  "label2id": {
+    "AM General Hummer SUV 2000": 0,
+    "Acura Integra Type R 2001": 5,
+    "Acura RL Sedan 2012": 1,
+    "Acura TL Sedan 2012": 2,
+    "Acura TL Type-S 2008": 3,
+    "Acura TSX Sedan 2012": 4,
+    "Acura ZDX Hatchback 2012": 6,
+    "Aston Martin V8 Vantage Convertible 2012": 7,
+    "Aston Martin V8 Vantage Coupe 2012": 8,
+    "Aston Martin Virage Convertible 2012": 9,
+    "Aston Martin Virage Coupe 2012": 10,
+    "Audi 100 Sedan 1994": 16,
+    "Audi 100 Wagon 1994": 17,
+    "Audi A5 Coupe 2012": 12,
+    "Audi R8 Coupe 2012": 14,
+    "Audi RS 4 Convertible 2008": 11,
+    "Audi S4 Sedan 2007": 23,
+    "Audi S4 Sedan 2012": 22,
+    "Audi S5 Convertible 2012": 20,
+    "Audi S5 Coupe 2012": 21,
+    "Audi S6 Sedan 2011": 19,
+    "Audi TT Hatchback 2011": 18,
+    "Audi TT RS Coupe 2012": 24,
+    "Audi TTS Coupe 2012": 13,
+    "Audi V8 Sedan 1994": 15,
+    "BMW 1 Series Convertible 2012": 26,
+    "BMW 1 Series Coupe 2012": 27,
+    "BMW 3 Series Sedan 2012": 28,
+    "BMW 3 Series Wagon 2012": 29,
+    "BMW 6 Series Convertible 2007": 30,
+    "BMW ActiveHybrid 5 Sedan 2012": 25,
+    "BMW M3 Coupe 2012": 33,
+    "BMW M5 Sedan 2010": 34,
+    "BMW M6 Convertible 2010": 35,
+    "BMW X3 SUV 2012": 36,
+    "BMW X5 SUV 2007": 31,
+    "BMW X6 SUV 2012": 32,
+    "BMW Z4 Convertible 2012": 37,
+    "Bentley Arnage Sedan 2009": 39,
+    "Bentley Continental Flying Spur Sedan 2007": 43,
+    "Bentley Continental GT Coupe 2007": 42,
+    "Bentley Continental GT Coupe 2012": 41,
+    "Bentley Continental Supersports Conv. Convertible 2012": 38,
+    "Bentley Mulsanne Sedan 2011": 40,
+    "Bugatti Veyron 16.4 Convertible 2009": 44,
+    "Bugatti Veyron 16.4 Coupe 2009": 45,
+    "Buick Enclave SUV 2012": 49,
+    "Buick Rainier SUV 2007": 47,
+    "Buick Regal GS 2012": 46,
+    "Buick Verano Sedan 2012": 48,
+    "Cadillac CTS-V Sedan 2012": 50,
+    "Cadillac Escalade EXT Crew Cab 2007": 52,
+    "Cadillac SRX SUV 2012": 51,
+    "Chevrolet Avalanche Crew Cab 2012": 64,
+    "Chevrolet Camaro Convertible 2012": 58,
+    "Chevrolet Cobalt SS 2010": 65,
+    "Chevrolet Corvette Convertible 2012": 54,
+    "Chevrolet Corvette Ron Fellows Edition Z06 2007": 56,
+    "Chevrolet Corvette ZR1 2012": 55,
+    "Chevrolet Express Cargo Van 2007": 63,
+    "Chevrolet Express Van 2007": 70,
+    "Chevrolet HHR SS 2010": 59,
+    "Chevrolet Impala Sedan 2007": 60,
+    "Chevrolet Malibu Hybrid Sedan 2010": 66,
+    "Chevrolet Malibu Sedan 2007": 72,
+    "Chevrolet Monte Carlo Coupe 2007": 71,
+    "Chevrolet Silverado 1500 Classic Extended Cab 2007": 69,
+    "Chevrolet Silverado 1500 Extended Cab 2012": 73,
+    "Chevrolet Silverado 1500 Hybrid Crew Cab 2012": 53,
+    "Chevrolet Silverado 1500 Regular Cab 2012": 74,
+    "Chevrolet Silverado 2500HD Regular Cab 2012": 68,
+    "Chevrolet Sonic Sedan 2012": 62,
+    "Chevrolet Tahoe Hybrid SUV 2012": 61,
+    "Chevrolet TrailBlazer SS 2009": 67,
+    "Chevrolet Traverse SUV 2012": 57,
+    "Chrysler 300 SRT-8 2010": 78,
+    "Chrysler Aspen SUV 2009": 75,
+    "Chrysler Crossfire Convertible 2008": 79,
+    "Chrysler PT Cruiser Convertible 2008": 80,
+    "Chrysler Sebring Convertible 2010": 76,
+    "Chrysler Town and Country Minivan 2012": 77,
+    "Daewoo Nubira Wagon 2002": 81,
+    "Dodge Caliber Wagon 2007": 83,
+    "Dodge Caliber Wagon 2012": 82,
+    "Dodge Caravan Minivan 1997": 84,
+    "Dodge Challenger SRT8 2011": 92,
+    "Dodge Charger SRT-8 2009": 96,
+    "Dodge Charger Sedan 2012": 95,
+    "Dodge Dakota Club Cab 2007": 90,
+    "Dodge Dakota Crew Cab 2010": 89,
+    "Dodge Durango SUV 2007": 94,
+    "Dodge Durango SUV 2012": 93,
+    "Dodge Journey SUV 2012": 88,
+    "Dodge Magnum Wagon 2008": 91,
+    "Dodge Ram Pickup 3500 Crew Cab 2010": 85,
+    "Dodge Ram Pickup 3500 Quad Cab 2009": 86,
+    "Dodge Sprinter Cargo Van 2009": 87,
+    "Eagle Talon Hatchback 1998": 97,
+    "FIAT 500 Abarth 2012": 98,
+    "FIAT 500 Convertible 2012": 99,
+    "Ferrari 458 Italia Convertible 2012": 102,
+    "Ferrari 458 Italia Coupe 2012": 103,
+    "Ferrari California Convertible 2012": 101,
+    "Ferrari FF Coupe 2012": 100,
+    "Fisker Karma Sedan 2012": 104,
+    "Ford E-Series Wagon Van 2012": 115,
+    "Ford Edge SUV 2012": 109,
+    "Ford Expedition EL SUV 2009": 108,
+    "Ford F-150 Regular Cab 2007": 113,
+    "Ford F-150 Regular Cab 2012": 112,
+    "Ford F-450 Super Duty Crew Cab 2012": 105,
+    "Ford Fiesta Sedan 2012": 116,
+    "Ford Focus Sedan 2007": 114,
+    "Ford Freestar Minivan 2007": 107,
+    "Ford GT Coupe 2006": 111,
+    "Ford Mustang Convertible 2007": 106,
+    "Ford Ranger SuperCab 2011": 110,
+    "GMC Acadia SUV 2012": 120,
+    "GMC Canyon Extended Cab 2012": 121,
+    "GMC Savana Van 2012": 118,
+    "GMC Terrain SUV 2012": 117,
+    "GMC Yukon Hybrid SUV 2012": 119,
+    "Geo Metro Convertible 1993": 122,
+    "HUMMER H2 SUT Crew Cab 2009": 124,
+    "HUMMER H3T Crew Cab 2010": 123,
+    "Honda Accord Coupe 2012": 127,
+    "Honda Accord Sedan 2012": 128,
+    "Honda Odyssey Minivan 2007": 126,
+    "Honda Odyssey Minivan 2012": 125,
+    "Hyundai Accent Sedan 2012": 135,
+    "Hyundai Azera Sedan 2012": 139,
+    "Hyundai Elantra Sedan 2007": 134,
+    "Hyundai Elantra Touring Hatchback 2012": 138,
+    "Hyundai Genesis Sedan 2012": 136,
+    "Hyundai Santa Fe SUV 2012": 130,
+    "Hyundai Sonata Hybrid Sedan 2012": 133,
+    "Hyundai Sonata Sedan 2012": 137,
+    "Hyundai Tucson SUV 2012": 131,
+    "Hyundai Veloster Hatchback 2012": 129,
+    "Hyundai Veracruz SUV 2012": 132,
+    "Infiniti G Coupe IPL 2012": 140,
+    "Infiniti QX56 SUV 2011": 141,
+    "Isuzu Ascender SUV 2008": 142,
+    "Jaguar XK XKR 2012": 143,
+    "Jeep Compass SUV 2012": 148,
+    "Jeep Grand Cherokee SUV 2012": 147,
+    "Jeep Liberty SUV 2012": 146,
+    "Jeep Patriot SUV 2012": 144,
+    "Jeep Wrangler SUV 2012": 145,
+    "Lamborghini Aventador Coupe 2012": 150,
+    "Lamborghini Diablo Coupe 2001": 152,
+    "Lamborghini Gallardo LP 570-4 Superleggera 2012": 151,
+    "Lamborghini Reventon Coupe 2008": 149,
+    "Land Rover LR2 SUV 2012": 154,
+    "Land Rover Range Rover SUV 2012": 153,
+    "Lincoln Town Car Sedan 2011": 155,
+    "MINI Cooper Roadster Convertible 2012": 156,
+    "Maybach Landaulet Convertible 2012": 157,
+    "Mazda Tribute SUV 2011": 158,
+    "McLaren MP4-12C Coupe 2012": 159,
+    "Mercedes-Benz 300-Class Convertible 1993": 160,
+    "Mercedes-Benz C-Class Sedan 2012": 161,
+    "Mercedes-Benz E-Class Sedan 2012": 163,
+    "Mercedes-Benz S-Class Sedan 2012": 164,
+    "Mercedes-Benz SL-Class Coupe 2009": 162,
+    "Mercedes-Benz Sprinter Van 2012": 165,
+    "Mitsubishi Lancer Sedan 2012": 166,
+    "Nissan 240SX Coupe 1998": 170,
+    "Nissan Juke Hatchback 2012": 169,
+    "Nissan Leaf Hatchback 2012": 167,
+    "Nissan NV Passenger Van 2012": 168,
+    "Plymouth Neon Coupe 1999": 171,
+    "Porsche Panamera Sedan 2012": 172,
+    "Ram C/V Cargo Van Minivan 2012": 173,
+    "Rolls-Royce Ghost Sedan 2012": 175,
+    "Rolls-Royce Phantom Drophead Coupe Convertible 2012": 174,
+    "Rolls-Royce Phantom Sedan 2012": 176,
+    "Scion xD Hatchback 2012": 177,
+    "Spyker C8 Convertible 2009": 178,
+    "Spyker C8 Coupe 2009": 179,
+    "Suzuki Aerio Sedan 2007": 180,
+    "Suzuki Kizashi Sedan 2012": 181,
+    "Suzuki SX4 Hatchback 2012": 182,
+    "Suzuki SX4 Sedan 2012": 183,
+    "Tesla Model S Sedan 2012": 184,
+    "Toyota 4Runner SUV 2012": 188,
+    "Toyota Camry Sedan 2012": 186,
+    "Toyota Corolla Sedan 2012": 187,
+    "Toyota Sequoia SUV 2012": 185,
+    "Volkswagen Beetle Hatchback 2012": 191,
+    "Volkswagen Golf Hatchback 1991": 190,
+    "Volkswagen Golf Hatchback 2012": 189,
+    "Volvo 240 Sedan 1993": 193,
+    "Volvo C30 Hatchback 2012": 192,
+    "Volvo XC90 SUV 2007": 194,
+    "smart fortwo Convertible 2012": 195
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-stanford-cars-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet152-stanford-cars-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-stanford-cars-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/README.md b/resnet152-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..87da44ac33dbfa8028ca1cd21053441832694274
--- /dev/null
+++ b/resnet152-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stanford-cars.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: stanford-cars
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: train
+type: transformers
+val_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: test
+```
+
diff --git a/resnet152-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/config.json b/resnet152-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1e0f59991da08604f363224d408031555ecd60f4
--- /dev/null
+++ b/resnet152-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,435 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "AM General Hummer SUV 2000",
+    "1": "Acura RL Sedan 2012",
+    "2": "Acura TL Sedan 2012",
+    "3": "Acura TL Type-S 2008",
+    "4": "Acura TSX Sedan 2012",
+    "5": "Acura Integra Type R 2001",
+    "6": "Acura ZDX Hatchback 2012",
+    "7": "Aston Martin V8 Vantage Convertible 2012",
+    "8": "Aston Martin V8 Vantage Coupe 2012",
+    "9": "Aston Martin Virage Convertible 2012",
+    "10": "Aston Martin Virage Coupe 2012",
+    "11": "Audi RS 4 Convertible 2008",
+    "12": "Audi A5 Coupe 2012",
+    "13": "Audi TTS Coupe 2012",
+    "14": "Audi R8 Coupe 2012",
+    "15": "Audi V8 Sedan 1994",
+    "16": "Audi 100 Sedan 1994",
+    "17": "Audi 100 Wagon 1994",
+    "18": "Audi TT Hatchback 2011",
+    "19": "Audi S6 Sedan 2011",
+    "20": "Audi S5 Convertible 2012",
+    "21": "Audi S5 Coupe 2012",
+    "22": "Audi S4 Sedan 2012",
+    "23": "Audi S4 Sedan 2007",
+    "24": "Audi TT RS Coupe 2012",
+    "25": "BMW ActiveHybrid 5 Sedan 2012",
+    "26": "BMW 1 Series Convertible 2012",
+    "27": "BMW 1 Series Coupe 2012",
+    "28": "BMW 3 Series Sedan 2012",
+    "29": "BMW 3 Series Wagon 2012",
+    "30": "BMW 6 Series Convertible 2007",
+    "31": "BMW X5 SUV 2007",
+    "32": "BMW X6 SUV 2012",
+    "33": "BMW M3 Coupe 2012",
+    "34": "BMW M5 Sedan 2010",
+    "35": "BMW M6 Convertible 2010",
+    "36": "BMW X3 SUV 2012",
+    "37": "BMW Z4 Convertible 2012",
+    "38": "Bentley Continental Supersports Conv. Convertible 2012",
+    "39": "Bentley Arnage Sedan 2009",
+    "40": "Bentley Mulsanne Sedan 2011",
+    "41": "Bentley Continental GT Coupe 2012",
+    "42": "Bentley Continental GT Coupe 2007",
+    "43": "Bentley Continental Flying Spur Sedan 2007",
+    "44": "Bugatti Veyron 16.4 Convertible 2009",
+    "45": "Bugatti Veyron 16.4 Coupe 2009",
+    "46": "Buick Regal GS 2012",
+    "47": "Buick Rainier SUV 2007",
+    "48": "Buick Verano Sedan 2012",
+    "49": "Buick Enclave SUV 2012",
+    "50": "Cadillac CTS-V Sedan 2012",
+    "51": "Cadillac SRX SUV 2012",
+    "52": "Cadillac Escalade EXT Crew Cab 2007",
+    "53": "Chevrolet Silverado 1500 Hybrid Crew Cab 2012",
+    "54": "Chevrolet Corvette Convertible 2012",
+    "55": "Chevrolet Corvette ZR1 2012",
+    "56": "Chevrolet Corvette Ron Fellows Edition Z06 2007",
+    "57": "Chevrolet Traverse SUV 2012",
+    "58": "Chevrolet Camaro Convertible 2012",
+    "59": "Chevrolet HHR SS 2010",
+    "60": "Chevrolet Impala Sedan 2007",
+    "61": "Chevrolet Tahoe Hybrid SUV 2012",
+    "62": "Chevrolet Sonic Sedan 2012",
+    "63": "Chevrolet Express Cargo Van 2007",
+    "64": "Chevrolet Avalanche Crew Cab 2012",
+    "65": "Chevrolet Cobalt SS 2010",
+    "66": "Chevrolet Malibu Hybrid Sedan 2010",
+    "67": "Chevrolet TrailBlazer SS 2009",
+    "68": "Chevrolet Silverado 2500HD Regular Cab 2012",
+    "69": "Chevrolet Silverado 1500 Classic Extended Cab 2007",
+    "70": "Chevrolet Express Van 2007",
+    "71": "Chevrolet Monte Carlo Coupe 2007",
+    "72": "Chevrolet Malibu Sedan 2007",
+    "73": "Chevrolet Silverado 1500 Extended Cab 2012",
+    "74": "Chevrolet Silverado 1500 Regular Cab 2012",
+    "75": "Chrysler Aspen SUV 2009",
+    "76": "Chrysler Sebring Convertible 2010",
+    "77": "Chrysler Town and Country Minivan 2012",
+    "78": "Chrysler 300 SRT-8 2010",
+    "79": "Chrysler Crossfire Convertible 2008",
+    "80": "Chrysler PT Cruiser Convertible 2008",
+    "81": "Daewoo Nubira Wagon 2002",
+    "82": "Dodge Caliber Wagon 2012",
+    "83": "Dodge Caliber Wagon 2007",
+    "84": "Dodge Caravan Minivan 1997",
+    "85": "Dodge Ram Pickup 3500 Crew Cab 2010",
+    "86": "Dodge Ram Pickup 3500 Quad Cab 2009",
+    "87": "Dodge Sprinter Cargo Van 2009",
+    "88": "Dodge Journey SUV 2012",
+    "89": "Dodge Dakota Crew Cab 2010",
+    "90": "Dodge Dakota Club Cab 2007",
+    "91": "Dodge Magnum Wagon 2008",
+    "92": "Dodge Challenger SRT8 2011",
+    "93": "Dodge Durango SUV 2012",
+    "94": "Dodge Durango SUV 2007",
+    "95": "Dodge Charger Sedan 2012",
+    "96": "Dodge Charger SRT-8 2009",
+    "97": "Eagle Talon Hatchback 1998",
+    "98": "FIAT 500 Abarth 2012",
+    "99": "FIAT 500 Convertible 2012",
+    "100": "Ferrari FF Coupe 2012",
+    "101": "Ferrari California Convertible 2012",
+    "102": "Ferrari 458 Italia Convertible 2012",
+    "103": "Ferrari 458 Italia Coupe 2012",
+    "104": "Fisker Karma Sedan 2012",
+    "105": "Ford F-450 Super Duty Crew Cab 2012",
+    "106": "Ford Mustang Convertible 2007",
+    "107": "Ford Freestar Minivan 2007",
+    "108": "Ford Expedition EL SUV 2009",
+    "109": "Ford Edge SUV 2012",
+    "110": "Ford Ranger SuperCab 2011",
+    "111": "Ford GT Coupe 2006",
+    "112": "Ford F-150 Regular Cab 2012",
+    "113": "Ford F-150 Regular Cab 2007",
+    "114": "Ford Focus Sedan 2007",
+    "115": "Ford E-Series Wagon Van 2012",
+    "116": "Ford Fiesta Sedan 2012",
+    "117": "GMC Terrain SUV 2012",
+    "118": "GMC Savana Van 2012",
+    "119": "GMC Yukon Hybrid SUV 2012",
+    "120": "GMC Acadia SUV 2012",
+    "121": "GMC Canyon Extended Cab 2012",
+    "122": "Geo Metro Convertible 1993",
+    "123": "HUMMER H3T Crew Cab 2010",
+    "124": "HUMMER H2 SUT Crew Cab 2009",
+    "125": "Honda Odyssey Minivan 2012",
+    "126": "Honda Odyssey Minivan 2007",
+    "127": "Honda Accord Coupe 2012",
+    "128": "Honda Accord Sedan 2012",
+    "129": "Hyundai Veloster Hatchback 2012",
+    "130": "Hyundai Santa Fe SUV 2012",
+    "131": "Hyundai Tucson SUV 2012",
+    "132": "Hyundai Veracruz SUV 2012",
+    "133": "Hyundai Sonata Hybrid Sedan 2012",
+    "134": "Hyundai Elantra Sedan 2007",
+    "135": "Hyundai Accent Sedan 2012",
+    "136": "Hyundai Genesis Sedan 2012",
+    "137": "Hyundai Sonata Sedan 2012",
+    "138": "Hyundai Elantra Touring Hatchback 2012",
+    "139": "Hyundai Azera Sedan 2012",
+    "140": "Infiniti G Coupe IPL 2012",
+    "141": "Infiniti QX56 SUV 2011",
+    "142": "Isuzu Ascender SUV 2008",
+    "143": "Jaguar XK XKR 2012",
+    "144": "Jeep Patriot SUV 2012",
+    "145": "Jeep Wrangler SUV 2012",
+    "146": "Jeep Liberty SUV 2012",
+    "147": "Jeep Grand Cherokee SUV 2012",
+    "148": "Jeep Compass SUV 2012",
+    "149": "Lamborghini Reventon Coupe 2008",
+    "150": "Lamborghini Aventador Coupe 2012",
+    "151": "Lamborghini Gallardo LP 570-4 Superleggera 2012",
+    "152": "Lamborghini Diablo Coupe 2001",
+    "153": "Land Rover Range Rover SUV 2012",
+    "154": "Land Rover LR2 SUV 2012",
+    "155": "Lincoln Town Car Sedan 2011",
+    "156": "MINI Cooper Roadster Convertible 2012",
+    "157": "Maybach Landaulet Convertible 2012",
+    "158": "Mazda Tribute SUV 2011",
+    "159": "McLaren MP4-12C Coupe 2012",
+    "160": "Mercedes-Benz 300-Class Convertible 1993",
+    "161": "Mercedes-Benz C-Class Sedan 2012",
+    "162": "Mercedes-Benz SL-Class Coupe 2009",
+    "163": "Mercedes-Benz E-Class Sedan 2012",
+    "164": "Mercedes-Benz S-Class Sedan 2012",
+    "165": "Mercedes-Benz Sprinter Van 2012",
+    "166": "Mitsubishi Lancer Sedan 2012",
+    "167": "Nissan Leaf Hatchback 2012",
+    "168": "Nissan NV Passenger Van 2012",
+    "169": "Nissan Juke Hatchback 2012",
+    "170": "Nissan 240SX Coupe 1998",
+    "171": "Plymouth Neon Coupe 1999",
+    "172": "Porsche Panamera Sedan 2012",
+    "173": "Ram C/V Cargo Van Minivan 2012",
+    "174": "Rolls-Royce Phantom Drophead Coupe Convertible 2012",
+    "175": "Rolls-Royce Ghost Sedan 2012",
+    "176": "Rolls-Royce Phantom Sedan 2012",
+    "177": "Scion xD Hatchback 2012",
+    "178": "Spyker C8 Convertible 2009",
+    "179": "Spyker C8 Coupe 2009",
+    "180": "Suzuki Aerio Sedan 2007",
+    "181": "Suzuki Kizashi Sedan 2012",
+    "182": "Suzuki SX4 Hatchback 2012",
+    "183": "Suzuki SX4 Sedan 2012",
+    "184": "Tesla Model S Sedan 2012",
+    "185": "Toyota Sequoia SUV 2012",
+    "186": "Toyota Camry Sedan 2012",
+    "187": "Toyota Corolla Sedan 2012",
+    "188": "Toyota 4Runner SUV 2012",
+    "189": "Volkswagen Golf Hatchback 2012",
+    "190": "Volkswagen Golf Hatchback 1991",
+    "191": "Volkswagen Beetle Hatchback 2012",
+    "192": "Volvo C30 Hatchback 2012",
+    "193": "Volvo 240 Sedan 1993",
+    "194": "Volvo XC90 SUV 2007",
+    "195": "smart fortwo Convertible 2012"
+  },
+  "label2id": {
+    "AM General Hummer SUV 2000": 0,
+    "Acura Integra Type R 2001": 5,
+    "Acura RL Sedan 2012": 1,
+    "Acura TL Sedan 2012": 2,
+    "Acura TL Type-S 2008": 3,
+    "Acura TSX Sedan 2012": 4,
+    "Acura ZDX Hatchback 2012": 6,
+    "Aston Martin V8 Vantage Convertible 2012": 7,
+    "Aston Martin V8 Vantage Coupe 2012": 8,
+    "Aston Martin Virage Convertible 2012": 9,
+    "Aston Martin Virage Coupe 2012": 10,
+    "Audi 100 Sedan 1994": 16,
+    "Audi 100 Wagon 1994": 17,
+    "Audi A5 Coupe 2012": 12,
+    "Audi R8 Coupe 2012": 14,
+    "Audi RS 4 Convertible 2008": 11,
+    "Audi S4 Sedan 2007": 23,
+    "Audi S4 Sedan 2012": 22,
+    "Audi S5 Convertible 2012": 20,
+    "Audi S5 Coupe 2012": 21,
+    "Audi S6 Sedan 2011": 19,
+    "Audi TT Hatchback 2011": 18,
+    "Audi TT RS Coupe 2012": 24,
+    "Audi TTS Coupe 2012": 13,
+    "Audi V8 Sedan 1994": 15,
+    "BMW 1 Series Convertible 2012": 26,
+    "BMW 1 Series Coupe 2012": 27,
+    "BMW 3 Series Sedan 2012": 28,
+    "BMW 3 Series Wagon 2012": 29,
+    "BMW 6 Series Convertible 2007": 30,
+    "BMW ActiveHybrid 5 Sedan 2012": 25,
+    "BMW M3 Coupe 2012": 33,
+    "BMW M5 Sedan 2010": 34,
+    "BMW M6 Convertible 2010": 35,
+    "BMW X3 SUV 2012": 36,
+    "BMW X5 SUV 2007": 31,
+    "BMW X6 SUV 2012": 32,
+    "BMW Z4 Convertible 2012": 37,
+    "Bentley Arnage Sedan 2009": 39,
+    "Bentley Continental Flying Spur Sedan 2007": 43,
+    "Bentley Continental GT Coupe 2007": 42,
+    "Bentley Continental GT Coupe 2012": 41,
+    "Bentley Continental Supersports Conv. Convertible 2012": 38,
+    "Bentley Mulsanne Sedan 2011": 40,
+    "Bugatti Veyron 16.4 Convertible 2009": 44,
+    "Bugatti Veyron 16.4 Coupe 2009": 45,
+    "Buick Enclave SUV 2012": 49,
+    "Buick Rainier SUV 2007": 47,
+    "Buick Regal GS 2012": 46,
+    "Buick Verano Sedan 2012": 48,
+    "Cadillac CTS-V Sedan 2012": 50,
+    "Cadillac Escalade EXT Crew Cab 2007": 52,
+    "Cadillac SRX SUV 2012": 51,
+    "Chevrolet Avalanche Crew Cab 2012": 64,
+    "Chevrolet Camaro Convertible 2012": 58,
+    "Chevrolet Cobalt SS 2010": 65,
+    "Chevrolet Corvette Convertible 2012": 54,
+    "Chevrolet Corvette Ron Fellows Edition Z06 2007": 56,
+    "Chevrolet Corvette ZR1 2012": 55,
+    "Chevrolet Express Cargo Van 2007": 63,
+    "Chevrolet Express Van 2007": 70,
+    "Chevrolet HHR SS 2010": 59,
+    "Chevrolet Impala Sedan 2007": 60,
+    "Chevrolet Malibu Hybrid Sedan 2010": 66,
+    "Chevrolet Malibu Sedan 2007": 72,
+    "Chevrolet Monte Carlo Coupe 2007": 71,
+    "Chevrolet Silverado 1500 Classic Extended Cab 2007": 69,
+    "Chevrolet Silverado 1500 Extended Cab 2012": 73,
+    "Chevrolet Silverado 1500 Hybrid Crew Cab 2012": 53,
+    "Chevrolet Silverado 1500 Regular Cab 2012": 74,
+    "Chevrolet Silverado 2500HD Regular Cab 2012": 68,
+    "Chevrolet Sonic Sedan 2012": 62,
+    "Chevrolet Tahoe Hybrid SUV 2012": 61,
+    "Chevrolet TrailBlazer SS 2009": 67,
+    "Chevrolet Traverse SUV 2012": 57,
+    "Chrysler 300 SRT-8 2010": 78,
+    "Chrysler Aspen SUV 2009": 75,
+    "Chrysler Crossfire Convertible 2008": 79,
+    "Chrysler PT Cruiser Convertible 2008": 80,
+    "Chrysler Sebring Convertible 2010": 76,
+    "Chrysler Town and Country Minivan 2012": 77,
+    "Daewoo Nubira Wagon 2002": 81,
+    "Dodge Caliber Wagon 2007": 83,
+    "Dodge Caliber Wagon 2012": 82,
+    "Dodge Caravan Minivan 1997": 84,
+    "Dodge Challenger SRT8 2011": 92,
+    "Dodge Charger SRT-8 2009": 96,
+    "Dodge Charger Sedan 2012": 95,
+    "Dodge Dakota Club Cab 2007": 90,
+    "Dodge Dakota Crew Cab 2010": 89,
+    "Dodge Durango SUV 2007": 94,
+    "Dodge Durango SUV 2012": 93,
+    "Dodge Journey SUV 2012": 88,
+    "Dodge Magnum Wagon 2008": 91,
+    "Dodge Ram Pickup 3500 Crew Cab 2010": 85,
+    "Dodge Ram Pickup 3500 Quad Cab 2009": 86,
+    "Dodge Sprinter Cargo Van 2009": 87,
+    "Eagle Talon Hatchback 1998": 97,
+    "FIAT 500 Abarth 2012": 98,
+    "FIAT 500 Convertible 2012": 99,
+    "Ferrari 458 Italia Convertible 2012": 102,
+    "Ferrari 458 Italia Coupe 2012": 103,
+    "Ferrari California Convertible 2012": 101,
+    "Ferrari FF Coupe 2012": 100,
+    "Fisker Karma Sedan 2012": 104,
+    "Ford E-Series Wagon Van 2012": 115,
+    "Ford Edge SUV 2012": 109,
+    "Ford Expedition EL SUV 2009": 108,
+    "Ford F-150 Regular Cab 2007": 113,
+    "Ford F-150 Regular Cab 2012": 112,
+    "Ford F-450 Super Duty Crew Cab 2012": 105,
+    "Ford Fiesta Sedan 2012": 116,
+    "Ford Focus Sedan 2007": 114,
+    "Ford Freestar Minivan 2007": 107,
+    "Ford GT Coupe 2006": 111,
+    "Ford Mustang Convertible 2007": 106,
+    "Ford Ranger SuperCab 2011": 110,
+    "GMC Acadia SUV 2012": 120,
+    "GMC Canyon Extended Cab 2012": 121,
+    "GMC Savana Van 2012": 118,
+    "GMC Terrain SUV 2012": 117,
+    "GMC Yukon Hybrid SUV 2012": 119,
+    "Geo Metro Convertible 1993": 122,
+    "HUMMER H2 SUT Crew Cab 2009": 124,
+    "HUMMER H3T Crew Cab 2010": 123,
+    "Honda Accord Coupe 2012": 127,
+    "Honda Accord Sedan 2012": 128,
+    "Honda Odyssey Minivan 2007": 126,
+    "Honda Odyssey Minivan 2012": 125,
+    "Hyundai Accent Sedan 2012": 135,
+    "Hyundai Azera Sedan 2012": 139,
+    "Hyundai Elantra Sedan 2007": 134,
+    "Hyundai Elantra Touring Hatchback 2012": 138,
+    "Hyundai Genesis Sedan 2012": 136,
+    "Hyundai Santa Fe SUV 2012": 130,
+    "Hyundai Sonata Hybrid Sedan 2012": 133,
+    "Hyundai Sonata Sedan 2012": 137,
+    "Hyundai Tucson SUV 2012": 131,
+    "Hyundai Veloster Hatchback 2012": 129,
+    "Hyundai Veracruz SUV 2012": 132,
+    "Infiniti G Coupe IPL 2012": 140,
+    "Infiniti QX56 SUV 2011": 141,
+    "Isuzu Ascender SUV 2008": 142,
+    "Jaguar XK XKR 2012": 143,
+    "Jeep Compass SUV 2012": 148,
+    "Jeep Grand Cherokee SUV 2012": 147,
+    "Jeep Liberty SUV 2012": 146,
+    "Jeep Patriot SUV 2012": 144,
+    "Jeep Wrangler SUV 2012": 145,
+    "Lamborghini Aventador Coupe 2012": 150,
+    "Lamborghini Diablo Coupe 2001": 152,
+    "Lamborghini Gallardo LP 570-4 Superleggera 2012": 151,
+    "Lamborghini Reventon Coupe 2008": 149,
+    "Land Rover LR2 SUV 2012": 154,
+    "Land Rover Range Rover SUV 2012": 153,
+    "Lincoln Town Car Sedan 2011": 155,
+    "MINI Cooper Roadster Convertible 2012": 156,
+    "Maybach Landaulet Convertible 2012": 157,
+    "Mazda Tribute SUV 2011": 158,
+    "McLaren MP4-12C Coupe 2012": 159,
+    "Mercedes-Benz 300-Class Convertible 1993": 160,
+    "Mercedes-Benz C-Class Sedan 2012": 161,
+    "Mercedes-Benz E-Class Sedan 2012": 163,
+    "Mercedes-Benz S-Class Sedan 2012": 164,
+    "Mercedes-Benz SL-Class Coupe 2009": 162,
+    "Mercedes-Benz Sprinter Van 2012": 165,
+    "Mitsubishi Lancer Sedan 2012": 166,
+    "Nissan 240SX Coupe 1998": 170,
+    "Nissan Juke Hatchback 2012": 169,
+    "Nissan Leaf Hatchback 2012": 167,
+    "Nissan NV Passenger Van 2012": 168,
+    "Plymouth Neon Coupe 1999": 171,
+    "Porsche Panamera Sedan 2012": 172,
+    "Ram C/V Cargo Van Minivan 2012": 173,
+    "Rolls-Royce Ghost Sedan 2012": 175,
+    "Rolls-Royce Phantom Drophead Coupe Convertible 2012": 174,
+    "Rolls-Royce Phantom Sedan 2012": 176,
+    "Scion xD Hatchback 2012": 177,
+    "Spyker C8 Convertible 2009": 178,
+    "Spyker C8 Coupe 2009": 179,
+    "Suzuki Aerio Sedan 2007": 180,
+    "Suzuki Kizashi Sedan 2012": 181,
+    "Suzuki SX4 Hatchback 2012": 182,
+    "Suzuki SX4 Sedan 2012": 183,
+    "Tesla Model S Sedan 2012": 184,
+    "Toyota 4Runner SUV 2012": 188,
+    "Toyota Camry Sedan 2012": 186,
+    "Toyota Corolla Sedan 2012": 187,
+    "Toyota Sequoia SUV 2012": 185,
+    "Volkswagen Beetle Hatchback 2012": 191,
+    "Volkswagen Golf Hatchback 1991": 190,
+    "Volkswagen Golf Hatchback 2012": 189,
+    "Volvo 240 Sedan 1993": 193,
+    "Volvo C30 Hatchback 2012": 192,
+    "Volvo XC90 SUV 2007": 194,
+    "smart fortwo Convertible 2012": 195
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet152-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/README.md b/resnet152-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..4f6c52ec036a241fab5a330ba4a09c21e7bad407
--- /dev/null
+++ b/resnet152-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stanford-cars.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: stanford-cars
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: train
+type: transformers
+val_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: test
+```
+
diff --git a/resnet152-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/config.json b/resnet152-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1e0f59991da08604f363224d408031555ecd60f4
--- /dev/null
+++ b/resnet152-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,435 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "AM General Hummer SUV 2000",
+    "1": "Acura RL Sedan 2012",
+    "2": "Acura TL Sedan 2012",
+    "3": "Acura TL Type-S 2008",
+    "4": "Acura TSX Sedan 2012",
+    "5": "Acura Integra Type R 2001",
+    "6": "Acura ZDX Hatchback 2012",
+    "7": "Aston Martin V8 Vantage Convertible 2012",
+    "8": "Aston Martin V8 Vantage Coupe 2012",
+    "9": "Aston Martin Virage Convertible 2012",
+    "10": "Aston Martin Virage Coupe 2012",
+    "11": "Audi RS 4 Convertible 2008",
+    "12": "Audi A5 Coupe 2012",
+    "13": "Audi TTS Coupe 2012",
+    "14": "Audi R8 Coupe 2012",
+    "15": "Audi V8 Sedan 1994",
+    "16": "Audi 100 Sedan 1994",
+    "17": "Audi 100 Wagon 1994",
+    "18": "Audi TT Hatchback 2011",
+    "19": "Audi S6 Sedan 2011",
+    "20": "Audi S5 Convertible 2012",
+    "21": "Audi S5 Coupe 2012",
+    "22": "Audi S4 Sedan 2012",
+    "23": "Audi S4 Sedan 2007",
+    "24": "Audi TT RS Coupe 2012",
+    "25": "BMW ActiveHybrid 5 Sedan 2012",
+    "26": "BMW 1 Series Convertible 2012",
+    "27": "BMW 1 Series Coupe 2012",
+    "28": "BMW 3 Series Sedan 2012",
+    "29": "BMW 3 Series Wagon 2012",
+    "30": "BMW 6 Series Convertible 2007",
+    "31": "BMW X5 SUV 2007",
+    "32": "BMW X6 SUV 2012",
+    "33": "BMW M3 Coupe 2012",
+    "34": "BMW M5 Sedan 2010",
+    "35": "BMW M6 Convertible 2010",
+    "36": "BMW X3 SUV 2012",
+    "37": "BMW Z4 Convertible 2012",
+    "38": "Bentley Continental Supersports Conv. Convertible 2012",
+    "39": "Bentley Arnage Sedan 2009",
+    "40": "Bentley Mulsanne Sedan 2011",
+    "41": "Bentley Continental GT Coupe 2012",
+    "42": "Bentley Continental GT Coupe 2007",
+    "43": "Bentley Continental Flying Spur Sedan 2007",
+    "44": "Bugatti Veyron 16.4 Convertible 2009",
+    "45": "Bugatti Veyron 16.4 Coupe 2009",
+    "46": "Buick Regal GS 2012",
+    "47": "Buick Rainier SUV 2007",
+    "48": "Buick Verano Sedan 2012",
+    "49": "Buick Enclave SUV 2012",
+    "50": "Cadillac CTS-V Sedan 2012",
+    "51": "Cadillac SRX SUV 2012",
+    "52": "Cadillac Escalade EXT Crew Cab 2007",
+    "53": "Chevrolet Silverado 1500 Hybrid Crew Cab 2012",
+    "54": "Chevrolet Corvette Convertible 2012",
+    "55": "Chevrolet Corvette ZR1 2012",
+    "56": "Chevrolet Corvette Ron Fellows Edition Z06 2007",
+    "57": "Chevrolet Traverse SUV 2012",
+    "58": "Chevrolet Camaro Convertible 2012",
+    "59": "Chevrolet HHR SS 2010",
+    "60": "Chevrolet Impala Sedan 2007",
+    "61": "Chevrolet Tahoe Hybrid SUV 2012",
+    "62": "Chevrolet Sonic Sedan 2012",
+    "63": "Chevrolet Express Cargo Van 2007",
+    "64": "Chevrolet Avalanche Crew Cab 2012",
+    "65": "Chevrolet Cobalt SS 2010",
+    "66": "Chevrolet Malibu Hybrid Sedan 2010",
+    "67": "Chevrolet TrailBlazer SS 2009",
+    "68": "Chevrolet Silverado 2500HD Regular Cab 2012",
+    "69": "Chevrolet Silverado 1500 Classic Extended Cab 2007",
+    "70": "Chevrolet Express Van 2007",
+    "71": "Chevrolet Monte Carlo Coupe 2007",
+    "72": "Chevrolet Malibu Sedan 2007",
+    "73": "Chevrolet Silverado 1500 Extended Cab 2012",
+    "74": "Chevrolet Silverado 1500 Regular Cab 2012",
+    "75": "Chrysler Aspen SUV 2009",
+    "76": "Chrysler Sebring Convertible 2010",
+    "77": "Chrysler Town and Country Minivan 2012",
+    "78": "Chrysler 300 SRT-8 2010",
+    "79": "Chrysler Crossfire Convertible 2008",
+    "80": "Chrysler PT Cruiser Convertible 2008",
+    "81": "Daewoo Nubira Wagon 2002",
+    "82": "Dodge Caliber Wagon 2012",
+    "83": "Dodge Caliber Wagon 2007",
+    "84": "Dodge Caravan Minivan 1997",
+    "85": "Dodge Ram Pickup 3500 Crew Cab 2010",
+    "86": "Dodge Ram Pickup 3500 Quad Cab 2009",
+    "87": "Dodge Sprinter Cargo Van 2009",
+    "88": "Dodge Journey SUV 2012",
+    "89": "Dodge Dakota Crew Cab 2010",
+    "90": "Dodge Dakota Club Cab 2007",
+    "91": "Dodge Magnum Wagon 2008",
+    "92": "Dodge Challenger SRT8 2011",
+    "93": "Dodge Durango SUV 2012",
+    "94": "Dodge Durango SUV 2007",
+    "95": "Dodge Charger Sedan 2012",
+    "96": "Dodge Charger SRT-8 2009",
+    "97": "Eagle Talon Hatchback 1998",
+    "98": "FIAT 500 Abarth 2012",
+    "99": "FIAT 500 Convertible 2012",
+    "100": "Ferrari FF Coupe 2012",
+    "101": "Ferrari California Convertible 2012",
+    "102": "Ferrari 458 Italia Convertible 2012",
+    "103": "Ferrari 458 Italia Coupe 2012",
+    "104": "Fisker Karma Sedan 2012",
+    "105": "Ford F-450 Super Duty Crew Cab 2012",
+    "106": "Ford Mustang Convertible 2007",
+    "107": "Ford Freestar Minivan 2007",
+    "108": "Ford Expedition EL SUV 2009",
+    "109": "Ford Edge SUV 2012",
+    "110": "Ford Ranger SuperCab 2011",
+    "111": "Ford GT Coupe 2006",
+    "112": "Ford F-150 Regular Cab 2012",
+    "113": "Ford F-150 Regular Cab 2007",
+    "114": "Ford Focus Sedan 2007",
+    "115": "Ford E-Series Wagon Van 2012",
+    "116": "Ford Fiesta Sedan 2012",
+    "117": "GMC Terrain SUV 2012",
+    "118": "GMC Savana Van 2012",
+    "119": "GMC Yukon Hybrid SUV 2012",
+    "120": "GMC Acadia SUV 2012",
+    "121": "GMC Canyon Extended Cab 2012",
+    "122": "Geo Metro Convertible 1993",
+    "123": "HUMMER H3T Crew Cab 2010",
+    "124": "HUMMER H2 SUT Crew Cab 2009",
+    "125": "Honda Odyssey Minivan 2012",
+    "126": "Honda Odyssey Minivan 2007",
+    "127": "Honda Accord Coupe 2012",
+    "128": "Honda Accord Sedan 2012",
+    "129": "Hyundai Veloster Hatchback 2012",
+    "130": "Hyundai Santa Fe SUV 2012",
+    "131": "Hyundai Tucson SUV 2012",
+    "132": "Hyundai Veracruz SUV 2012",
+    "133": "Hyundai Sonata Hybrid Sedan 2012",
+    "134": "Hyundai Elantra Sedan 2007",
+    "135": "Hyundai Accent Sedan 2012",
+    "136": "Hyundai Genesis Sedan 2012",
+    "137": "Hyundai Sonata Sedan 2012",
+    "138": "Hyundai Elantra Touring Hatchback 2012",
+    "139": "Hyundai Azera Sedan 2012",
+    "140": "Infiniti G Coupe IPL 2012",
+    "141": "Infiniti QX56 SUV 2011",
+    "142": "Isuzu Ascender SUV 2008",
+    "143": "Jaguar XK XKR 2012",
+    "144": "Jeep Patriot SUV 2012",
+    "145": "Jeep Wrangler SUV 2012",
+    "146": "Jeep Liberty SUV 2012",
+    "147": "Jeep Grand Cherokee SUV 2012",
+    "148": "Jeep Compass SUV 2012",
+    "149": "Lamborghini Reventon Coupe 2008",
+    "150": "Lamborghini Aventador Coupe 2012",
+    "151": "Lamborghini Gallardo LP 570-4 Superleggera 2012",
+    "152": "Lamborghini Diablo Coupe 2001",
+    "153": "Land Rover Range Rover SUV 2012",
+    "154": "Land Rover LR2 SUV 2012",
+    "155": "Lincoln Town Car Sedan 2011",
+    "156": "MINI Cooper Roadster Convertible 2012",
+    "157": "Maybach Landaulet Convertible 2012",
+    "158": "Mazda Tribute SUV 2011",
+    "159": "McLaren MP4-12C Coupe 2012",
+    "160": "Mercedes-Benz 300-Class Convertible 1993",
+    "161": "Mercedes-Benz C-Class Sedan 2012",
+    "162": "Mercedes-Benz SL-Class Coupe 2009",
+    "163": "Mercedes-Benz E-Class Sedan 2012",
+    "164": "Mercedes-Benz S-Class Sedan 2012",
+    "165": "Mercedes-Benz Sprinter Van 2012",
+    "166": "Mitsubishi Lancer Sedan 2012",
+    "167": "Nissan Leaf Hatchback 2012",
+    "168": "Nissan NV Passenger Van 2012",
+    "169": "Nissan Juke Hatchback 2012",
+    "170": "Nissan 240SX Coupe 1998",
+    "171": "Plymouth Neon Coupe 1999",
+    "172": "Porsche Panamera Sedan 2012",
+    "173": "Ram C/V Cargo Van Minivan 2012",
+    "174": "Rolls-Royce Phantom Drophead Coupe Convertible 2012",
+    "175": "Rolls-Royce Ghost Sedan 2012",
+    "176": "Rolls-Royce Phantom Sedan 2012",
+    "177": "Scion xD Hatchback 2012",
+    "178": "Spyker C8 Convertible 2009",
+    "179": "Spyker C8 Coupe 2009",
+    "180": "Suzuki Aerio Sedan 2007",
+    "181": "Suzuki Kizashi Sedan 2012",
+    "182": "Suzuki SX4 Hatchback 2012",
+    "183": "Suzuki SX4 Sedan 2012",
+    "184": "Tesla Model S Sedan 2012",
+    "185": "Toyota Sequoia SUV 2012",
+    "186": "Toyota Camry Sedan 2012",
+    "187": "Toyota Corolla Sedan 2012",
+    "188": "Toyota 4Runner SUV 2012",
+    "189": "Volkswagen Golf Hatchback 2012",
+    "190": "Volkswagen Golf Hatchback 1991",
+    "191": "Volkswagen Beetle Hatchback 2012",
+    "192": "Volvo C30 Hatchback 2012",
+    "193": "Volvo 240 Sedan 1993",
+    "194": "Volvo XC90 SUV 2007",
+    "195": "smart fortwo Convertible 2012"
+  },
+  "label2id": {
+    "AM General Hummer SUV 2000": 0,
+    "Acura Integra Type R 2001": 5,
+    "Acura RL Sedan 2012": 1,
+    "Acura TL Sedan 2012": 2,
+    "Acura TL Type-S 2008": 3,
+    "Acura TSX Sedan 2012": 4,
+    "Acura ZDX Hatchback 2012": 6,
+    "Aston Martin V8 Vantage Convertible 2012": 7,
+    "Aston Martin V8 Vantage Coupe 2012": 8,
+    "Aston Martin Virage Convertible 2012": 9,
+    "Aston Martin Virage Coupe 2012": 10,
+    "Audi 100 Sedan 1994": 16,
+    "Audi 100 Wagon 1994": 17,
+    "Audi A5 Coupe 2012": 12,
+    "Audi R8 Coupe 2012": 14,
+    "Audi RS 4 Convertible 2008": 11,
+    "Audi S4 Sedan 2007": 23,
+    "Audi S4 Sedan 2012": 22,
+    "Audi S5 Convertible 2012": 20,
+    "Audi S5 Coupe 2012": 21,
+    "Audi S6 Sedan 2011": 19,
+    "Audi TT Hatchback 2011": 18,
+    "Audi TT RS Coupe 2012": 24,
+    "Audi TTS Coupe 2012": 13,
+    "Audi V8 Sedan 1994": 15,
+    "BMW 1 Series Convertible 2012": 26,
+    "BMW 1 Series Coupe 2012": 27,
+    "BMW 3 Series Sedan 2012": 28,
+    "BMW 3 Series Wagon 2012": 29,
+    "BMW 6 Series Convertible 2007": 30,
+    "BMW ActiveHybrid 5 Sedan 2012": 25,
+    "BMW M3 Coupe 2012": 33,
+    "BMW M5 Sedan 2010": 34,
+    "BMW M6 Convertible 2010": 35,
+    "BMW X3 SUV 2012": 36,
+    "BMW X5 SUV 2007": 31,
+    "BMW X6 SUV 2012": 32,
+    "BMW Z4 Convertible 2012": 37,
+    "Bentley Arnage Sedan 2009": 39,
+    "Bentley Continental Flying Spur Sedan 2007": 43,
+    "Bentley Continental GT Coupe 2007": 42,
+    "Bentley Continental GT Coupe 2012": 41,
+    "Bentley Continental Supersports Conv. Convertible 2012": 38,
+    "Bentley Mulsanne Sedan 2011": 40,
+    "Bugatti Veyron 16.4 Convertible 2009": 44,
+    "Bugatti Veyron 16.4 Coupe 2009": 45,
+    "Buick Enclave SUV 2012": 49,
+    "Buick Rainier SUV 2007": 47,
+    "Buick Regal GS 2012": 46,
+    "Buick Verano Sedan 2012": 48,
+    "Cadillac CTS-V Sedan 2012": 50,
+    "Cadillac Escalade EXT Crew Cab 2007": 52,
+    "Cadillac SRX SUV 2012": 51,
+    "Chevrolet Avalanche Crew Cab 2012": 64,
+    "Chevrolet Camaro Convertible 2012": 58,
+    "Chevrolet Cobalt SS 2010": 65,
+    "Chevrolet Corvette Convertible 2012": 54,
+    "Chevrolet Corvette Ron Fellows Edition Z06 2007": 56,
+    "Chevrolet Corvette ZR1 2012": 55,
+    "Chevrolet Express Cargo Van 2007": 63,
+    "Chevrolet Express Van 2007": 70,
+    "Chevrolet HHR SS 2010": 59,
+    "Chevrolet Impala Sedan 2007": 60,
+    "Chevrolet Malibu Hybrid Sedan 2010": 66,
+    "Chevrolet Malibu Sedan 2007": 72,
+    "Chevrolet Monte Carlo Coupe 2007": 71,
+    "Chevrolet Silverado 1500 Classic Extended Cab 2007": 69,
+    "Chevrolet Silverado 1500 Extended Cab 2012": 73,
+    "Chevrolet Silverado 1500 Hybrid Crew Cab 2012": 53,
+    "Chevrolet Silverado 1500 Regular Cab 2012": 74,
+    "Chevrolet Silverado 2500HD Regular Cab 2012": 68,
+    "Chevrolet Sonic Sedan 2012": 62,
+    "Chevrolet Tahoe Hybrid SUV 2012": 61,
+    "Chevrolet TrailBlazer SS 2009": 67,
+    "Chevrolet Traverse SUV 2012": 57,
+    "Chrysler 300 SRT-8 2010": 78,
+    "Chrysler Aspen SUV 2009": 75,
+    "Chrysler Crossfire Convertible 2008": 79,
+    "Chrysler PT Cruiser Convertible 2008": 80,
+    "Chrysler Sebring Convertible 2010": 76,
+    "Chrysler Town and Country Minivan 2012": 77,
+    "Daewoo Nubira Wagon 2002": 81,
+    "Dodge Caliber Wagon 2007": 83,
+    "Dodge Caliber Wagon 2012": 82,
+    "Dodge Caravan Minivan 1997": 84,
+    "Dodge Challenger SRT8 2011": 92,
+    "Dodge Charger SRT-8 2009": 96,
+    "Dodge Charger Sedan 2012": 95,
+    "Dodge Dakota Club Cab 2007": 90,
+    "Dodge Dakota Crew Cab 2010": 89,
+    "Dodge Durango SUV 2007": 94,
+    "Dodge Durango SUV 2012": 93,
+    "Dodge Journey SUV 2012": 88,
+    "Dodge Magnum Wagon 2008": 91,
+    "Dodge Ram Pickup 3500 Crew Cab 2010": 85,
+    "Dodge Ram Pickup 3500 Quad Cab 2009": 86,
+    "Dodge Sprinter Cargo Van 2009": 87,
+    "Eagle Talon Hatchback 1998": 97,
+    "FIAT 500 Abarth 2012": 98,
+    "FIAT 500 Convertible 2012": 99,
+    "Ferrari 458 Italia Convertible 2012": 102,
+    "Ferrari 458 Italia Coupe 2012": 103,
+    "Ferrari California Convertible 2012": 101,
+    "Ferrari FF Coupe 2012": 100,
+    "Fisker Karma Sedan 2012": 104,
+    "Ford E-Series Wagon Van 2012": 115,
+    "Ford Edge SUV 2012": 109,
+    "Ford Expedition EL SUV 2009": 108,
+    "Ford F-150 Regular Cab 2007": 113,
+    "Ford F-150 Regular Cab 2012": 112,
+    "Ford F-450 Super Duty Crew Cab 2012": 105,
+    "Ford Fiesta Sedan 2012": 116,
+    "Ford Focus Sedan 2007": 114,
+    "Ford Freestar Minivan 2007": 107,
+    "Ford GT Coupe 2006": 111,
+    "Ford Mustang Convertible 2007": 106,
+    "Ford Ranger SuperCab 2011": 110,
+    "GMC Acadia SUV 2012": 120,
+    "GMC Canyon Extended Cab 2012": 121,
+    "GMC Savana Van 2012": 118,
+    "GMC Terrain SUV 2012": 117,
+    "GMC Yukon Hybrid SUV 2012": 119,
+    "Geo Metro Convertible 1993": 122,
+    "HUMMER H2 SUT Crew Cab 2009": 124,
+    "HUMMER H3T Crew Cab 2010": 123,
+    "Honda Accord Coupe 2012": 127,
+    "Honda Accord Sedan 2012": 128,
+    "Honda Odyssey Minivan 2007": 126,
+    "Honda Odyssey Minivan 2012": 125,
+    "Hyundai Accent Sedan 2012": 135,
+    "Hyundai Azera Sedan 2012": 139,
+    "Hyundai Elantra Sedan 2007": 134,
+    "Hyundai Elantra Touring Hatchback 2012": 138,
+    "Hyundai Genesis Sedan 2012": 136,
+    "Hyundai Santa Fe SUV 2012": 130,
+    "Hyundai Sonata Hybrid Sedan 2012": 133,
+    "Hyundai Sonata Sedan 2012": 137,
+    "Hyundai Tucson SUV 2012": 131,
+    "Hyundai Veloster Hatchback 2012": 129,
+    "Hyundai Veracruz SUV 2012": 132,
+    "Infiniti G Coupe IPL 2012": 140,
+    "Infiniti QX56 SUV 2011": 141,
+    "Isuzu Ascender SUV 2008": 142,
+    "Jaguar XK XKR 2012": 143,
+    "Jeep Compass SUV 2012": 148,
+    "Jeep Grand Cherokee SUV 2012": 147,
+    "Jeep Liberty SUV 2012": 146,
+    "Jeep Patriot SUV 2012": 144,
+    "Jeep Wrangler SUV 2012": 145,
+    "Lamborghini Aventador Coupe 2012": 150,
+    "Lamborghini Diablo Coupe 2001": 152,
+    "Lamborghini Gallardo LP 570-4 Superleggera 2012": 151,
+    "Lamborghini Reventon Coupe 2008": 149,
+    "Land Rover LR2 SUV 2012": 154,
+    "Land Rover Range Rover SUV 2012": 153,
+    "Lincoln Town Car Sedan 2011": 155,
+    "MINI Cooper Roadster Convertible 2012": 156,
+    "Maybach Landaulet Convertible 2012": 157,
+    "Mazda Tribute SUV 2011": 158,
+    "McLaren MP4-12C Coupe 2012": 159,
+    "Mercedes-Benz 300-Class Convertible 1993": 160,
+    "Mercedes-Benz C-Class Sedan 2012": 161,
+    "Mercedes-Benz E-Class Sedan 2012": 163,
+    "Mercedes-Benz S-Class Sedan 2012": 164,
+    "Mercedes-Benz SL-Class Coupe 2009": 162,
+    "Mercedes-Benz Sprinter Van 2012": 165,
+    "Mitsubishi Lancer Sedan 2012": 166,
+    "Nissan 240SX Coupe 1998": 170,
+    "Nissan Juke Hatchback 2012": 169,
+    "Nissan Leaf Hatchback 2012": 167,
+    "Nissan NV Passenger Van 2012": 168,
+    "Plymouth Neon Coupe 1999": 171,
+    "Porsche Panamera Sedan 2012": 172,
+    "Ram C/V Cargo Van Minivan 2012": 173,
+    "Rolls-Royce Ghost Sedan 2012": 175,
+    "Rolls-Royce Phantom Drophead Coupe Convertible 2012": 174,
+    "Rolls-Royce Phantom Sedan 2012": 176,
+    "Scion xD Hatchback 2012": 177,
+    "Spyker C8 Convertible 2009": 178,
+    "Spyker C8 Coupe 2009": 179,
+    "Suzuki Aerio Sedan 2007": 180,
+    "Suzuki Kizashi Sedan 2012": 181,
+    "Suzuki SX4 Hatchback 2012": 182,
+    "Suzuki SX4 Sedan 2012": 183,
+    "Tesla Model S Sedan 2012": 184,
+    "Toyota 4Runner SUV 2012": 188,
+    "Toyota Camry Sedan 2012": 186,
+    "Toyota Corolla Sedan 2012": 187,
+    "Toyota Sequoia SUV 2012": 185,
+    "Volkswagen Beetle Hatchback 2012": 191,
+    "Volkswagen Golf Hatchback 1991": 190,
+    "Volkswagen Golf Hatchback 2012": 189,
+    "Volvo 240 Sedan 1993": 193,
+    "Volvo C30 Hatchback 2012": 192,
+    "Volvo XC90 SUV 2007": 194,
+    "smart fortwo Convertible 2012": 195
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet152-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-stanford-cars-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/README.md b/resnet152-stanford-cars-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..eb624463359f1dbca1baefcf1dda0a8d33f41113
--- /dev/null
+++ b/resnet152-stanford-cars-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stanford-cars.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: stanford-cars
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: train
+type: transformers
+val_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: test
+```
+
diff --git a/resnet152-stanford-cars-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/config.json b/resnet152-stanford-cars-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1e0f59991da08604f363224d408031555ecd60f4
--- /dev/null
+++ b/resnet152-stanford-cars-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,435 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "AM General Hummer SUV 2000",
+    "1": "Acura RL Sedan 2012",
+    "2": "Acura TL Sedan 2012",
+    "3": "Acura TL Type-S 2008",
+    "4": "Acura TSX Sedan 2012",
+    "5": "Acura Integra Type R 2001",
+    "6": "Acura ZDX Hatchback 2012",
+    "7": "Aston Martin V8 Vantage Convertible 2012",
+    "8": "Aston Martin V8 Vantage Coupe 2012",
+    "9": "Aston Martin Virage Convertible 2012",
+    "10": "Aston Martin Virage Coupe 2012",
+    "11": "Audi RS 4 Convertible 2008",
+    "12": "Audi A5 Coupe 2012",
+    "13": "Audi TTS Coupe 2012",
+    "14": "Audi R8 Coupe 2012",
+    "15": "Audi V8 Sedan 1994",
+    "16": "Audi 100 Sedan 1994",
+    "17": "Audi 100 Wagon 1994",
+    "18": "Audi TT Hatchback 2011",
+    "19": "Audi S6 Sedan 2011",
+    "20": "Audi S5 Convertible 2012",
+    "21": "Audi S5 Coupe 2012",
+    "22": "Audi S4 Sedan 2012",
+    "23": "Audi S4 Sedan 2007",
+    "24": "Audi TT RS Coupe 2012",
+    "25": "BMW ActiveHybrid 5 Sedan 2012",
+    "26": "BMW 1 Series Convertible 2012",
+    "27": "BMW 1 Series Coupe 2012",
+    "28": "BMW 3 Series Sedan 2012",
+    "29": "BMW 3 Series Wagon 2012",
+    "30": "BMW 6 Series Convertible 2007",
+    "31": "BMW X5 SUV 2007",
+    "32": "BMW X6 SUV 2012",
+    "33": "BMW M3 Coupe 2012",
+    "34": "BMW M5 Sedan 2010",
+    "35": "BMW M6 Convertible 2010",
+    "36": "BMW X3 SUV 2012",
+    "37": "BMW Z4 Convertible 2012",
+    "38": "Bentley Continental Supersports Conv. Convertible 2012",
+    "39": "Bentley Arnage Sedan 2009",
+    "40": "Bentley Mulsanne Sedan 2011",
+    "41": "Bentley Continental GT Coupe 2012",
+    "42": "Bentley Continental GT Coupe 2007",
+    "43": "Bentley Continental Flying Spur Sedan 2007",
+    "44": "Bugatti Veyron 16.4 Convertible 2009",
+    "45": "Bugatti Veyron 16.4 Coupe 2009",
+    "46": "Buick Regal GS 2012",
+    "47": "Buick Rainier SUV 2007",
+    "48": "Buick Verano Sedan 2012",
+    "49": "Buick Enclave SUV 2012",
+    "50": "Cadillac CTS-V Sedan 2012",
+    "51": "Cadillac SRX SUV 2012",
+    "52": "Cadillac Escalade EXT Crew Cab 2007",
+    "53": "Chevrolet Silverado 1500 Hybrid Crew Cab 2012",
+    "54": "Chevrolet Corvette Convertible 2012",
+    "55": "Chevrolet Corvette ZR1 2012",
+    "56": "Chevrolet Corvette Ron Fellows Edition Z06 2007",
+    "57": "Chevrolet Traverse SUV 2012",
+    "58": "Chevrolet Camaro Convertible 2012",
+    "59": "Chevrolet HHR SS 2010",
+    "60": "Chevrolet Impala Sedan 2007",
+    "61": "Chevrolet Tahoe Hybrid SUV 2012",
+    "62": "Chevrolet Sonic Sedan 2012",
+    "63": "Chevrolet Express Cargo Van 2007",
+    "64": "Chevrolet Avalanche Crew Cab 2012",
+    "65": "Chevrolet Cobalt SS 2010",
+    "66": "Chevrolet Malibu Hybrid Sedan 2010",
+    "67": "Chevrolet TrailBlazer SS 2009",
+    "68": "Chevrolet Silverado 2500HD Regular Cab 2012",
+    "69": "Chevrolet Silverado 1500 Classic Extended Cab 2007",
+    "70": "Chevrolet Express Van 2007",
+    "71": "Chevrolet Monte Carlo Coupe 2007",
+    "72": "Chevrolet Malibu Sedan 2007",
+    "73": "Chevrolet Silverado 1500 Extended Cab 2012",
+    "74": "Chevrolet Silverado 1500 Regular Cab 2012",
+    "75": "Chrysler Aspen SUV 2009",
+    "76": "Chrysler Sebring Convertible 2010",
+    "77": "Chrysler Town and Country Minivan 2012",
+    "78": "Chrysler 300 SRT-8 2010",
+    "79": "Chrysler Crossfire Convertible 2008",
+    "80": "Chrysler PT Cruiser Convertible 2008",
+    "81": "Daewoo Nubira Wagon 2002",
+    "82": "Dodge Caliber Wagon 2012",
+    "83": "Dodge Caliber Wagon 2007",
+    "84": "Dodge Caravan Minivan 1997",
+    "85": "Dodge Ram Pickup 3500 Crew Cab 2010",
+    "86": "Dodge Ram Pickup 3500 Quad Cab 2009",
+    "87": "Dodge Sprinter Cargo Van 2009",
+    "88": "Dodge Journey SUV 2012",
+    "89": "Dodge Dakota Crew Cab 2010",
+    "90": "Dodge Dakota Club Cab 2007",
+    "91": "Dodge Magnum Wagon 2008",
+    "92": "Dodge Challenger SRT8 2011",
+    "93": "Dodge Durango SUV 2012",
+    "94": "Dodge Durango SUV 2007",
+    "95": "Dodge Charger Sedan 2012",
+    "96": "Dodge Charger SRT-8 2009",
+    "97": "Eagle Talon Hatchback 1998",
+    "98": "FIAT 500 Abarth 2012",
+    "99": "FIAT 500 Convertible 2012",
+    "100": "Ferrari FF Coupe 2012",
+    "101": "Ferrari California Convertible 2012",
+    "102": "Ferrari 458 Italia Convertible 2012",
+    "103": "Ferrari 458 Italia Coupe 2012",
+    "104": "Fisker Karma Sedan 2012",
+    "105": "Ford F-450 Super Duty Crew Cab 2012",
+    "106": "Ford Mustang Convertible 2007",
+    "107": "Ford Freestar Minivan 2007",
+    "108": "Ford Expedition EL SUV 2009",
+    "109": "Ford Edge SUV 2012",
+    "110": "Ford Ranger SuperCab 2011",
+    "111": "Ford GT Coupe 2006",
+    "112": "Ford F-150 Regular Cab 2012",
+    "113": "Ford F-150 Regular Cab 2007",
+    "114": "Ford Focus Sedan 2007",
+    "115": "Ford E-Series Wagon Van 2012",
+    "116": "Ford Fiesta Sedan 2012",
+    "117": "GMC Terrain SUV 2012",
+    "118": "GMC Savana Van 2012",
+    "119": "GMC Yukon Hybrid SUV 2012",
+    "120": "GMC Acadia SUV 2012",
+    "121": "GMC Canyon Extended Cab 2012",
+    "122": "Geo Metro Convertible 1993",
+    "123": "HUMMER H3T Crew Cab 2010",
+    "124": "HUMMER H2 SUT Crew Cab 2009",
+    "125": "Honda Odyssey Minivan 2012",
+    "126": "Honda Odyssey Minivan 2007",
+    "127": "Honda Accord Coupe 2012",
+    "128": "Honda Accord Sedan 2012",
+    "129": "Hyundai Veloster Hatchback 2012",
+    "130": "Hyundai Santa Fe SUV 2012",
+    "131": "Hyundai Tucson SUV 2012",
+    "132": "Hyundai Veracruz SUV 2012",
+    "133": "Hyundai Sonata Hybrid Sedan 2012",
+    "134": "Hyundai Elantra Sedan 2007",
+    "135": "Hyundai Accent Sedan 2012",
+    "136": "Hyundai Genesis Sedan 2012",
+    "137": "Hyundai Sonata Sedan 2012",
+    "138": "Hyundai Elantra Touring Hatchback 2012",
+    "139": "Hyundai Azera Sedan 2012",
+    "140": "Infiniti G Coupe IPL 2012",
+    "141": "Infiniti QX56 SUV 2011",
+    "142": "Isuzu Ascender SUV 2008",
+    "143": "Jaguar XK XKR 2012",
+    "144": "Jeep Patriot SUV 2012",
+    "145": "Jeep Wrangler SUV 2012",
+    "146": "Jeep Liberty SUV 2012",
+    "147": "Jeep Grand Cherokee SUV 2012",
+    "148": "Jeep Compass SUV 2012",
+    "149": "Lamborghini Reventon Coupe 2008",
+    "150": "Lamborghini Aventador Coupe 2012",
+    "151": "Lamborghini Gallardo LP 570-4 Superleggera 2012",
+    "152": "Lamborghini Diablo Coupe 2001",
+    "153": "Land Rover Range Rover SUV 2012",
+    "154": "Land Rover LR2 SUV 2012",
+    "155": "Lincoln Town Car Sedan 2011",
+    "156": "MINI Cooper Roadster Convertible 2012",
+    "157": "Maybach Landaulet Convertible 2012",
+    "158": "Mazda Tribute SUV 2011",
+    "159": "McLaren MP4-12C Coupe 2012",
+    "160": "Mercedes-Benz 300-Class Convertible 1993",
+    "161": "Mercedes-Benz C-Class Sedan 2012",
+    "162": "Mercedes-Benz SL-Class Coupe 2009",
+    "163": "Mercedes-Benz E-Class Sedan 2012",
+    "164": "Mercedes-Benz S-Class Sedan 2012",
+    "165": "Mercedes-Benz Sprinter Van 2012",
+    "166": "Mitsubishi Lancer Sedan 2012",
+    "167": "Nissan Leaf Hatchback 2012",
+    "168": "Nissan NV Passenger Van 2012",
+    "169": "Nissan Juke Hatchback 2012",
+    "170": "Nissan 240SX Coupe 1998",
+    "171": "Plymouth Neon Coupe 1999",
+    "172": "Porsche Panamera Sedan 2012",
+    "173": "Ram C/V Cargo Van Minivan 2012",
+    "174": "Rolls-Royce Phantom Drophead Coupe Convertible 2012",
+    "175": "Rolls-Royce Ghost Sedan 2012",
+    "176": "Rolls-Royce Phantom Sedan 2012",
+    "177": "Scion xD Hatchback 2012",
+    "178": "Spyker C8 Convertible 2009",
+    "179": "Spyker C8 Coupe 2009",
+    "180": "Suzuki Aerio Sedan 2007",
+    "181": "Suzuki Kizashi Sedan 2012",
+    "182": "Suzuki SX4 Hatchback 2012",
+    "183": "Suzuki SX4 Sedan 2012",
+    "184": "Tesla Model S Sedan 2012",
+    "185": "Toyota Sequoia SUV 2012",
+    "186": "Toyota Camry Sedan 2012",
+    "187": "Toyota Corolla Sedan 2012",
+    "188": "Toyota 4Runner SUV 2012",
+    "189": "Volkswagen Golf Hatchback 2012",
+    "190": "Volkswagen Golf Hatchback 1991",
+    "191": "Volkswagen Beetle Hatchback 2012",
+    "192": "Volvo C30 Hatchback 2012",
+    "193": "Volvo 240 Sedan 1993",
+    "194": "Volvo XC90 SUV 2007",
+    "195": "smart fortwo Convertible 2012"
+  },
+  "label2id": {
+    "AM General Hummer SUV 2000": 0,
+    "Acura Integra Type R 2001": 5,
+    "Acura RL Sedan 2012": 1,
+    "Acura TL Sedan 2012": 2,
+    "Acura TL Type-S 2008": 3,
+    "Acura TSX Sedan 2012": 4,
+    "Acura ZDX Hatchback 2012": 6,
+    "Aston Martin V8 Vantage Convertible 2012": 7,
+    "Aston Martin V8 Vantage Coupe 2012": 8,
+    "Aston Martin Virage Convertible 2012": 9,
+    "Aston Martin Virage Coupe 2012": 10,
+    "Audi 100 Sedan 1994": 16,
+    "Audi 100 Wagon 1994": 17,
+    "Audi A5 Coupe 2012": 12,
+    "Audi R8 Coupe 2012": 14,
+    "Audi RS 4 Convertible 2008": 11,
+    "Audi S4 Sedan 2007": 23,
+    "Audi S4 Sedan 2012": 22,
+    "Audi S5 Convertible 2012": 20,
+    "Audi S5 Coupe 2012": 21,
+    "Audi S6 Sedan 2011": 19,
+    "Audi TT Hatchback 2011": 18,
+    "Audi TT RS Coupe 2012": 24,
+    "Audi TTS Coupe 2012": 13,
+    "Audi V8 Sedan 1994": 15,
+    "BMW 1 Series Convertible 2012": 26,
+    "BMW 1 Series Coupe 2012": 27,
+    "BMW 3 Series Sedan 2012": 28,
+    "BMW 3 Series Wagon 2012": 29,
+    "BMW 6 Series Convertible 2007": 30,
+    "BMW ActiveHybrid 5 Sedan 2012": 25,
+    "BMW M3 Coupe 2012": 33,
+    "BMW M5 Sedan 2010": 34,
+    "BMW M6 Convertible 2010": 35,
+    "BMW X3 SUV 2012": 36,
+    "BMW X5 SUV 2007": 31,
+    "BMW X6 SUV 2012": 32,
+    "BMW Z4 Convertible 2012": 37,
+    "Bentley Arnage Sedan 2009": 39,
+    "Bentley Continental Flying Spur Sedan 2007": 43,
+    "Bentley Continental GT Coupe 2007": 42,
+    "Bentley Continental GT Coupe 2012": 41,
+    "Bentley Continental Supersports Conv. Convertible 2012": 38,
+    "Bentley Mulsanne Sedan 2011": 40,
+    "Bugatti Veyron 16.4 Convertible 2009": 44,
+    "Bugatti Veyron 16.4 Coupe 2009": 45,
+    "Buick Enclave SUV 2012": 49,
+    "Buick Rainier SUV 2007": 47,
+    "Buick Regal GS 2012": 46,
+    "Buick Verano Sedan 2012": 48,
+    "Cadillac CTS-V Sedan 2012": 50,
+    "Cadillac Escalade EXT Crew Cab 2007": 52,
+    "Cadillac SRX SUV 2012": 51,
+    "Chevrolet Avalanche Crew Cab 2012": 64,
+    "Chevrolet Camaro Convertible 2012": 58,
+    "Chevrolet Cobalt SS 2010": 65,
+    "Chevrolet Corvette Convertible 2012": 54,
+    "Chevrolet Corvette Ron Fellows Edition Z06 2007": 56,
+    "Chevrolet Corvette ZR1 2012": 55,
+    "Chevrolet Express Cargo Van 2007": 63,
+    "Chevrolet Express Van 2007": 70,
+    "Chevrolet HHR SS 2010": 59,
+    "Chevrolet Impala Sedan 2007": 60,
+    "Chevrolet Malibu Hybrid Sedan 2010": 66,
+    "Chevrolet Malibu Sedan 2007": 72,
+    "Chevrolet Monte Carlo Coupe 2007": 71,
+    "Chevrolet Silverado 1500 Classic Extended Cab 2007": 69,
+    "Chevrolet Silverado 1500 Extended Cab 2012": 73,
+    "Chevrolet Silverado 1500 Hybrid Crew Cab 2012": 53,
+    "Chevrolet Silverado 1500 Regular Cab 2012": 74,
+    "Chevrolet Silverado 2500HD Regular Cab 2012": 68,
+    "Chevrolet Sonic Sedan 2012": 62,
+    "Chevrolet Tahoe Hybrid SUV 2012": 61,
+    "Chevrolet TrailBlazer SS 2009": 67,
+    "Chevrolet Traverse SUV 2012": 57,
+    "Chrysler 300 SRT-8 2010": 78,
+    "Chrysler Aspen SUV 2009": 75,
+    "Chrysler Crossfire Convertible 2008": 79,
+    "Chrysler PT Cruiser Convertible 2008": 80,
+    "Chrysler Sebring Convertible 2010": 76,
+    "Chrysler Town and Country Minivan 2012": 77,
+    "Daewoo Nubira Wagon 2002": 81,
+    "Dodge Caliber Wagon 2007": 83,
+    "Dodge Caliber Wagon 2012": 82,
+    "Dodge Caravan Minivan 1997": 84,
+    "Dodge Challenger SRT8 2011": 92,
+    "Dodge Charger SRT-8 2009": 96,
+    "Dodge Charger Sedan 2012": 95,
+    "Dodge Dakota Club Cab 2007": 90,
+    "Dodge Dakota Crew Cab 2010": 89,
+    "Dodge Durango SUV 2007": 94,
+    "Dodge Durango SUV 2012": 93,
+    "Dodge Journey SUV 2012": 88,
+    "Dodge Magnum Wagon 2008": 91,
+    "Dodge Ram Pickup 3500 Crew Cab 2010": 85,
+    "Dodge Ram Pickup 3500 Quad Cab 2009": 86,
+    "Dodge Sprinter Cargo Van 2009": 87,
+    "Eagle Talon Hatchback 1998": 97,
+    "FIAT 500 Abarth 2012": 98,
+    "FIAT 500 Convertible 2012": 99,
+    "Ferrari 458 Italia Convertible 2012": 102,
+    "Ferrari 458 Italia Coupe 2012": 103,
+    "Ferrari California Convertible 2012": 101,
+    "Ferrari FF Coupe 2012": 100,
+    "Fisker Karma Sedan 2012": 104,
+    "Ford E-Series Wagon Van 2012": 115,
+    "Ford Edge SUV 2012": 109,
+    "Ford Expedition EL SUV 2009": 108,
+    "Ford F-150 Regular Cab 2007": 113,
+    "Ford F-150 Regular Cab 2012": 112,
+    "Ford F-450 Super Duty Crew Cab 2012": 105,
+    "Ford Fiesta Sedan 2012": 116,
+    "Ford Focus Sedan 2007": 114,
+    "Ford Freestar Minivan 2007": 107,
+    "Ford GT Coupe 2006": 111,
+    "Ford Mustang Convertible 2007": 106,
+    "Ford Ranger SuperCab 2011": 110,
+    "GMC Acadia SUV 2012": 120,
+    "GMC Canyon Extended Cab 2012": 121,
+    "GMC Savana Van 2012": 118,
+    "GMC Terrain SUV 2012": 117,
+    "GMC Yukon Hybrid SUV 2012": 119,
+    "Geo Metro Convertible 1993": 122,
+    "HUMMER H2 SUT Crew Cab 2009": 124,
+    "HUMMER H3T Crew Cab 2010": 123,
+    "Honda Accord Coupe 2012": 127,
+    "Honda Accord Sedan 2012": 128,
+    "Honda Odyssey Minivan 2007": 126,
+    "Honda Odyssey Minivan 2012": 125,
+    "Hyundai Accent Sedan 2012": 135,
+    "Hyundai Azera Sedan 2012": 139,
+    "Hyundai Elantra Sedan 2007": 134,
+    "Hyundai Elantra Touring Hatchback 2012": 138,
+    "Hyundai Genesis Sedan 2012": 136,
+    "Hyundai Santa Fe SUV 2012": 130,
+    "Hyundai Sonata Hybrid Sedan 2012": 133,
+    "Hyundai Sonata Sedan 2012": 137,
+    "Hyundai Tucson SUV 2012": 131,
+    "Hyundai Veloster Hatchback 2012": 129,
+    "Hyundai Veracruz SUV 2012": 132,
+    "Infiniti G Coupe IPL 2012": 140,
+    "Infiniti QX56 SUV 2011": 141,
+    "Isuzu Ascender SUV 2008": 142,
+    "Jaguar XK XKR 2012": 143,
+    "Jeep Compass SUV 2012": 148,
+    "Jeep Grand Cherokee SUV 2012": 147,
+    "Jeep Liberty SUV 2012": 146,
+    "Jeep Patriot SUV 2012": 144,
+    "Jeep Wrangler SUV 2012": 145,
+    "Lamborghini Aventador Coupe 2012": 150,
+    "Lamborghini Diablo Coupe 2001": 152,
+    "Lamborghini Gallardo LP 570-4 Superleggera 2012": 151,
+    "Lamborghini Reventon Coupe 2008": 149,
+    "Land Rover LR2 SUV 2012": 154,
+    "Land Rover Range Rover SUV 2012": 153,
+    "Lincoln Town Car Sedan 2011": 155,
+    "MINI Cooper Roadster Convertible 2012": 156,
+    "Maybach Landaulet Convertible 2012": 157,
+    "Mazda Tribute SUV 2011": 158,
+    "McLaren MP4-12C Coupe 2012": 159,
+    "Mercedes-Benz 300-Class Convertible 1993": 160,
+    "Mercedes-Benz C-Class Sedan 2012": 161,
+    "Mercedes-Benz E-Class Sedan 2012": 163,
+    "Mercedes-Benz S-Class Sedan 2012": 164,
+    "Mercedes-Benz SL-Class Coupe 2009": 162,
+    "Mercedes-Benz Sprinter Van 2012": 165,
+    "Mitsubishi Lancer Sedan 2012": 166,
+    "Nissan 240SX Coupe 1998": 170,
+    "Nissan Juke Hatchback 2012": 169,
+    "Nissan Leaf Hatchback 2012": 167,
+    "Nissan NV Passenger Van 2012": 168,
+    "Plymouth Neon Coupe 1999": 171,
+    "Porsche Panamera Sedan 2012": 172,
+    "Ram C/V Cargo Van Minivan 2012": 173,
+    "Rolls-Royce Ghost Sedan 2012": 175,
+    "Rolls-Royce Phantom Drophead Coupe Convertible 2012": 174,
+    "Rolls-Royce Phantom Sedan 2012": 176,
+    "Scion xD Hatchback 2012": 177,
+    "Spyker C8 Convertible 2009": 178,
+    "Spyker C8 Coupe 2009": 179,
+    "Suzuki Aerio Sedan 2007": 180,
+    "Suzuki Kizashi Sedan 2012": 181,
+    "Suzuki SX4 Hatchback 2012": 182,
+    "Suzuki SX4 Sedan 2012": 183,
+    "Tesla Model S Sedan 2012": 184,
+    "Toyota 4Runner SUV 2012": 188,
+    "Toyota Camry Sedan 2012": 186,
+    "Toyota Corolla Sedan 2012": 187,
+    "Toyota Sequoia SUV 2012": 185,
+    "Volkswagen Beetle Hatchback 2012": 191,
+    "Volkswagen Golf Hatchback 1991": 190,
+    "Volkswagen Golf Hatchback 2012": 189,
+    "Volvo 240 Sedan 1993": 193,
+    "Volvo C30 Hatchback 2012": 192,
+    "Volvo XC90 SUV 2007": 194,
+    "smart fortwo Convertible 2012": 195
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-stanford-cars-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet152-stanford-cars-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-stanford-cars-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.8-3000/README.md b/resnet152-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..c7d00943e0572b0a39f27e8c5610c7e3a9a9a04d
--- /dev/null
+++ b/resnet152-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stanford-cars.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: stanford-cars
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: train
+type: transformers
+val_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: test
+```
+
diff --git a/resnet152-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.8-3000/config.json b/resnet152-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1e0f59991da08604f363224d408031555ecd60f4
--- /dev/null
+++ b/resnet152-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,435 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "AM General Hummer SUV 2000",
+    "1": "Acura RL Sedan 2012",
+    "2": "Acura TL Sedan 2012",
+    "3": "Acura TL Type-S 2008",
+    "4": "Acura TSX Sedan 2012",
+    "5": "Acura Integra Type R 2001",
+    "6": "Acura ZDX Hatchback 2012",
+    "7": "Aston Martin V8 Vantage Convertible 2012",
+    "8": "Aston Martin V8 Vantage Coupe 2012",
+    "9": "Aston Martin Virage Convertible 2012",
+    "10": "Aston Martin Virage Coupe 2012",
+    "11": "Audi RS 4 Convertible 2008",
+    "12": "Audi A5 Coupe 2012",
+    "13": "Audi TTS Coupe 2012",
+    "14": "Audi R8 Coupe 2012",
+    "15": "Audi V8 Sedan 1994",
+    "16": "Audi 100 Sedan 1994",
+    "17": "Audi 100 Wagon 1994",
+    "18": "Audi TT Hatchback 2011",
+    "19": "Audi S6 Sedan 2011",
+    "20": "Audi S5 Convertible 2012",
+    "21": "Audi S5 Coupe 2012",
+    "22": "Audi S4 Sedan 2012",
+    "23": "Audi S4 Sedan 2007",
+    "24": "Audi TT RS Coupe 2012",
+    "25": "BMW ActiveHybrid 5 Sedan 2012",
+    "26": "BMW 1 Series Convertible 2012",
+    "27": "BMW 1 Series Coupe 2012",
+    "28": "BMW 3 Series Sedan 2012",
+    "29": "BMW 3 Series Wagon 2012",
+    "30": "BMW 6 Series Convertible 2007",
+    "31": "BMW X5 SUV 2007",
+    "32": "BMW X6 SUV 2012",
+    "33": "BMW M3 Coupe 2012",
+    "34": "BMW M5 Sedan 2010",
+    "35": "BMW M6 Convertible 2010",
+    "36": "BMW X3 SUV 2012",
+    "37": "BMW Z4 Convertible 2012",
+    "38": "Bentley Continental Supersports Conv. Convertible 2012",
+    "39": "Bentley Arnage Sedan 2009",
+    "40": "Bentley Mulsanne Sedan 2011",
+    "41": "Bentley Continental GT Coupe 2012",
+    "42": "Bentley Continental GT Coupe 2007",
+    "43": "Bentley Continental Flying Spur Sedan 2007",
+    "44": "Bugatti Veyron 16.4 Convertible 2009",
+    "45": "Bugatti Veyron 16.4 Coupe 2009",
+    "46": "Buick Regal GS 2012",
+    "47": "Buick Rainier SUV 2007",
+    "48": "Buick Verano Sedan 2012",
+    "49": "Buick Enclave SUV 2012",
+    "50": "Cadillac CTS-V Sedan 2012",
+    "51": "Cadillac SRX SUV 2012",
+    "52": "Cadillac Escalade EXT Crew Cab 2007",
+    "53": "Chevrolet Silverado 1500 Hybrid Crew Cab 2012",
+    "54": "Chevrolet Corvette Convertible 2012",
+    "55": "Chevrolet Corvette ZR1 2012",
+    "56": "Chevrolet Corvette Ron Fellows Edition Z06 2007",
+    "57": "Chevrolet Traverse SUV 2012",
+    "58": "Chevrolet Camaro Convertible 2012",
+    "59": "Chevrolet HHR SS 2010",
+    "60": "Chevrolet Impala Sedan 2007",
+    "61": "Chevrolet Tahoe Hybrid SUV 2012",
+    "62": "Chevrolet Sonic Sedan 2012",
+    "63": "Chevrolet Express Cargo Van 2007",
+    "64": "Chevrolet Avalanche Crew Cab 2012",
+    "65": "Chevrolet Cobalt SS 2010",
+    "66": "Chevrolet Malibu Hybrid Sedan 2010",
+    "67": "Chevrolet TrailBlazer SS 2009",
+    "68": "Chevrolet Silverado 2500HD Regular Cab 2012",
+    "69": "Chevrolet Silverado 1500 Classic Extended Cab 2007",
+    "70": "Chevrolet Express Van 2007",
+    "71": "Chevrolet Monte Carlo Coupe 2007",
+    "72": "Chevrolet Malibu Sedan 2007",
+    "73": "Chevrolet Silverado 1500 Extended Cab 2012",
+    "74": "Chevrolet Silverado 1500 Regular Cab 2012",
+    "75": "Chrysler Aspen SUV 2009",
+    "76": "Chrysler Sebring Convertible 2010",
+    "77": "Chrysler Town and Country Minivan 2012",
+    "78": "Chrysler 300 SRT-8 2010",
+    "79": "Chrysler Crossfire Convertible 2008",
+    "80": "Chrysler PT Cruiser Convertible 2008",
+    "81": "Daewoo Nubira Wagon 2002",
+    "82": "Dodge Caliber Wagon 2012",
+    "83": "Dodge Caliber Wagon 2007",
+    "84": "Dodge Caravan Minivan 1997",
+    "85": "Dodge Ram Pickup 3500 Crew Cab 2010",
+    "86": "Dodge Ram Pickup 3500 Quad Cab 2009",
+    "87": "Dodge Sprinter Cargo Van 2009",
+    "88": "Dodge Journey SUV 2012",
+    "89": "Dodge Dakota Crew Cab 2010",
+    "90": "Dodge Dakota Club Cab 2007",
+    "91": "Dodge Magnum Wagon 2008",
+    "92": "Dodge Challenger SRT8 2011",
+    "93": "Dodge Durango SUV 2012",
+    "94": "Dodge Durango SUV 2007",
+    "95": "Dodge Charger Sedan 2012",
+    "96": "Dodge Charger SRT-8 2009",
+    "97": "Eagle Talon Hatchback 1998",
+    "98": "FIAT 500 Abarth 2012",
+    "99": "FIAT 500 Convertible 2012",
+    "100": "Ferrari FF Coupe 2012",
+    "101": "Ferrari California Convertible 2012",
+    "102": "Ferrari 458 Italia Convertible 2012",
+    "103": "Ferrari 458 Italia Coupe 2012",
+    "104": "Fisker Karma Sedan 2012",
+    "105": "Ford F-450 Super Duty Crew Cab 2012",
+    "106": "Ford Mustang Convertible 2007",
+    "107": "Ford Freestar Minivan 2007",
+    "108": "Ford Expedition EL SUV 2009",
+    "109": "Ford Edge SUV 2012",
+    "110": "Ford Ranger SuperCab 2011",
+    "111": "Ford GT Coupe 2006",
+    "112": "Ford F-150 Regular Cab 2012",
+    "113": "Ford F-150 Regular Cab 2007",
+    "114": "Ford Focus Sedan 2007",
+    "115": "Ford E-Series Wagon Van 2012",
+    "116": "Ford Fiesta Sedan 2012",
+    "117": "GMC Terrain SUV 2012",
+    "118": "GMC Savana Van 2012",
+    "119": "GMC Yukon Hybrid SUV 2012",
+    "120": "GMC Acadia SUV 2012",
+    "121": "GMC Canyon Extended Cab 2012",
+    "122": "Geo Metro Convertible 1993",
+    "123": "HUMMER H3T Crew Cab 2010",
+    "124": "HUMMER H2 SUT Crew Cab 2009",
+    "125": "Honda Odyssey Minivan 2012",
+    "126": "Honda Odyssey Minivan 2007",
+    "127": "Honda Accord Coupe 2012",
+    "128": "Honda Accord Sedan 2012",
+    "129": "Hyundai Veloster Hatchback 2012",
+    "130": "Hyundai Santa Fe SUV 2012",
+    "131": "Hyundai Tucson SUV 2012",
+    "132": "Hyundai Veracruz SUV 2012",
+    "133": "Hyundai Sonata Hybrid Sedan 2012",
+    "134": "Hyundai Elantra Sedan 2007",
+    "135": "Hyundai Accent Sedan 2012",
+    "136": "Hyundai Genesis Sedan 2012",
+    "137": "Hyundai Sonata Sedan 2012",
+    "138": "Hyundai Elantra Touring Hatchback 2012",
+    "139": "Hyundai Azera Sedan 2012",
+    "140": "Infiniti G Coupe IPL 2012",
+    "141": "Infiniti QX56 SUV 2011",
+    "142": "Isuzu Ascender SUV 2008",
+    "143": "Jaguar XK XKR 2012",
+    "144": "Jeep Patriot SUV 2012",
+    "145": "Jeep Wrangler SUV 2012",
+    "146": "Jeep Liberty SUV 2012",
+    "147": "Jeep Grand Cherokee SUV 2012",
+    "148": "Jeep Compass SUV 2012",
+    "149": "Lamborghini Reventon Coupe 2008",
+    "150": "Lamborghini Aventador Coupe 2012",
+    "151": "Lamborghini Gallardo LP 570-4 Superleggera 2012",
+    "152": "Lamborghini Diablo Coupe 2001",
+    "153": "Land Rover Range Rover SUV 2012",
+    "154": "Land Rover LR2 SUV 2012",
+    "155": "Lincoln Town Car Sedan 2011",
+    "156": "MINI Cooper Roadster Convertible 2012",
+    "157": "Maybach Landaulet Convertible 2012",
+    "158": "Mazda Tribute SUV 2011",
+    "159": "McLaren MP4-12C Coupe 2012",
+    "160": "Mercedes-Benz 300-Class Convertible 1993",
+    "161": "Mercedes-Benz C-Class Sedan 2012",
+    "162": "Mercedes-Benz SL-Class Coupe 2009",
+    "163": "Mercedes-Benz E-Class Sedan 2012",
+    "164": "Mercedes-Benz S-Class Sedan 2012",
+    "165": "Mercedes-Benz Sprinter Van 2012",
+    "166": "Mitsubishi Lancer Sedan 2012",
+    "167": "Nissan Leaf Hatchback 2012",
+    "168": "Nissan NV Passenger Van 2012",
+    "169": "Nissan Juke Hatchback 2012",
+    "170": "Nissan 240SX Coupe 1998",
+    "171": "Plymouth Neon Coupe 1999",
+    "172": "Porsche Panamera Sedan 2012",
+    "173": "Ram C/V Cargo Van Minivan 2012",
+    "174": "Rolls-Royce Phantom Drophead Coupe Convertible 2012",
+    "175": "Rolls-Royce Ghost Sedan 2012",
+    "176": "Rolls-Royce Phantom Sedan 2012",
+    "177": "Scion xD Hatchback 2012",
+    "178": "Spyker C8 Convertible 2009",
+    "179": "Spyker C8 Coupe 2009",
+    "180": "Suzuki Aerio Sedan 2007",
+    "181": "Suzuki Kizashi Sedan 2012",
+    "182": "Suzuki SX4 Hatchback 2012",
+    "183": "Suzuki SX4 Sedan 2012",
+    "184": "Tesla Model S Sedan 2012",
+    "185": "Toyota Sequoia SUV 2012",
+    "186": "Toyota Camry Sedan 2012",
+    "187": "Toyota Corolla Sedan 2012",
+    "188": "Toyota 4Runner SUV 2012",
+    "189": "Volkswagen Golf Hatchback 2012",
+    "190": "Volkswagen Golf Hatchback 1991",
+    "191": "Volkswagen Beetle Hatchback 2012",
+    "192": "Volvo C30 Hatchback 2012",
+    "193": "Volvo 240 Sedan 1993",
+    "194": "Volvo XC90 SUV 2007",
+    "195": "smart fortwo Convertible 2012"
+  },
+  "label2id": {
+    "AM General Hummer SUV 2000": 0,
+    "Acura Integra Type R 2001": 5,
+    "Acura RL Sedan 2012": 1,
+    "Acura TL Sedan 2012": 2,
+    "Acura TL Type-S 2008": 3,
+    "Acura TSX Sedan 2012": 4,
+    "Acura ZDX Hatchback 2012": 6,
+    "Aston Martin V8 Vantage Convertible 2012": 7,
+    "Aston Martin V8 Vantage Coupe 2012": 8,
+    "Aston Martin Virage Convertible 2012": 9,
+    "Aston Martin Virage Coupe 2012": 10,
+    "Audi 100 Sedan 1994": 16,
+    "Audi 100 Wagon 1994": 17,
+    "Audi A5 Coupe 2012": 12,
+    "Audi R8 Coupe 2012": 14,
+    "Audi RS 4 Convertible 2008": 11,
+    "Audi S4 Sedan 2007": 23,
+    "Audi S4 Sedan 2012": 22,
+    "Audi S5 Convertible 2012": 20,
+    "Audi S5 Coupe 2012": 21,
+    "Audi S6 Sedan 2011": 19,
+    "Audi TT Hatchback 2011": 18,
+    "Audi TT RS Coupe 2012": 24,
+    "Audi TTS Coupe 2012": 13,
+    "Audi V8 Sedan 1994": 15,
+    "BMW 1 Series Convertible 2012": 26,
+    "BMW 1 Series Coupe 2012": 27,
+    "BMW 3 Series Sedan 2012": 28,
+    "BMW 3 Series Wagon 2012": 29,
+    "BMW 6 Series Convertible 2007": 30,
+    "BMW ActiveHybrid 5 Sedan 2012": 25,
+    "BMW M3 Coupe 2012": 33,
+    "BMW M5 Sedan 2010": 34,
+    "BMW M6 Convertible 2010": 35,
+    "BMW X3 SUV 2012": 36,
+    "BMW X5 SUV 2007": 31,
+    "BMW X6 SUV 2012": 32,
+    "BMW Z4 Convertible 2012": 37,
+    "Bentley Arnage Sedan 2009": 39,
+    "Bentley Continental Flying Spur Sedan 2007": 43,
+    "Bentley Continental GT Coupe 2007": 42,
+    "Bentley Continental GT Coupe 2012": 41,
+    "Bentley Continental Supersports Conv. Convertible 2012": 38,
+    "Bentley Mulsanne Sedan 2011": 40,
+    "Bugatti Veyron 16.4 Convertible 2009": 44,
+    "Bugatti Veyron 16.4 Coupe 2009": 45,
+    "Buick Enclave SUV 2012": 49,
+    "Buick Rainier SUV 2007": 47,
+    "Buick Regal GS 2012": 46,
+    "Buick Verano Sedan 2012": 48,
+    "Cadillac CTS-V Sedan 2012": 50,
+    "Cadillac Escalade EXT Crew Cab 2007": 52,
+    "Cadillac SRX SUV 2012": 51,
+    "Chevrolet Avalanche Crew Cab 2012": 64,
+    "Chevrolet Camaro Convertible 2012": 58,
+    "Chevrolet Cobalt SS 2010": 65,
+    "Chevrolet Corvette Convertible 2012": 54,
+    "Chevrolet Corvette Ron Fellows Edition Z06 2007": 56,
+    "Chevrolet Corvette ZR1 2012": 55,
+    "Chevrolet Express Cargo Van 2007": 63,
+    "Chevrolet Express Van 2007": 70,
+    "Chevrolet HHR SS 2010": 59,
+    "Chevrolet Impala Sedan 2007": 60,
+    "Chevrolet Malibu Hybrid Sedan 2010": 66,
+    "Chevrolet Malibu Sedan 2007": 72,
+    "Chevrolet Monte Carlo Coupe 2007": 71,
+    "Chevrolet Silverado 1500 Classic Extended Cab 2007": 69,
+    "Chevrolet Silverado 1500 Extended Cab 2012": 73,
+    "Chevrolet Silverado 1500 Hybrid Crew Cab 2012": 53,
+    "Chevrolet Silverado 1500 Regular Cab 2012": 74,
+    "Chevrolet Silverado 2500HD Regular Cab 2012": 68,
+    "Chevrolet Sonic Sedan 2012": 62,
+    "Chevrolet Tahoe Hybrid SUV 2012": 61,
+    "Chevrolet TrailBlazer SS 2009": 67,
+    "Chevrolet Traverse SUV 2012": 57,
+    "Chrysler 300 SRT-8 2010": 78,
+    "Chrysler Aspen SUV 2009": 75,
+    "Chrysler Crossfire Convertible 2008": 79,
+    "Chrysler PT Cruiser Convertible 2008": 80,
+    "Chrysler Sebring Convertible 2010": 76,
+    "Chrysler Town and Country Minivan 2012": 77,
+    "Daewoo Nubira Wagon 2002": 81,
+    "Dodge Caliber Wagon 2007": 83,
+    "Dodge Caliber Wagon 2012": 82,
+    "Dodge Caravan Minivan 1997": 84,
+    "Dodge Challenger SRT8 2011": 92,
+    "Dodge Charger SRT-8 2009": 96,
+    "Dodge Charger Sedan 2012": 95,
+    "Dodge Dakota Club Cab 2007": 90,
+    "Dodge Dakota Crew Cab 2010": 89,
+    "Dodge Durango SUV 2007": 94,
+    "Dodge Durango SUV 2012": 93,
+    "Dodge Journey SUV 2012": 88,
+    "Dodge Magnum Wagon 2008": 91,
+    "Dodge Ram Pickup 3500 Crew Cab 2010": 85,
+    "Dodge Ram Pickup 3500 Quad Cab 2009": 86,
+    "Dodge Sprinter Cargo Van 2009": 87,
+    "Eagle Talon Hatchback 1998": 97,
+    "FIAT 500 Abarth 2012": 98,
+    "FIAT 500 Convertible 2012": 99,
+    "Ferrari 458 Italia Convertible 2012": 102,
+    "Ferrari 458 Italia Coupe 2012": 103,
+    "Ferrari California Convertible 2012": 101,
+    "Ferrari FF Coupe 2012": 100,
+    "Fisker Karma Sedan 2012": 104,
+    "Ford E-Series Wagon Van 2012": 115,
+    "Ford Edge SUV 2012": 109,
+    "Ford Expedition EL SUV 2009": 108,
+    "Ford F-150 Regular Cab 2007": 113,
+    "Ford F-150 Regular Cab 2012": 112,
+    "Ford F-450 Super Duty Crew Cab 2012": 105,
+    "Ford Fiesta Sedan 2012": 116,
+    "Ford Focus Sedan 2007": 114,
+    "Ford Freestar Minivan 2007": 107,
+    "Ford GT Coupe 2006": 111,
+    "Ford Mustang Convertible 2007": 106,
+    "Ford Ranger SuperCab 2011": 110,
+    "GMC Acadia SUV 2012": 120,
+    "GMC Canyon Extended Cab 2012": 121,
+    "GMC Savana Van 2012": 118,
+    "GMC Terrain SUV 2012": 117,
+    "GMC Yukon Hybrid SUV 2012": 119,
+    "Geo Metro Convertible 1993": 122,
+    "HUMMER H2 SUT Crew Cab 2009": 124,
+    "HUMMER H3T Crew Cab 2010": 123,
+    "Honda Accord Coupe 2012": 127,
+    "Honda Accord Sedan 2012": 128,
+    "Honda Odyssey Minivan 2007": 126,
+    "Honda Odyssey Minivan 2012": 125,
+    "Hyundai Accent Sedan 2012": 135,
+    "Hyundai Azera Sedan 2012": 139,
+    "Hyundai Elantra Sedan 2007": 134,
+    "Hyundai Elantra Touring Hatchback 2012": 138,
+    "Hyundai Genesis Sedan 2012": 136,
+    "Hyundai Santa Fe SUV 2012": 130,
+    "Hyundai Sonata Hybrid Sedan 2012": 133,
+    "Hyundai Sonata Sedan 2012": 137,
+    "Hyundai Tucson SUV 2012": 131,
+    "Hyundai Veloster Hatchback 2012": 129,
+    "Hyundai Veracruz SUV 2012": 132,
+    "Infiniti G Coupe IPL 2012": 140,
+    "Infiniti QX56 SUV 2011": 141,
+    "Isuzu Ascender SUV 2008": 142,
+    "Jaguar XK XKR 2012": 143,
+    "Jeep Compass SUV 2012": 148,
+    "Jeep Grand Cherokee SUV 2012": 147,
+    "Jeep Liberty SUV 2012": 146,
+    "Jeep Patriot SUV 2012": 144,
+    "Jeep Wrangler SUV 2012": 145,
+    "Lamborghini Aventador Coupe 2012": 150,
+    "Lamborghini Diablo Coupe 2001": 152,
+    "Lamborghini Gallardo LP 570-4 Superleggera 2012": 151,
+    "Lamborghini Reventon Coupe 2008": 149,
+    "Land Rover LR2 SUV 2012": 154,
+    "Land Rover Range Rover SUV 2012": 153,
+    "Lincoln Town Car Sedan 2011": 155,
+    "MINI Cooper Roadster Convertible 2012": 156,
+    "Maybach Landaulet Convertible 2012": 157,
+    "Mazda Tribute SUV 2011": 158,
+    "McLaren MP4-12C Coupe 2012": 159,
+    "Mercedes-Benz 300-Class Convertible 1993": 160,
+    "Mercedes-Benz C-Class Sedan 2012": 161,
+    "Mercedes-Benz E-Class Sedan 2012": 163,
+    "Mercedes-Benz S-Class Sedan 2012": 164,
+    "Mercedes-Benz SL-Class Coupe 2009": 162,
+    "Mercedes-Benz Sprinter Van 2012": 165,
+    "Mitsubishi Lancer Sedan 2012": 166,
+    "Nissan 240SX Coupe 1998": 170,
+    "Nissan Juke Hatchback 2012": 169,
+    "Nissan Leaf Hatchback 2012": 167,
+    "Nissan NV Passenger Van 2012": 168,
+    "Plymouth Neon Coupe 1999": 171,
+    "Porsche Panamera Sedan 2012": 172,
+    "Ram C/V Cargo Van Minivan 2012": 173,
+    "Rolls-Royce Ghost Sedan 2012": 175,
+    "Rolls-Royce Phantom Drophead Coupe Convertible 2012": 174,
+    "Rolls-Royce Phantom Sedan 2012": 176,
+    "Scion xD Hatchback 2012": 177,
+    "Spyker C8 Convertible 2009": 178,
+    "Spyker C8 Coupe 2009": 179,
+    "Suzuki Aerio Sedan 2007": 180,
+    "Suzuki Kizashi Sedan 2012": 181,
+    "Suzuki SX4 Hatchback 2012": 182,
+    "Suzuki SX4 Sedan 2012": 183,
+    "Tesla Model S Sedan 2012": 184,
+    "Toyota 4Runner SUV 2012": 188,
+    "Toyota Camry Sedan 2012": 186,
+    "Toyota Corolla Sedan 2012": 187,
+    "Toyota Sequoia SUV 2012": 185,
+    "Volkswagen Beetle Hatchback 2012": 191,
+    "Volkswagen Golf Hatchback 1991": 190,
+    "Volkswagen Golf Hatchback 2012": 189,
+    "Volvo 240 Sedan 1993": 193,
+    "Volvo C30 Hatchback 2012": 192,
+    "Volvo XC90 SUV 2007": 194,
+    "smart fortwo Convertible 2012": 195
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet152-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-stl10-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/README.md b/resnet152-stl10-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..32ffd24993f9112aee430366f23e2f1b32b34543
--- /dev/null
+++ b/resnet152-stl10-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stl10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: stl10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: train
+type: transformers
+val_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: test
+```
+
diff --git a/resnet152-stl10-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/config.json b/resnet152-stl10-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..4e96dfc41ebe7919b6d046db75114c5d465f222d
--- /dev/null
+++ b/resnet152-stl10-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "bird",
+    "2": "car",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "horse",
+    "7": "monkey",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "bird": 1,
+    "car": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "horse": 6,
+    "monkey": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-stl10-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet152-stl10-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-stl10-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-stl10-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/README.md b/resnet152-stl10-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..3f7ab36c9e531817eaf53a8d12c257b8811fc03b
--- /dev/null
+++ b/resnet152-stl10-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stl10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: stl10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: train
+type: transformers
+val_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: test
+```
+
diff --git a/resnet152-stl10-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/config.json b/resnet152-stl10-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..4e96dfc41ebe7919b6d046db75114c5d465f222d
--- /dev/null
+++ b/resnet152-stl10-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "bird",
+    "2": "car",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "horse",
+    "7": "monkey",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "bird": 1,
+    "car": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "horse": 6,
+    "monkey": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-stl10-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet152-stl10-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-stl10-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-stl10-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/README.md b/resnet152-stl10-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..0356fdbbca9c43c2cbefc50b8b105bbb2286968e
--- /dev/null
+++ b/resnet152-stl10-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stl10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: stl10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: train
+type: transformers
+val_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: test
+```
+
diff --git a/resnet152-stl10-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/config.json b/resnet152-stl10-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..4e96dfc41ebe7919b6d046db75114c5d465f222d
--- /dev/null
+++ b/resnet152-stl10-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "bird",
+    "2": "car",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "horse",
+    "7": "monkey",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "bird": 1,
+    "car": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "horse": 6,
+    "monkey": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-stl10-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet152-stl10-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-stl10-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/README.md b/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..6ef094429722e6a4a76142bd3a3ffb5ac17d68a6
--- /dev/null
+++ b/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stl10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: stl10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: train
+type: transformers
+val_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: test
+```
+
diff --git a/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/config.json b/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..4e96dfc41ebe7919b6d046db75114c5d465f222d
--- /dev/null
+++ b/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "bird",
+    "2": "car",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "horse",
+    "7": "monkey",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "bird": 1,
+    "car": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "horse": 6,
+    "monkey": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/README.md b/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..fdc1d0ff9dd59217e7ecdfd49a585d01b8a7df0c
--- /dev/null
+++ b/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stl10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: stl10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: train
+type: transformers
+val_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: test
+```
+
diff --git a/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/config.json b/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..4e96dfc41ebe7919b6d046db75114c5d465f222d
--- /dev/null
+++ b/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "bird",
+    "2": "car",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "horse",
+    "7": "monkey",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "bird": 1,
+    "car": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "horse": 6,
+    "monkey": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/README.md b/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..a9b45d80b2a3c2041d9cca180dcf833a442ae5a0
--- /dev/null
+++ b/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stl10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: stl10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: train
+type: transformers
+val_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: test
+```
+
diff --git a/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/config.json b/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..4e96dfc41ebe7919b6d046db75114c5d465f222d
--- /dev/null
+++ b/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "bird",
+    "2": "car",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "horse",
+    "7": "monkey",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "bird": 1,
+    "car": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "horse": 6,
+    "monkey": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-stl10-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/README.md b/resnet152-stl10-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..32ffd24993f9112aee430366f23e2f1b32b34543
--- /dev/null
+++ b/resnet152-stl10-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stl10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: stl10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: train
+type: transformers
+val_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: test
+```
+
diff --git a/resnet152-stl10-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/config.json b/resnet152-stl10-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..4e96dfc41ebe7919b6d046db75114c5d465f222d
--- /dev/null
+++ b/resnet152-stl10-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "bird",
+    "2": "car",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "horse",
+    "7": "monkey",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "bird": 1,
+    "car": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "horse": 6,
+    "monkey": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-stl10-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet152-stl10-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-stl10-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-stl10-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/README.md b/resnet152-stl10-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..969d8bc1b9a6b7368970686980bf32aa06ca84ad
--- /dev/null
+++ b/resnet152-stl10-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stl10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: stl10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: train
+type: transformers
+val_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: test
+```
+
diff --git a/resnet152-stl10-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/config.json b/resnet152-stl10-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..4e96dfc41ebe7919b6d046db75114c5d465f222d
--- /dev/null
+++ b/resnet152-stl10-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "bird",
+    "2": "car",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "horse",
+    "7": "monkey",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "bird": 1,
+    "car": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "horse": 6,
+    "monkey": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-stl10-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet152-stl10-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-stl10-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-stl10-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/README.md b/resnet152-stl10-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..3e72c3eec5903b8cad63744200bd030c58397445
--- /dev/null
+++ b/resnet152-stl10-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stl10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: stl10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: train
+type: transformers
+val_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: test
+```
+
diff --git a/resnet152-stl10-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/config.json b/resnet152-stl10-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..4e96dfc41ebe7919b6d046db75114c5d465f222d
--- /dev/null
+++ b/resnet152-stl10-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "bird",
+    "2": "car",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "horse",
+    "7": "monkey",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "bird": 1,
+    "car": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "horse": 6,
+    "monkey": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-stl10-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet152-stl10-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-stl10-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-sun397-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/README.md b/resnet152-sun397-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..8d613ed9100146b1b6b945a12a7f8d2b40245a6a
--- /dev/null
+++ b/resnet152-sun397-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset sun397.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: sun397
+    pretrained: true
+test_datasets: null
+train_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: train
+type: transformers
+val_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: test
+```
+
diff --git a/resnet152-sun397-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/config.json b/resnet152-sun397-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..235472e739b23ead2b88b4266434b8f42502d7ea
--- /dev/null
+++ b/resnet152-sun397-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,837 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "abbey",
+    "1": "airplane cabin",
+    "2": "airport terminal",
+    "3": "alley",
+    "4": "amphitheater",
+    "5": "amusement arcade",
+    "6": "amusement park",
+    "7": "anechoic chamber",
+    "8": "apartment building outdoor",
+    "9": "apse indoor",
+    "10": "aquarium",
+    "11": "aqueduct",
+    "12": "arch",
+    "13": "archive",
+    "14": "arrival gate outdoor",
+    "15": "art gallery",
+    "16": "art school",
+    "17": "art studio",
+    "18": "assembly line",
+    "19": "athletic field outdoor",
+    "20": "atrium public",
+    "21": "attic",
+    "22": "auditorium",
+    "23": "auto factory",
+    "24": "badlands",
+    "25": "badminton court indoor",
+    "26": "baggage claim",
+    "27": "bakery shop",
+    "28": "balcony exterior",
+    "29": "balcony interior",
+    "30": "ball pit",
+    "31": "ballroom",
+    "32": "bamboo forest",
+    "33": "banquet hall",
+    "34": "bar",
+    "35": "barn",
+    "36": "barndoor",
+    "37": "baseball field",
+    "38": "basement",
+    "39": "basilica",
+    "40": "basketball court outdoor",
+    "41": "bathroom",
+    "42": "batters box",
+    "43": "bayou",
+    "44": "bazaar indoor",
+    "45": "bazaar outdoor",
+    "46": "beach",
+    "47": "beauty salon",
+    "48": "bedroom",
+    "49": "berth",
+    "50": "biology laboratory",
+    "51": "bistro indoor",
+    "52": "boardwalk",
+    "53": "boat deck",
+    "54": "boathouse",
+    "55": "bookstore",
+    "56": "booth indoor",
+    "57": "botanical garden",
+    "58": "bow window indoor",
+    "59": "bow window outdoor",
+    "60": "bowling alley",
+    "61": "boxing ring",
+    "62": "brewery indoor",
+    "63": "bridge",
+    "64": "building facade",
+    "65": "bullring",
+    "66": "burial chamber",
+    "67": "bus interior",
+    "68": "butchers shop",
+    "69": "butte",
+    "70": "cabin outdoor",
+    "71": "cafeteria",
+    "72": "campsite",
+    "73": "campus",
+    "74": "canal natural",
+    "75": "canal urban",
+    "76": "candy store",
+    "77": "canyon",
+    "78": "car interior backseat",
+    "79": "car interior frontseat",
+    "80": "carrousel",
+    "81": "casino indoor",
+    "82": "castle",
+    "83": "catacomb",
+    "84": "cathedral indoor",
+    "85": "cathedral outdoor",
+    "86": "cavern indoor",
+    "87": "cemetery",
+    "88": "chalet",
+    "89": "cheese factory",
+    "90": "chemistry lab",
+    "91": "chicken coop indoor",
+    "92": "chicken coop outdoor",
+    "93": "childs room",
+    "94": "church indoor",
+    "95": "church outdoor",
+    "96": "classroom",
+    "97": "clean room",
+    "98": "cliff",
+    "99": "cloister indoor",
+    "100": "closet",
+    "101": "clothing store",
+    "102": "coast",
+    "103": "cockpit",
+    "104": "coffee shop",
+    "105": "computer room",
+    "106": "conference center",
+    "107": "conference room",
+    "108": "construction site",
+    "109": "control room",
+    "110": "control tower outdoor",
+    "111": "corn field",
+    "112": "corral",
+    "113": "corridor",
+    "114": "cottage garden",
+    "115": "courthouse",
+    "116": "courtroom",
+    "117": "courtyard",
+    "118": "covered bridge exterior",
+    "119": "creek",
+    "120": "crevasse",
+    "121": "crosswalk",
+    "122": "cubicle office",
+    "123": "dam",
+    "124": "delicatessen",
+    "125": "dentists office",
+    "126": "desert sand",
+    "127": "desert vegetation",
+    "128": "diner indoor",
+    "129": "diner outdoor",
+    "130": "dinette home",
+    "131": "dinette vehicle",
+    "132": "dining car",
+    "133": "dining room",
+    "134": "discotheque",
+    "135": "dock",
+    "136": "doorway outdoor",
+    "137": "dorm room",
+    "138": "driveway",
+    "139": "driving range outdoor",
+    "140": "drugstore",
+    "141": "electrical substation",
+    "142": "elevator door",
+    "143": "elevator interior",
+    "144": "elevator shaft",
+    "145": "engine room",
+    "146": "escalator indoor",
+    "147": "excavation",
+    "148": "factory indoor",
+    "149": "fairway",
+    "150": "fastfood restaurant",
+    "151": "field cultivated",
+    "152": "field wild",
+    "153": "fire escape",
+    "154": "fire station",
+    "155": "firing range indoor",
+    "156": "fishpond",
+    "157": "florist shop indoor",
+    "158": "food court",
+    "159": "forest broadleaf",
+    "160": "forest needleleaf",
+    "161": "forest path",
+    "162": "forest road",
+    "163": "formal garden",
+    "164": "fountain",
+    "165": "galley",
+    "166": "game room",
+    "167": "garage indoor",
+    "168": "garbage dump",
+    "169": "gas station",
+    "170": "gazebo exterior",
+    "171": "general store indoor",
+    "172": "general store outdoor",
+    "173": "gift shop",
+    "174": "golf course",
+    "175": "greenhouse indoor",
+    "176": "greenhouse outdoor",
+    "177": "gymnasium indoor",
+    "178": "hangar indoor",
+    "179": "hangar outdoor",
+    "180": "harbor",
+    "181": "hayfield",
+    "182": "heliport",
+    "183": "herb garden",
+    "184": "highway",
+    "185": "hill",
+    "186": "home office",
+    "187": "hospital",
+    "188": "hospital room",
+    "189": "hot spring",
+    "190": "hot tub outdoor",
+    "191": "hotel outdoor",
+    "192": "hotel room",
+    "193": "house",
+    "194": "hunting lodge outdoor",
+    "195": "ice cream parlor",
+    "196": "ice floe",
+    "197": "ice shelf",
+    "198": "ice skating rink indoor",
+    "199": "ice skating rink outdoor",
+    "200": "iceberg",
+    "201": "igloo",
+    "202": "industrial area",
+    "203": "inn outdoor",
+    "204": "islet",
+    "205": "jacuzzi indoor",
+    "206": "jail cell",
+    "207": "jail indoor",
+    "208": "jewelry shop",
+    "209": "kasbah",
+    "210": "kennel indoor",
+    "211": "kennel outdoor",
+    "212": "kindergarden classroom",
+    "213": "kitchen",
+    "214": "kitchenette",
+    "215": "labyrinth outdoor",
+    "216": "lake natural",
+    "217": "landfill",
+    "218": "landing deck",
+    "219": "laundromat",
+    "220": "lecture room",
+    "221": "library indoor",
+    "222": "library outdoor",
+    "223": "lido deck outdoor",
+    "224": "lift bridge",
+    "225": "lighthouse",
+    "226": "limousine interior",
+    "227": "living room",
+    "228": "lobby",
+    "229": "lock chamber",
+    "230": "locker room",
+    "231": "mansion",
+    "232": "manufactured home",
+    "233": "market indoor",
+    "234": "market outdoor",
+    "235": "marsh",
+    "236": "martial arts gym",
+    "237": "mausoleum",
+    "238": "medina",
+    "239": "moat water",
+    "240": "monastery outdoor",
+    "241": "mosque indoor",
+    "242": "mosque outdoor",
+    "243": "motel",
+    "244": "mountain",
+    "245": "mountain snowy",
+    "246": "movie theater indoor",
+    "247": "museum indoor",
+    "248": "music store",
+    "249": "music studio",
+    "250": "nuclear power plant outdoor",
+    "251": "nursery",
+    "252": "oast house",
+    "253": "observatory outdoor",
+    "254": "ocean",
+    "255": "office",
+    "256": "office building",
+    "257": "oil refinery outdoor",
+    "258": "oilrig",
+    "259": "operating room",
+    "260": "orchard",
+    "261": "outhouse outdoor",
+    "262": "pagoda",
+    "263": "palace",
+    "264": "pantry",
+    "265": "park",
+    "266": "parking garage indoor",
+    "267": "parking garage outdoor",
+    "268": "parking lot",
+    "269": "parlor",
+    "270": "pasture",
+    "271": "patio",
+    "272": "pavilion",
+    "273": "pharmacy",
+    "274": "phone booth",
+    "275": "physics laboratory",
+    "276": "picnic area",
+    "277": "pilothouse indoor",
+    "278": "planetarium outdoor",
+    "279": "playground",
+    "280": "playroom",
+    "281": "plaza",
+    "282": "podium indoor",
+    "283": "podium outdoor",
+    "284": "pond",
+    "285": "poolroom establishment",
+    "286": "poolroom home",
+    "287": "power plant outdoor",
+    "288": "promenade deck",
+    "289": "pub indoor",
+    "290": "pulpit",
+    "291": "putting green",
+    "292": "racecourse",
+    "293": "raceway",
+    "294": "raft",
+    "295": "railroad track",
+    "296": "rainforest",
+    "297": "reception",
+    "298": "recreation room",
+    "299": "residential neighborhood",
+    "300": "restaurant",
+    "301": "restaurant kitchen",
+    "302": "restaurant patio",
+    "303": "rice paddy",
+    "304": "riding arena",
+    "305": "river",
+    "306": "rock arch",
+    "307": "rope bridge",
+    "308": "ruin",
+    "309": "runway",
+    "310": "sandbar",
+    "311": "sandbox",
+    "312": "sauna",
+    "313": "schoolhouse",
+    "314": "sea cliff",
+    "315": "server room",
+    "316": "shed",
+    "317": "shoe shop",
+    "318": "shopfront",
+    "319": "shopping mall indoor",
+    "320": "shower",
+    "321": "skatepark",
+    "322": "ski lodge",
+    "323": "ski resort",
+    "324": "ski slope",
+    "325": "sky",
+    "326": "skyscraper",
+    "327": "slum",
+    "328": "snowfield",
+    "329": "squash court",
+    "330": "stable",
+    "331": "stadium baseball",
+    "332": "stadium football",
+    "333": "stage indoor",
+    "334": "staircase",
+    "335": "street",
+    "336": "subway interior",
+    "337": "subway station platform",
+    "338": "supermarket",
+    "339": "sushi bar",
+    "340": "swamp",
+    "341": "swimming pool indoor",
+    "342": "swimming pool outdoor",
+    "343": "synagogue indoor",
+    "344": "synagogue outdoor",
+    "345": "television studio",
+    "346": "temple east asia",
+    "347": "temple south asia",
+    "348": "tennis court indoor",
+    "349": "tennis court outdoor",
+    "350": "tent outdoor",
+    "351": "theater indoor procenium",
+    "352": "theater indoor seats",
+    "353": "thriftshop",
+    "354": "throne room",
+    "355": "ticket booth",
+    "356": "toll plaza",
+    "357": "topiary garden",
+    "358": "tower",
+    "359": "toyshop",
+    "360": "track outdoor",
+    "361": "train railway",
+    "362": "train station platform",
+    "363": "tree farm",
+    "364": "tree house",
+    "365": "trench",
+    "366": "underwater coral reef",
+    "367": "utility room",
+    "368": "valley",
+    "369": "van interior",
+    "370": "vegetable garden",
+    "371": "veranda",
+    "372": "veterinarians office",
+    "373": "viaduct",
+    "374": "videostore",
+    "375": "village",
+    "376": "vineyard",
+    "377": "volcano",
+    "378": "volleyball court indoor",
+    "379": "volleyball court outdoor",
+    "380": "waiting room",
+    "381": "warehouse indoor",
+    "382": "water tower",
+    "383": "waterfall block",
+    "384": "waterfall fan",
+    "385": "waterfall plunge",
+    "386": "watering hole",
+    "387": "wave",
+    "388": "wet bar",
+    "389": "wheat field",
+    "390": "wind farm",
+    "391": "windmill",
+    "392": "wine cellar barrel storage",
+    "393": "wine cellar bottle storage",
+    "394": "wrestling ring indoor",
+    "395": "yard",
+    "396": "youth hostel"
+  },
+  "label2id": {
+    "abbey": 0,
+    "airplane cabin": 1,
+    "airport terminal": 2,
+    "alley": 3,
+    "amphitheater": 4,
+    "amusement arcade": 5,
+    "amusement park": 6,
+    "anechoic chamber": 7,
+    "apartment building outdoor": 8,
+    "apse indoor": 9,
+    "aquarium": 10,
+    "aqueduct": 11,
+    "arch": 12,
+    "archive": 13,
+    "arrival gate outdoor": 14,
+    "art gallery": 15,
+    "art school": 16,
+    "art studio": 17,
+    "assembly line": 18,
+    "athletic field outdoor": 19,
+    "atrium public": 20,
+    "attic": 21,
+    "auditorium": 22,
+    "auto factory": 23,
+    "badlands": 24,
+    "badminton court indoor": 25,
+    "baggage claim": 26,
+    "bakery shop": 27,
+    "balcony exterior": 28,
+    "balcony interior": 29,
+    "ball pit": 30,
+    "ballroom": 31,
+    "bamboo forest": 32,
+    "banquet hall": 33,
+    "bar": 34,
+    "barn": 35,
+    "barndoor": 36,
+    "baseball field": 37,
+    "basement": 38,
+    "basilica": 39,
+    "basketball court outdoor": 40,
+    "bathroom": 41,
+    "batters box": 42,
+    "bayou": 43,
+    "bazaar indoor": 44,
+    "bazaar outdoor": 45,
+    "beach": 46,
+    "beauty salon": 47,
+    "bedroom": 48,
+    "berth": 49,
+    "biology laboratory": 50,
+    "bistro indoor": 51,
+    "boardwalk": 52,
+    "boat deck": 53,
+    "boathouse": 54,
+    "bookstore": 55,
+    "booth indoor": 56,
+    "botanical garden": 57,
+    "bow window indoor": 58,
+    "bow window outdoor": 59,
+    "bowling alley": 60,
+    "boxing ring": 61,
+    "brewery indoor": 62,
+    "bridge": 63,
+    "building facade": 64,
+    "bullring": 65,
+    "burial chamber": 66,
+    "bus interior": 67,
+    "butchers shop": 68,
+    "butte": 69,
+    "cabin outdoor": 70,
+    "cafeteria": 71,
+    "campsite": 72,
+    "campus": 73,
+    "canal natural": 74,
+    "canal urban": 75,
+    "candy store": 76,
+    "canyon": 77,
+    "car interior backseat": 78,
+    "car interior frontseat": 79,
+    "carrousel": 80,
+    "casino indoor": 81,
+    "castle": 82,
+    "catacomb": 83,
+    "cathedral indoor": 84,
+    "cathedral outdoor": 85,
+    "cavern indoor": 86,
+    "cemetery": 87,
+    "chalet": 88,
+    "cheese factory": 89,
+    "chemistry lab": 90,
+    "chicken coop indoor": 91,
+    "chicken coop outdoor": 92,
+    "childs room": 93,
+    "church indoor": 94,
+    "church outdoor": 95,
+    "classroom": 96,
+    "clean room": 97,
+    "cliff": 98,
+    "cloister indoor": 99,
+    "closet": 100,
+    "clothing store": 101,
+    "coast": 102,
+    "cockpit": 103,
+    "coffee shop": 104,
+    "computer room": 105,
+    "conference center": 106,
+    "conference room": 107,
+    "construction site": 108,
+    "control room": 109,
+    "control tower outdoor": 110,
+    "corn field": 111,
+    "corral": 112,
+    "corridor": 113,
+    "cottage garden": 114,
+    "courthouse": 115,
+    "courtroom": 116,
+    "courtyard": 117,
+    "covered bridge exterior": 118,
+    "creek": 119,
+    "crevasse": 120,
+    "crosswalk": 121,
+    "cubicle office": 122,
+    "dam": 123,
+    "delicatessen": 124,
+    "dentists office": 125,
+    "desert sand": 126,
+    "desert vegetation": 127,
+    "diner indoor": 128,
+    "diner outdoor": 129,
+    "dinette home": 130,
+    "dinette vehicle": 131,
+    "dining car": 132,
+    "dining room": 133,
+    "discotheque": 134,
+    "dock": 135,
+    "doorway outdoor": 136,
+    "dorm room": 137,
+    "driveway": 138,
+    "driving range outdoor": 139,
+    "drugstore": 140,
+    "electrical substation": 141,
+    "elevator door": 142,
+    "elevator interior": 143,
+    "elevator shaft": 144,
+    "engine room": 145,
+    "escalator indoor": 146,
+    "excavation": 147,
+    "factory indoor": 148,
+    "fairway": 149,
+    "fastfood restaurant": 150,
+    "field cultivated": 151,
+    "field wild": 152,
+    "fire escape": 153,
+    "fire station": 154,
+    "firing range indoor": 155,
+    "fishpond": 156,
+    "florist shop indoor": 157,
+    "food court": 158,
+    "forest broadleaf": 159,
+    "forest needleleaf": 160,
+    "forest path": 161,
+    "forest road": 162,
+    "formal garden": 163,
+    "fountain": 164,
+    "galley": 165,
+    "game room": 166,
+    "garage indoor": 167,
+    "garbage dump": 168,
+    "gas station": 169,
+    "gazebo exterior": 170,
+    "general store indoor": 171,
+    "general store outdoor": 172,
+    "gift shop": 173,
+    "golf course": 174,
+    "greenhouse indoor": 175,
+    "greenhouse outdoor": 176,
+    "gymnasium indoor": 177,
+    "hangar indoor": 178,
+    "hangar outdoor": 179,
+    "harbor": 180,
+    "hayfield": 181,
+    "heliport": 182,
+    "herb garden": 183,
+    "highway": 184,
+    "hill": 185,
+    "home office": 186,
+    "hospital": 187,
+    "hospital room": 188,
+    "hot spring": 189,
+    "hot tub outdoor": 190,
+    "hotel outdoor": 191,
+    "hotel room": 192,
+    "house": 193,
+    "hunting lodge outdoor": 194,
+    "ice cream parlor": 195,
+    "ice floe": 196,
+    "ice shelf": 197,
+    "ice skating rink indoor": 198,
+    "ice skating rink outdoor": 199,
+    "iceberg": 200,
+    "igloo": 201,
+    "industrial area": 202,
+    "inn outdoor": 203,
+    "islet": 204,
+    "jacuzzi indoor": 205,
+    "jail cell": 206,
+    "jail indoor": 207,
+    "jewelry shop": 208,
+    "kasbah": 209,
+    "kennel indoor": 210,
+    "kennel outdoor": 211,
+    "kindergarden classroom": 212,
+    "kitchen": 213,
+    "kitchenette": 214,
+    "labyrinth outdoor": 215,
+    "lake natural": 216,
+    "landfill": 217,
+    "landing deck": 218,
+    "laundromat": 219,
+    "lecture room": 220,
+    "library indoor": 221,
+    "library outdoor": 222,
+    "lido deck outdoor": 223,
+    "lift bridge": 224,
+    "lighthouse": 225,
+    "limousine interior": 226,
+    "living room": 227,
+    "lobby": 228,
+    "lock chamber": 229,
+    "locker room": 230,
+    "mansion": 231,
+    "manufactured home": 232,
+    "market indoor": 233,
+    "market outdoor": 234,
+    "marsh": 235,
+    "martial arts gym": 236,
+    "mausoleum": 237,
+    "medina": 238,
+    "moat water": 239,
+    "monastery outdoor": 240,
+    "mosque indoor": 241,
+    "mosque outdoor": 242,
+    "motel": 243,
+    "mountain": 244,
+    "mountain snowy": 245,
+    "movie theater indoor": 246,
+    "museum indoor": 247,
+    "music store": 248,
+    "music studio": 249,
+    "nuclear power plant outdoor": 250,
+    "nursery": 251,
+    "oast house": 252,
+    "observatory outdoor": 253,
+    "ocean": 254,
+    "office": 255,
+    "office building": 256,
+    "oil refinery outdoor": 257,
+    "oilrig": 258,
+    "operating room": 259,
+    "orchard": 260,
+    "outhouse outdoor": 261,
+    "pagoda": 262,
+    "palace": 263,
+    "pantry": 264,
+    "park": 265,
+    "parking garage indoor": 266,
+    "parking garage outdoor": 267,
+    "parking lot": 268,
+    "parlor": 269,
+    "pasture": 270,
+    "patio": 271,
+    "pavilion": 272,
+    "pharmacy": 273,
+    "phone booth": 274,
+    "physics laboratory": 275,
+    "picnic area": 276,
+    "pilothouse indoor": 277,
+    "planetarium outdoor": 278,
+    "playground": 279,
+    "playroom": 280,
+    "plaza": 281,
+    "podium indoor": 282,
+    "podium outdoor": 283,
+    "pond": 284,
+    "poolroom establishment": 285,
+    "poolroom home": 286,
+    "power plant outdoor": 287,
+    "promenade deck": 288,
+    "pub indoor": 289,
+    "pulpit": 290,
+    "putting green": 291,
+    "racecourse": 292,
+    "raceway": 293,
+    "raft": 294,
+    "railroad track": 295,
+    "rainforest": 296,
+    "reception": 297,
+    "recreation room": 298,
+    "residential neighborhood": 299,
+    "restaurant": 300,
+    "restaurant kitchen": 301,
+    "restaurant patio": 302,
+    "rice paddy": 303,
+    "riding arena": 304,
+    "river": 305,
+    "rock arch": 306,
+    "rope bridge": 307,
+    "ruin": 308,
+    "runway": 309,
+    "sandbar": 310,
+    "sandbox": 311,
+    "sauna": 312,
+    "schoolhouse": 313,
+    "sea cliff": 314,
+    "server room": 315,
+    "shed": 316,
+    "shoe shop": 317,
+    "shopfront": 318,
+    "shopping mall indoor": 319,
+    "shower": 320,
+    "skatepark": 321,
+    "ski lodge": 322,
+    "ski resort": 323,
+    "ski slope": 324,
+    "sky": 325,
+    "skyscraper": 326,
+    "slum": 327,
+    "snowfield": 328,
+    "squash court": 329,
+    "stable": 330,
+    "stadium baseball": 331,
+    "stadium football": 332,
+    "stage indoor": 333,
+    "staircase": 334,
+    "street": 335,
+    "subway interior": 336,
+    "subway station platform": 337,
+    "supermarket": 338,
+    "sushi bar": 339,
+    "swamp": 340,
+    "swimming pool indoor": 341,
+    "swimming pool outdoor": 342,
+    "synagogue indoor": 343,
+    "synagogue outdoor": 344,
+    "television studio": 345,
+    "temple east asia": 346,
+    "temple south asia": 347,
+    "tennis court indoor": 348,
+    "tennis court outdoor": 349,
+    "tent outdoor": 350,
+    "theater indoor procenium": 351,
+    "theater indoor seats": 352,
+    "thriftshop": 353,
+    "throne room": 354,
+    "ticket booth": 355,
+    "toll plaza": 356,
+    "topiary garden": 357,
+    "tower": 358,
+    "toyshop": 359,
+    "track outdoor": 360,
+    "train railway": 361,
+    "train station platform": 362,
+    "tree farm": 363,
+    "tree house": 364,
+    "trench": 365,
+    "underwater coral reef": 366,
+    "utility room": 367,
+    "valley": 368,
+    "van interior": 369,
+    "vegetable garden": 370,
+    "veranda": 371,
+    "veterinarians office": 372,
+    "viaduct": 373,
+    "videostore": 374,
+    "village": 375,
+    "vineyard": 376,
+    "volcano": 377,
+    "volleyball court indoor": 378,
+    "volleyball court outdoor": 379,
+    "waiting room": 380,
+    "warehouse indoor": 381,
+    "water tower": 382,
+    "waterfall block": 383,
+    "waterfall fan": 384,
+    "waterfall plunge": 385,
+    "watering hole": 386,
+    "wave": 387,
+    "wet bar": 388,
+    "wheat field": 389,
+    "wind farm": 390,
+    "windmill": 391,
+    "wine cellar barrel storage": 392,
+    "wine cellar bottle storage": 393,
+    "wrestling ring indoor": 394,
+    "yard": 395,
+    "youth hostel": 396
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-sun397-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet152-sun397-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-sun397-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-sun397-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md b/resnet152-sun397-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..2253b0dad1d7ed6de24c4d2063670d959edee6b0
--- /dev/null
+++ b/resnet152-sun397-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset sun397.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: sun397
+    pretrained: true
+test_datasets: null
+train_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: train
+type: transformers
+val_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: test
+```
+
diff --git a/resnet152-sun397-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/config.json b/resnet152-sun397-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..235472e739b23ead2b88b4266434b8f42502d7ea
--- /dev/null
+++ b/resnet152-sun397-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,837 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "abbey",
+    "1": "airplane cabin",
+    "2": "airport terminal",
+    "3": "alley",
+    "4": "amphitheater",
+    "5": "amusement arcade",
+    "6": "amusement park",
+    "7": "anechoic chamber",
+    "8": "apartment building outdoor",
+    "9": "apse indoor",
+    "10": "aquarium",
+    "11": "aqueduct",
+    "12": "arch",
+    "13": "archive",
+    "14": "arrival gate outdoor",
+    "15": "art gallery",
+    "16": "art school",
+    "17": "art studio",
+    "18": "assembly line",
+    "19": "athletic field outdoor",
+    "20": "atrium public",
+    "21": "attic",
+    "22": "auditorium",
+    "23": "auto factory",
+    "24": "badlands",
+    "25": "badminton court indoor",
+    "26": "baggage claim",
+    "27": "bakery shop",
+    "28": "balcony exterior",
+    "29": "balcony interior",
+    "30": "ball pit",
+    "31": "ballroom",
+    "32": "bamboo forest",
+    "33": "banquet hall",
+    "34": "bar",
+    "35": "barn",
+    "36": "barndoor",
+    "37": "baseball field",
+    "38": "basement",
+    "39": "basilica",
+    "40": "basketball court outdoor",
+    "41": "bathroom",
+    "42": "batters box",
+    "43": "bayou",
+    "44": "bazaar indoor",
+    "45": "bazaar outdoor",
+    "46": "beach",
+    "47": "beauty salon",
+    "48": "bedroom",
+    "49": "berth",
+    "50": "biology laboratory",
+    "51": "bistro indoor",
+    "52": "boardwalk",
+    "53": "boat deck",
+    "54": "boathouse",
+    "55": "bookstore",
+    "56": "booth indoor",
+    "57": "botanical garden",
+    "58": "bow window indoor",
+    "59": "bow window outdoor",
+    "60": "bowling alley",
+    "61": "boxing ring",
+    "62": "brewery indoor",
+    "63": "bridge",
+    "64": "building facade",
+    "65": "bullring",
+    "66": "burial chamber",
+    "67": "bus interior",
+    "68": "butchers shop",
+    "69": "butte",
+    "70": "cabin outdoor",
+    "71": "cafeteria",
+    "72": "campsite",
+    "73": "campus",
+    "74": "canal natural",
+    "75": "canal urban",
+    "76": "candy store",
+    "77": "canyon",
+    "78": "car interior backseat",
+    "79": "car interior frontseat",
+    "80": "carrousel",
+    "81": "casino indoor",
+    "82": "castle",
+    "83": "catacomb",
+    "84": "cathedral indoor",
+    "85": "cathedral outdoor",
+    "86": "cavern indoor",
+    "87": "cemetery",
+    "88": "chalet",
+    "89": "cheese factory",
+    "90": "chemistry lab",
+    "91": "chicken coop indoor",
+    "92": "chicken coop outdoor",
+    "93": "childs room",
+    "94": "church indoor",
+    "95": "church outdoor",
+    "96": "classroom",
+    "97": "clean room",
+    "98": "cliff",
+    "99": "cloister indoor",
+    "100": "closet",
+    "101": "clothing store",
+    "102": "coast",
+    "103": "cockpit",
+    "104": "coffee shop",
+    "105": "computer room",
+    "106": "conference center",
+    "107": "conference room",
+    "108": "construction site",
+    "109": "control room",
+    "110": "control tower outdoor",
+    "111": "corn field",
+    "112": "corral",
+    "113": "corridor",
+    "114": "cottage garden",
+    "115": "courthouse",
+    "116": "courtroom",
+    "117": "courtyard",
+    "118": "covered bridge exterior",
+    "119": "creek",
+    "120": "crevasse",
+    "121": "crosswalk",
+    "122": "cubicle office",
+    "123": "dam",
+    "124": "delicatessen",
+    "125": "dentists office",
+    "126": "desert sand",
+    "127": "desert vegetation",
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+    "129": "diner outdoor",
+    "130": "dinette home",
+    "131": "dinette vehicle",
+    "132": "dining car",
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+    "178": "hangar indoor",
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+    "195": "ice cream parlor",
+    "196": "ice floe",
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+    "198": "ice skating rink indoor",
+    "199": "ice skating rink outdoor",
+    "200": "iceberg",
+    "201": "igloo",
+    "202": "industrial area",
+    "203": "inn outdoor",
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+    "205": "jacuzzi indoor",
+    "206": "jail cell",
+    "207": "jail indoor",
+    "208": "jewelry shop",
+    "209": "kasbah",
+    "210": "kennel indoor",
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+    "212": "kindergarden classroom",
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+    "215": "labyrinth outdoor",
+    "216": "lake natural",
+    "217": "landfill",
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+    "219": "laundromat",
+    "220": "lecture room",
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+    "224": "lift bridge",
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+    "238": "medina",
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+    "240": "monastery outdoor",
+    "241": "mosque indoor",
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+    "244": "mountain",
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+    "250": "nuclear power plant outdoor",
+    "251": "nursery",
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+    "254": "ocean",
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+    "262": "pagoda",
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+    "267": "parking garage outdoor",
+    "268": "parking lot",
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+    "282": "podium indoor",
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+    "284": "pond",
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+    "288": "promenade deck",
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+    "291": "putting green",
+    "292": "racecourse",
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+    "294": "raft",
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+    "303": "rice paddy",
+    "304": "riding arena",
+    "305": "river",
+    "306": "rock arch",
+    "307": "rope bridge",
+    "308": "ruin",
+    "309": "runway",
+    "310": "sandbar",
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+    "312": "sauna",
+    "313": "schoolhouse",
+    "314": "sea cliff",
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+    "329": "squash court",
+    "330": "stable",
+    "331": "stadium baseball",
+    "332": "stadium football",
+    "333": "stage indoor",
+    "334": "staircase",
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+    "343": "synagogue indoor",
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+    "350": "tent outdoor",
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+    "358": "tower",
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+    "361": "train railway",
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+    "365": "trench",
+    "366": "underwater coral reef",
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+    "373": "viaduct",
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+    "376": "vineyard",
+    "377": "volcano",
+    "378": "volleyball court indoor",
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+    "380": "waiting room",
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+    "383": "waterfall block",
+    "384": "waterfall fan",
+    "385": "waterfall plunge",
+    "386": "watering hole",
+    "387": "wave",
+    "388": "wet bar",
+    "389": "wheat field",
+    "390": "wind farm",
+    "391": "windmill",
+    "392": "wine cellar barrel storage",
+    "393": "wine cellar bottle storage",
+    "394": "wrestling ring indoor",
+    "395": "yard",
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+  },
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+    "water tower": 382,
+    "waterfall block": 383,
+    "waterfall fan": 384,
+    "waterfall plunge": 385,
+    "watering hole": 386,
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+    "wheat field": 389,
+    "wind farm": 390,
+    "windmill": 391,
+    "wine cellar barrel storage": 392,
+    "wine cellar bottle storage": 393,
+    "wrestling ring indoor": 394,
+    "yard": 395,
+    "youth hostel": 396
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-sun397-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet152-sun397-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-sun397-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-sun397-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/README.md b/resnet152-sun397-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..491880bd5c13c29628035e496524389b957cd0cc
--- /dev/null
+++ b/resnet152-sun397-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset sun397.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: sun397
+    pretrained: true
+test_datasets: null
+train_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: train
+type: transformers
+val_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: test
+```
+
diff --git a/resnet152-sun397-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/config.json b/resnet152-sun397-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..235472e739b23ead2b88b4266434b8f42502d7ea
--- /dev/null
+++ b/resnet152-sun397-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,837 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "abbey",
+    "1": "airplane cabin",
+    "2": "airport terminal",
+    "3": "alley",
+    "4": "amphitheater",
+    "5": "amusement arcade",
+    "6": "amusement park",
+    "7": "anechoic chamber",
+    "8": "apartment building outdoor",
+    "9": "apse indoor",
+    "10": "aquarium",
+    "11": "aqueduct",
+    "12": "arch",
+    "13": "archive",
+    "14": "arrival gate outdoor",
+    "15": "art gallery",
+    "16": "art school",
+    "17": "art studio",
+    "18": "assembly line",
+    "19": "athletic field outdoor",
+    "20": "atrium public",
+    "21": "attic",
+    "22": "auditorium",
+    "23": "auto factory",
+    "24": "badlands",
+    "25": "badminton court indoor",
+    "26": "baggage claim",
+    "27": "bakery shop",
+    "28": "balcony exterior",
+    "29": "balcony interior",
+    "30": "ball pit",
+    "31": "ballroom",
+    "32": "bamboo forest",
+    "33": "banquet hall",
+    "34": "bar",
+    "35": "barn",
+    "36": "barndoor",
+    "37": "baseball field",
+    "38": "basement",
+    "39": "basilica",
+    "40": "basketball court outdoor",
+    "41": "bathroom",
+    "42": "batters box",
+    "43": "bayou",
+    "44": "bazaar indoor",
+    "45": "bazaar outdoor",
+    "46": "beach",
+    "47": "beauty salon",
+    "48": "bedroom",
+    "49": "berth",
+    "50": "biology laboratory",
+    "51": "bistro indoor",
+    "52": "boardwalk",
+    "53": "boat deck",
+    "54": "boathouse",
+    "55": "bookstore",
+    "56": "booth indoor",
+    "57": "botanical garden",
+    "58": "bow window indoor",
+    "59": "bow window outdoor",
+    "60": "bowling alley",
+    "61": "boxing ring",
+    "62": "brewery indoor",
+    "63": "bridge",
+    "64": "building facade",
+    "65": "bullring",
+    "66": "burial chamber",
+    "67": "bus interior",
+    "68": "butchers shop",
+    "69": "butte",
+    "70": "cabin outdoor",
+    "71": "cafeteria",
+    "72": "campsite",
+    "73": "campus",
+    "74": "canal natural",
+    "75": "canal urban",
+    "76": "candy store",
+    "77": "canyon",
+    "78": "car interior backseat",
+    "79": "car interior frontseat",
+    "80": "carrousel",
+    "81": "casino indoor",
+    "82": "castle",
+    "83": "catacomb",
+    "84": "cathedral indoor",
+    "85": "cathedral outdoor",
+    "86": "cavern indoor",
+    "87": "cemetery",
+    "88": "chalet",
+    "89": "cheese factory",
+    "90": "chemistry lab",
+    "91": "chicken coop indoor",
+    "92": "chicken coop outdoor",
+    "93": "childs room",
+    "94": "church indoor",
+    "95": "church outdoor",
+    "96": "classroom",
+    "97": "clean room",
+    "98": "cliff",
+    "99": "cloister indoor",
+    "100": "closet",
+    "101": "clothing store",
+    "102": "coast",
+    "103": "cockpit",
+    "104": "coffee shop",
+    "105": "computer room",
+    "106": "conference center",
+    "107": "conference room",
+    "108": "construction site",
+    "109": "control room",
+    "110": "control tower outdoor",
+    "111": "corn field",
+    "112": "corral",
+    "113": "corridor",
+    "114": "cottage garden",
+    "115": "courthouse",
+    "116": "courtroom",
+    "117": "courtyard",
+    "118": "covered bridge exterior",
+    "119": "creek",
+    "120": "crevasse",
+    "121": "crosswalk",
+    "122": "cubicle office",
+    "123": "dam",
+    "124": "delicatessen",
+    "125": "dentists office",
+    "126": "desert sand",
+    "127": "desert vegetation",
+    "128": "diner indoor",
+    "129": "diner outdoor",
+    "130": "dinette home",
+    "131": "dinette vehicle",
+    "132": "dining car",
+    "133": "dining room",
+    "134": "discotheque",
+    "135": "dock",
+    "136": "doorway outdoor",
+    "137": "dorm room",
+    "138": "driveway",
+    "139": "driving range outdoor",
+    "140": "drugstore",
+    "141": "electrical substation",
+    "142": "elevator door",
+    "143": "elevator interior",
+    "144": "elevator shaft",
+    "145": "engine room",
+    "146": "escalator indoor",
+    "147": "excavation",
+    "148": "factory indoor",
+    "149": "fairway",
+    "150": "fastfood restaurant",
+    "151": "field cultivated",
+    "152": "field wild",
+    "153": "fire escape",
+    "154": "fire station",
+    "155": "firing range indoor",
+    "156": "fishpond",
+    "157": "florist shop indoor",
+    "158": "food court",
+    "159": "forest broadleaf",
+    "160": "forest needleleaf",
+    "161": "forest path",
+    "162": "forest road",
+    "163": "formal garden",
+    "164": "fountain",
+    "165": "galley",
+    "166": "game room",
+    "167": "garage indoor",
+    "168": "garbage dump",
+    "169": "gas station",
+    "170": "gazebo exterior",
+    "171": "general store indoor",
+    "172": "general store outdoor",
+    "173": "gift shop",
+    "174": "golf course",
+    "175": "greenhouse indoor",
+    "176": "greenhouse outdoor",
+    "177": "gymnasium indoor",
+    "178": "hangar indoor",
+    "179": "hangar outdoor",
+    "180": "harbor",
+    "181": "hayfield",
+    "182": "heliport",
+    "183": "herb garden",
+    "184": "highway",
+    "185": "hill",
+    "186": "home office",
+    "187": "hospital",
+    "188": "hospital room",
+    "189": "hot spring",
+    "190": "hot tub outdoor",
+    "191": "hotel outdoor",
+    "192": "hotel room",
+    "193": "house",
+    "194": "hunting lodge outdoor",
+    "195": "ice cream parlor",
+    "196": "ice floe",
+    "197": "ice shelf",
+    "198": "ice skating rink indoor",
+    "199": "ice skating rink outdoor",
+    "200": "iceberg",
+    "201": "igloo",
+    "202": "industrial area",
+    "203": "inn outdoor",
+    "204": "islet",
+    "205": "jacuzzi indoor",
+    "206": "jail cell",
+    "207": "jail indoor",
+    "208": "jewelry shop",
+    "209": "kasbah",
+    "210": "kennel indoor",
+    "211": "kennel outdoor",
+    "212": "kindergarden classroom",
+    "213": "kitchen",
+    "214": "kitchenette",
+    "215": "labyrinth outdoor",
+    "216": "lake natural",
+    "217": "landfill",
+    "218": "landing deck",
+    "219": "laundromat",
+    "220": "lecture room",
+    "221": "library indoor",
+    "222": "library outdoor",
+    "223": "lido deck outdoor",
+    "224": "lift bridge",
+    "225": "lighthouse",
+    "226": "limousine interior",
+    "227": "living room",
+    "228": "lobby",
+    "229": "lock chamber",
+    "230": "locker room",
+    "231": "mansion",
+    "232": "manufactured home",
+    "233": "market indoor",
+    "234": "market outdoor",
+    "235": "marsh",
+    "236": "martial arts gym",
+    "237": "mausoleum",
+    "238": "medina",
+    "239": "moat water",
+    "240": "monastery outdoor",
+    "241": "mosque indoor",
+    "242": "mosque outdoor",
+    "243": "motel",
+    "244": "mountain",
+    "245": "mountain snowy",
+    "246": "movie theater indoor",
+    "247": "museum indoor",
+    "248": "music store",
+    "249": "music studio",
+    "250": "nuclear power plant outdoor",
+    "251": "nursery",
+    "252": "oast house",
+    "253": "observatory outdoor",
+    "254": "ocean",
+    "255": "office",
+    "256": "office building",
+    "257": "oil refinery outdoor",
+    "258": "oilrig",
+    "259": "operating room",
+    "260": "orchard",
+    "261": "outhouse outdoor",
+    "262": "pagoda",
+    "263": "palace",
+    "264": "pantry",
+    "265": "park",
+    "266": "parking garage indoor",
+    "267": "parking garage outdoor",
+    "268": "parking lot",
+    "269": "parlor",
+    "270": "pasture",
+    "271": "patio",
+    "272": "pavilion",
+    "273": "pharmacy",
+    "274": "phone booth",
+    "275": "physics laboratory",
+    "276": "picnic area",
+    "277": "pilothouse indoor",
+    "278": "planetarium outdoor",
+    "279": "playground",
+    "280": "playroom",
+    "281": "plaza",
+    "282": "podium indoor",
+    "283": "podium outdoor",
+    "284": "pond",
+    "285": "poolroom establishment",
+    "286": "poolroom home",
+    "287": "power plant outdoor",
+    "288": "promenade deck",
+    "289": "pub indoor",
+    "290": "pulpit",
+    "291": "putting green",
+    "292": "racecourse",
+    "293": "raceway",
+    "294": "raft",
+    "295": "railroad track",
+    "296": "rainforest",
+    "297": "reception",
+    "298": "recreation room",
+    "299": "residential neighborhood",
+    "300": "restaurant",
+    "301": "restaurant kitchen",
+    "302": "restaurant patio",
+    "303": "rice paddy",
+    "304": "riding arena",
+    "305": "river",
+    "306": "rock arch",
+    "307": "rope bridge",
+    "308": "ruin",
+    "309": "runway",
+    "310": "sandbar",
+    "311": "sandbox",
+    "312": "sauna",
+    "313": "schoolhouse",
+    "314": "sea cliff",
+    "315": "server room",
+    "316": "shed",
+    "317": "shoe shop",
+    "318": "shopfront",
+    "319": "shopping mall indoor",
+    "320": "shower",
+    "321": "skatepark",
+    "322": "ski lodge",
+    "323": "ski resort",
+    "324": "ski slope",
+    "325": "sky",
+    "326": "skyscraper",
+    "327": "slum",
+    "328": "snowfield",
+    "329": "squash court",
+    "330": "stable",
+    "331": "stadium baseball",
+    "332": "stadium football",
+    "333": "stage indoor",
+    "334": "staircase",
+    "335": "street",
+    "336": "subway interior",
+    "337": "subway station platform",
+    "338": "supermarket",
+    "339": "sushi bar",
+    "340": "swamp",
+    "341": "swimming pool indoor",
+    "342": "swimming pool outdoor",
+    "343": "synagogue indoor",
+    "344": "synagogue outdoor",
+    "345": "television studio",
+    "346": "temple east asia",
+    "347": "temple south asia",
+    "348": "tennis court indoor",
+    "349": "tennis court outdoor",
+    "350": "tent outdoor",
+    "351": "theater indoor procenium",
+    "352": "theater indoor seats",
+    "353": "thriftshop",
+    "354": "throne room",
+    "355": "ticket booth",
+    "356": "toll plaza",
+    "357": "topiary garden",
+    "358": "tower",
+    "359": "toyshop",
+    "360": "track outdoor",
+    "361": "train railway",
+    "362": "train station platform",
+    "363": "tree farm",
+    "364": "tree house",
+    "365": "trench",
+    "366": "underwater coral reef",
+    "367": "utility room",
+    "368": "valley",
+    "369": "van interior",
+    "370": "vegetable garden",
+    "371": "veranda",
+    "372": "veterinarians office",
+    "373": "viaduct",
+    "374": "videostore",
+    "375": "village",
+    "376": "vineyard",
+    "377": "volcano",
+    "378": "volleyball court indoor",
+    "379": "volleyball court outdoor",
+    "380": "waiting room",
+    "381": "warehouse indoor",
+    "382": "water tower",
+    "383": "waterfall block",
+    "384": "waterfall fan",
+    "385": "waterfall plunge",
+    "386": "watering hole",
+    "387": "wave",
+    "388": "wet bar",
+    "389": "wheat field",
+    "390": "wind farm",
+    "391": "windmill",
+    "392": "wine cellar barrel storage",
+    "393": "wine cellar bottle storage",
+    "394": "wrestling ring indoor",
+    "395": "yard",
+    "396": "youth hostel"
+  },
+  "label2id": {
+    "abbey": 0,
+    "airplane cabin": 1,
+    "airport terminal": 2,
+    "alley": 3,
+    "amphitheater": 4,
+    "amusement arcade": 5,
+    "amusement park": 6,
+    "anechoic chamber": 7,
+    "apartment building outdoor": 8,
+    "apse indoor": 9,
+    "aquarium": 10,
+    "aqueduct": 11,
+    "arch": 12,
+    "archive": 13,
+    "arrival gate outdoor": 14,
+    "art gallery": 15,
+    "art school": 16,
+    "art studio": 17,
+    "assembly line": 18,
+    "athletic field outdoor": 19,
+    "atrium public": 20,
+    "attic": 21,
+    "auditorium": 22,
+    "auto factory": 23,
+    "badlands": 24,
+    "badminton court indoor": 25,
+    "baggage claim": 26,
+    "bakery shop": 27,
+    "balcony exterior": 28,
+    "balcony interior": 29,
+    "ball pit": 30,
+    "ballroom": 31,
+    "bamboo forest": 32,
+    "banquet hall": 33,
+    "bar": 34,
+    "barn": 35,
+    "barndoor": 36,
+    "baseball field": 37,
+    "basement": 38,
+    "basilica": 39,
+    "basketball court outdoor": 40,
+    "bathroom": 41,
+    "batters box": 42,
+    "bayou": 43,
+    "bazaar indoor": 44,
+    "bazaar outdoor": 45,
+    "beach": 46,
+    "beauty salon": 47,
+    "bedroom": 48,
+    "berth": 49,
+    "biology laboratory": 50,
+    "bistro indoor": 51,
+    "boardwalk": 52,
+    "boat deck": 53,
+    "boathouse": 54,
+    "bookstore": 55,
+    "booth indoor": 56,
+    "botanical garden": 57,
+    "bow window indoor": 58,
+    "bow window outdoor": 59,
+    "bowling alley": 60,
+    "boxing ring": 61,
+    "brewery indoor": 62,
+    "bridge": 63,
+    "building facade": 64,
+    "bullring": 65,
+    "burial chamber": 66,
+    "bus interior": 67,
+    "butchers shop": 68,
+    "butte": 69,
+    "cabin outdoor": 70,
+    "cafeteria": 71,
+    "campsite": 72,
+    "campus": 73,
+    "canal natural": 74,
+    "canal urban": 75,
+    "candy store": 76,
+    "canyon": 77,
+    "car interior backseat": 78,
+    "car interior frontseat": 79,
+    "carrousel": 80,
+    "casino indoor": 81,
+    "castle": 82,
+    "catacomb": 83,
+    "cathedral indoor": 84,
+    "cathedral outdoor": 85,
+    "cavern indoor": 86,
+    "cemetery": 87,
+    "chalet": 88,
+    "cheese factory": 89,
+    "chemistry lab": 90,
+    "chicken coop indoor": 91,
+    "chicken coop outdoor": 92,
+    "childs room": 93,
+    "church indoor": 94,
+    "church outdoor": 95,
+    "classroom": 96,
+    "clean room": 97,
+    "cliff": 98,
+    "cloister indoor": 99,
+    "closet": 100,
+    "clothing store": 101,
+    "coast": 102,
+    "cockpit": 103,
+    "coffee shop": 104,
+    "computer room": 105,
+    "conference center": 106,
+    "conference room": 107,
+    "construction site": 108,
+    "control room": 109,
+    "control tower outdoor": 110,
+    "corn field": 111,
+    "corral": 112,
+    "corridor": 113,
+    "cottage garden": 114,
+    "courthouse": 115,
+    "courtroom": 116,
+    "courtyard": 117,
+    "covered bridge exterior": 118,
+    "creek": 119,
+    "crevasse": 120,
+    "crosswalk": 121,
+    "cubicle office": 122,
+    "dam": 123,
+    "delicatessen": 124,
+    "dentists office": 125,
+    "desert sand": 126,
+    "desert vegetation": 127,
+    "diner indoor": 128,
+    "diner outdoor": 129,
+    "dinette home": 130,
+    "dinette vehicle": 131,
+    "dining car": 132,
+    "dining room": 133,
+    "discotheque": 134,
+    "dock": 135,
+    "doorway outdoor": 136,
+    "dorm room": 137,
+    "driveway": 138,
+    "driving range outdoor": 139,
+    "drugstore": 140,
+    "electrical substation": 141,
+    "elevator door": 142,
+    "elevator interior": 143,
+    "elevator shaft": 144,
+    "engine room": 145,
+    "escalator indoor": 146,
+    "excavation": 147,
+    "factory indoor": 148,
+    "fairway": 149,
+    "fastfood restaurant": 150,
+    "field cultivated": 151,
+    "field wild": 152,
+    "fire escape": 153,
+    "fire station": 154,
+    "firing range indoor": 155,
+    "fishpond": 156,
+    "florist shop indoor": 157,
+    "food court": 158,
+    "forest broadleaf": 159,
+    "forest needleleaf": 160,
+    "forest path": 161,
+    "forest road": 162,
+    "formal garden": 163,
+    "fountain": 164,
+    "galley": 165,
+    "game room": 166,
+    "garage indoor": 167,
+    "garbage dump": 168,
+    "gas station": 169,
+    "gazebo exterior": 170,
+    "general store indoor": 171,
+    "general store outdoor": 172,
+    "gift shop": 173,
+    "golf course": 174,
+    "greenhouse indoor": 175,
+    "greenhouse outdoor": 176,
+    "gymnasium indoor": 177,
+    "hangar indoor": 178,
+    "hangar outdoor": 179,
+    "harbor": 180,
+    "hayfield": 181,
+    "heliport": 182,
+    "herb garden": 183,
+    "highway": 184,
+    "hill": 185,
+    "home office": 186,
+    "hospital": 187,
+    "hospital room": 188,
+    "hot spring": 189,
+    "hot tub outdoor": 190,
+    "hotel outdoor": 191,
+    "hotel room": 192,
+    "house": 193,
+    "hunting lodge outdoor": 194,
+    "ice cream parlor": 195,
+    "ice floe": 196,
+    "ice shelf": 197,
+    "ice skating rink indoor": 198,
+    "ice skating rink outdoor": 199,
+    "iceberg": 200,
+    "igloo": 201,
+    "industrial area": 202,
+    "inn outdoor": 203,
+    "islet": 204,
+    "jacuzzi indoor": 205,
+    "jail cell": 206,
+    "jail indoor": 207,
+    "jewelry shop": 208,
+    "kasbah": 209,
+    "kennel indoor": 210,
+    "kennel outdoor": 211,
+    "kindergarden classroom": 212,
+    "kitchen": 213,
+    "kitchenette": 214,
+    "labyrinth outdoor": 215,
+    "lake natural": 216,
+    "landfill": 217,
+    "landing deck": 218,
+    "laundromat": 219,
+    "lecture room": 220,
+    "library indoor": 221,
+    "library outdoor": 222,
+    "lido deck outdoor": 223,
+    "lift bridge": 224,
+    "lighthouse": 225,
+    "limousine interior": 226,
+    "living room": 227,
+    "lobby": 228,
+    "lock chamber": 229,
+    "locker room": 230,
+    "mansion": 231,
+    "manufactured home": 232,
+    "market indoor": 233,
+    "market outdoor": 234,
+    "marsh": 235,
+    "martial arts gym": 236,
+    "mausoleum": 237,
+    "medina": 238,
+    "moat water": 239,
+    "monastery outdoor": 240,
+    "mosque indoor": 241,
+    "mosque outdoor": 242,
+    "motel": 243,
+    "mountain": 244,
+    "mountain snowy": 245,
+    "movie theater indoor": 246,
+    "museum indoor": 247,
+    "music store": 248,
+    "music studio": 249,
+    "nuclear power plant outdoor": 250,
+    "nursery": 251,
+    "oast house": 252,
+    "observatory outdoor": 253,
+    "ocean": 254,
+    "office": 255,
+    "office building": 256,
+    "oil refinery outdoor": 257,
+    "oilrig": 258,
+    "operating room": 259,
+    "orchard": 260,
+    "outhouse outdoor": 261,
+    "pagoda": 262,
+    "palace": 263,
+    "pantry": 264,
+    "park": 265,
+    "parking garage indoor": 266,
+    "parking garage outdoor": 267,
+    "parking lot": 268,
+    "parlor": 269,
+    "pasture": 270,
+    "patio": 271,
+    "pavilion": 272,
+    "pharmacy": 273,
+    "phone booth": 274,
+    "physics laboratory": 275,
+    "picnic area": 276,
+    "pilothouse indoor": 277,
+    "planetarium outdoor": 278,
+    "playground": 279,
+    "playroom": 280,
+    "plaza": 281,
+    "podium indoor": 282,
+    "podium outdoor": 283,
+    "pond": 284,
+    "poolroom establishment": 285,
+    "poolroom home": 286,
+    "power plant outdoor": 287,
+    "promenade deck": 288,
+    "pub indoor": 289,
+    "pulpit": 290,
+    "putting green": 291,
+    "racecourse": 292,
+    "raceway": 293,
+    "raft": 294,
+    "railroad track": 295,
+    "rainforest": 296,
+    "reception": 297,
+    "recreation room": 298,
+    "residential neighborhood": 299,
+    "restaurant": 300,
+    "restaurant kitchen": 301,
+    "restaurant patio": 302,
+    "rice paddy": 303,
+    "riding arena": 304,
+    "river": 305,
+    "rock arch": 306,
+    "rope bridge": 307,
+    "ruin": 308,
+    "runway": 309,
+    "sandbar": 310,
+    "sandbox": 311,
+    "sauna": 312,
+    "schoolhouse": 313,
+    "sea cliff": 314,
+    "server room": 315,
+    "shed": 316,
+    "shoe shop": 317,
+    "shopfront": 318,
+    "shopping mall indoor": 319,
+    "shower": 320,
+    "skatepark": 321,
+    "ski lodge": 322,
+    "ski resort": 323,
+    "ski slope": 324,
+    "sky": 325,
+    "skyscraper": 326,
+    "slum": 327,
+    "snowfield": 328,
+    "squash court": 329,
+    "stable": 330,
+    "stadium baseball": 331,
+    "stadium football": 332,
+    "stage indoor": 333,
+    "staircase": 334,
+    "street": 335,
+    "subway interior": 336,
+    "subway station platform": 337,
+    "supermarket": 338,
+    "sushi bar": 339,
+    "swamp": 340,
+    "swimming pool indoor": 341,
+    "swimming pool outdoor": 342,
+    "synagogue indoor": 343,
+    "synagogue outdoor": 344,
+    "television studio": 345,
+    "temple east asia": 346,
+    "temple south asia": 347,
+    "tennis court indoor": 348,
+    "tennis court outdoor": 349,
+    "tent outdoor": 350,
+    "theater indoor procenium": 351,
+    "theater indoor seats": 352,
+    "thriftshop": 353,
+    "throne room": 354,
+    "ticket booth": 355,
+    "toll plaza": 356,
+    "topiary garden": 357,
+    "tower": 358,
+    "toyshop": 359,
+    "track outdoor": 360,
+    "train railway": 361,
+    "train station platform": 362,
+    "tree farm": 363,
+    "tree house": 364,
+    "trench": 365,
+    "underwater coral reef": 366,
+    "utility room": 367,
+    "valley": 368,
+    "van interior": 369,
+    "vegetable garden": 370,
+    "veranda": 371,
+    "veterinarians office": 372,
+    "viaduct": 373,
+    "videostore": 374,
+    "village": 375,
+    "vineyard": 376,
+    "volcano": 377,
+    "volleyball court indoor": 378,
+    "volleyball court outdoor": 379,
+    "waiting room": 380,
+    "warehouse indoor": 381,
+    "water tower": 382,
+    "waterfall block": 383,
+    "waterfall fan": 384,
+    "waterfall plunge": 385,
+    "watering hole": 386,
+    "wave": 387,
+    "wet bar": 388,
+    "wheat field": 389,
+    "wind farm": 390,
+    "windmill": 391,
+    "wine cellar barrel storage": 392,
+    "wine cellar bottle storage": 393,
+    "wrestling ring indoor": 394,
+    "yard": 395,
+    "youth hostel": 396
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-sun397-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet152-sun397-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-sun397-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-sun397-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/README.md b/resnet152-sun397-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..6e6a5a02e7be52a00265850bbcca83befbd6e358
--- /dev/null
+++ b/resnet152-sun397-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset sun397.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: sun397
+    pretrained: true
+test_datasets: null
+train_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: train
+type: transformers
+val_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: test
+```
+
diff --git a/resnet152-sun397-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/config.json b/resnet152-sun397-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..235472e739b23ead2b88b4266434b8f42502d7ea
--- /dev/null
+++ b/resnet152-sun397-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/config.json
@@ -0,0 +1,837 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "abbey",
+    "1": "airplane cabin",
+    "2": "airport terminal",
+    "3": "alley",
+    "4": "amphitheater",
+    "5": "amusement arcade",
+    "6": "amusement park",
+    "7": "anechoic chamber",
+    "8": "apartment building outdoor",
+    "9": "apse indoor",
+    "10": "aquarium",
+    "11": "aqueduct",
+    "12": "arch",
+    "13": "archive",
+    "14": "arrival gate outdoor",
+    "15": "art gallery",
+    "16": "art school",
+    "17": "art studio",
+    "18": "assembly line",
+    "19": "athletic field outdoor",
+    "20": "atrium public",
+    "21": "attic",
+    "22": "auditorium",
+    "23": "auto factory",
+    "24": "badlands",
+    "25": "badminton court indoor",
+    "26": "baggage claim",
+    "27": "bakery shop",
+    "28": "balcony exterior",
+    "29": "balcony interior",
+    "30": "ball pit",
+    "31": "ballroom",
+    "32": "bamboo forest",
+    "33": "banquet hall",
+    "34": "bar",
+    "35": "barn",
+    "36": "barndoor",
+    "37": "baseball field",
+    "38": "basement",
+    "39": "basilica",
+    "40": "basketball court outdoor",
+    "41": "bathroom",
+    "42": "batters box",
+    "43": "bayou",
+    "44": "bazaar indoor",
+    "45": "bazaar outdoor",
+    "46": "beach",
+    "47": "beauty salon",
+    "48": "bedroom",
+    "49": "berth",
+    "50": "biology laboratory",
+    "51": "bistro indoor",
+    "52": "boardwalk",
+    "53": "boat deck",
+    "54": "boathouse",
+    "55": "bookstore",
+    "56": "booth indoor",
+    "57": "botanical garden",
+    "58": "bow window indoor",
+    "59": "bow window outdoor",
+    "60": "bowling alley",
+    "61": "boxing ring",
+    "62": "brewery indoor",
+    "63": "bridge",
+    "64": "building facade",
+    "65": "bullring",
+    "66": "burial chamber",
+    "67": "bus interior",
+    "68": "butchers shop",
+    "69": "butte",
+    "70": "cabin outdoor",
+    "71": "cafeteria",
+    "72": "campsite",
+    "73": "campus",
+    "74": "canal natural",
+    "75": "canal urban",
+    "76": "candy store",
+    "77": "canyon",
+    "78": "car interior backseat",
+    "79": "car interior frontseat",
+    "80": "carrousel",
+    "81": "casino indoor",
+    "82": "castle",
+    "83": "catacomb",
+    "84": "cathedral indoor",
+    "85": "cathedral outdoor",
+    "86": "cavern indoor",
+    "87": "cemetery",
+    "88": "chalet",
+    "89": "cheese factory",
+    "90": "chemistry lab",
+    "91": "chicken coop indoor",
+    "92": "chicken coop outdoor",
+    "93": "childs room",
+    "94": "church indoor",
+    "95": "church outdoor",
+    "96": "classroom",
+    "97": "clean room",
+    "98": "cliff",
+    "99": "cloister indoor",
+    "100": "closet",
+    "101": "clothing store",
+    "102": "coast",
+    "103": "cockpit",
+    "104": "coffee shop",
+    "105": "computer room",
+    "106": "conference center",
+    "107": "conference room",
+    "108": "construction site",
+    "109": "control room",
+    "110": "control tower outdoor",
+    "111": "corn field",
+    "112": "corral",
+    "113": "corridor",
+    "114": "cottage garden",
+    "115": "courthouse",
+    "116": "courtroom",
+    "117": "courtyard",
+    "118": "covered bridge exterior",
+    "119": "creek",
+    "120": "crevasse",
+    "121": "crosswalk",
+    "122": "cubicle office",
+    "123": "dam",
+    "124": "delicatessen",
+    "125": "dentists office",
+    "126": "desert sand",
+    "127": "desert vegetation",
+    "128": "diner indoor",
+    "129": "diner outdoor",
+    "130": "dinette home",
+    "131": "dinette vehicle",
+    "132": "dining car",
+    "133": "dining room",
+    "134": "discotheque",
+    "135": "dock",
+    "136": "doorway outdoor",
+    "137": "dorm room",
+    "138": "driveway",
+    "139": "driving range outdoor",
+    "140": "drugstore",
+    "141": "electrical substation",
+    "142": "elevator door",
+    "143": "elevator interior",
+    "144": "elevator shaft",
+    "145": "engine room",
+    "146": "escalator indoor",
+    "147": "excavation",
+    "148": "factory indoor",
+    "149": "fairway",
+    "150": "fastfood restaurant",
+    "151": "field cultivated",
+    "152": "field wild",
+    "153": "fire escape",
+    "154": "fire station",
+    "155": "firing range indoor",
+    "156": "fishpond",
+    "157": "florist shop indoor",
+    "158": "food court",
+    "159": "forest broadleaf",
+    "160": "forest needleleaf",
+    "161": "forest path",
+    "162": "forest road",
+    "163": "formal garden",
+    "164": "fountain",
+    "165": "galley",
+    "166": "game room",
+    "167": "garage indoor",
+    "168": "garbage dump",
+    "169": "gas station",
+    "170": "gazebo exterior",
+    "171": "general store indoor",
+    "172": "general store outdoor",
+    "173": "gift shop",
+    "174": "golf course",
+    "175": "greenhouse indoor",
+    "176": "greenhouse outdoor",
+    "177": "gymnasium indoor",
+    "178": "hangar indoor",
+    "179": "hangar outdoor",
+    "180": "harbor",
+    "181": "hayfield",
+    "182": "heliport",
+    "183": "herb garden",
+    "184": "highway",
+    "185": "hill",
+    "186": "home office",
+    "187": "hospital",
+    "188": "hospital room",
+    "189": "hot spring",
+    "190": "hot tub outdoor",
+    "191": "hotel outdoor",
+    "192": "hotel room",
+    "193": "house",
+    "194": "hunting lodge outdoor",
+    "195": "ice cream parlor",
+    "196": "ice floe",
+    "197": "ice shelf",
+    "198": "ice skating rink indoor",
+    "199": "ice skating rink outdoor",
+    "200": "iceberg",
+    "201": "igloo",
+    "202": "industrial area",
+    "203": "inn outdoor",
+    "204": "islet",
+    "205": "jacuzzi indoor",
+    "206": "jail cell",
+    "207": "jail indoor",
+    "208": "jewelry shop",
+    "209": "kasbah",
+    "210": "kennel indoor",
+    "211": "kennel outdoor",
+    "212": "kindergarden classroom",
+    "213": "kitchen",
+    "214": "kitchenette",
+    "215": "labyrinth outdoor",
+    "216": "lake natural",
+    "217": "landfill",
+    "218": "landing deck",
+    "219": "laundromat",
+    "220": "lecture room",
+    "221": "library indoor",
+    "222": "library outdoor",
+    "223": "lido deck outdoor",
+    "224": "lift bridge",
+    "225": "lighthouse",
+    "226": "limousine interior",
+    "227": "living room",
+    "228": "lobby",
+    "229": "lock chamber",
+    "230": "locker room",
+    "231": "mansion",
+    "232": "manufactured home",
+    "233": "market indoor",
+    "234": "market outdoor",
+    "235": "marsh",
+    "236": "martial arts gym",
+    "237": "mausoleum",
+    "238": "medina",
+    "239": "moat water",
+    "240": "monastery outdoor",
+    "241": "mosque indoor",
+    "242": "mosque outdoor",
+    "243": "motel",
+    "244": "mountain",
+    "245": "mountain snowy",
+    "246": "movie theater indoor",
+    "247": "museum indoor",
+    "248": "music store",
+    "249": "music studio",
+    "250": "nuclear power plant outdoor",
+    "251": "nursery",
+    "252": "oast house",
+    "253": "observatory outdoor",
+    "254": "ocean",
+    "255": "office",
+    "256": "office building",
+    "257": "oil refinery outdoor",
+    "258": "oilrig",
+    "259": "operating room",
+    "260": "orchard",
+    "261": "outhouse outdoor",
+    "262": "pagoda",
+    "263": "palace",
+    "264": "pantry",
+    "265": "park",
+    "266": "parking garage indoor",
+    "267": "parking garage outdoor",
+    "268": "parking lot",
+    "269": "parlor",
+    "270": "pasture",
+    "271": "patio",
+    "272": "pavilion",
+    "273": "pharmacy",
+    "274": "phone booth",
+    "275": "physics laboratory",
+    "276": "picnic area",
+    "277": "pilothouse indoor",
+    "278": "planetarium outdoor",
+    "279": "playground",
+    "280": "playroom",
+    "281": "plaza",
+    "282": "podium indoor",
+    "283": "podium outdoor",
+    "284": "pond",
+    "285": "poolroom establishment",
+    "286": "poolroom home",
+    "287": "power plant outdoor",
+    "288": "promenade deck",
+    "289": "pub indoor",
+    "290": "pulpit",
+    "291": "putting green",
+    "292": "racecourse",
+    "293": "raceway",
+    "294": "raft",
+    "295": "railroad track",
+    "296": "rainforest",
+    "297": "reception",
+    "298": "recreation room",
+    "299": "residential neighborhood",
+    "300": "restaurant",
+    "301": "restaurant kitchen",
+    "302": "restaurant patio",
+    "303": "rice paddy",
+    "304": "riding arena",
+    "305": "river",
+    "306": "rock arch",
+    "307": "rope bridge",
+    "308": "ruin",
+    "309": "runway",
+    "310": "sandbar",
+    "311": "sandbox",
+    "312": "sauna",
+    "313": "schoolhouse",
+    "314": "sea cliff",
+    "315": "server room",
+    "316": "shed",
+    "317": "shoe shop",
+    "318": "shopfront",
+    "319": "shopping mall indoor",
+    "320": "shower",
+    "321": "skatepark",
+    "322": "ski lodge",
+    "323": "ski resort",
+    "324": "ski slope",
+    "325": "sky",
+    "326": "skyscraper",
+    "327": "slum",
+    "328": "snowfield",
+    "329": "squash court",
+    "330": "stable",
+    "331": "stadium baseball",
+    "332": "stadium football",
+    "333": "stage indoor",
+    "334": "staircase",
+    "335": "street",
+    "336": "subway interior",
+    "337": "subway station platform",
+    "338": "supermarket",
+    "339": "sushi bar",
+    "340": "swamp",
+    "341": "swimming pool indoor",
+    "342": "swimming pool outdoor",
+    "343": "synagogue indoor",
+    "344": "synagogue outdoor",
+    "345": "television studio",
+    "346": "temple east asia",
+    "347": "temple south asia",
+    "348": "tennis court indoor",
+    "349": "tennis court outdoor",
+    "350": "tent outdoor",
+    "351": "theater indoor procenium",
+    "352": "theater indoor seats",
+    "353": "thriftshop",
+    "354": "throne room",
+    "355": "ticket booth",
+    "356": "toll plaza",
+    "357": "topiary garden",
+    "358": "tower",
+    "359": "toyshop",
+    "360": "track outdoor",
+    "361": "train railway",
+    "362": "train station platform",
+    "363": "tree farm",
+    "364": "tree house",
+    "365": "trench",
+    "366": "underwater coral reef",
+    "367": "utility room",
+    "368": "valley",
+    "369": "van interior",
+    "370": "vegetable garden",
+    "371": "veranda",
+    "372": "veterinarians office",
+    "373": "viaduct",
+    "374": "videostore",
+    "375": "village",
+    "376": "vineyard",
+    "377": "volcano",
+    "378": "volleyball court indoor",
+    "379": "volleyball court outdoor",
+    "380": "waiting room",
+    "381": "warehouse indoor",
+    "382": "water tower",
+    "383": "waterfall block",
+    "384": "waterfall fan",
+    "385": "waterfall plunge",
+    "386": "watering hole",
+    "387": "wave",
+    "388": "wet bar",
+    "389": "wheat field",
+    "390": "wind farm",
+    "391": "windmill",
+    "392": "wine cellar barrel storage",
+    "393": "wine cellar bottle storage",
+    "394": "wrestling ring indoor",
+    "395": "yard",
+    "396": "youth hostel"
+  },
+  "label2id": {
+    "abbey": 0,
+    "airplane cabin": 1,
+    "airport terminal": 2,
+    "alley": 3,
+    "amphitheater": 4,
+    "amusement arcade": 5,
+    "amusement park": 6,
+    "anechoic chamber": 7,
+    "apartment building outdoor": 8,
+    "apse indoor": 9,
+    "aquarium": 10,
+    "aqueduct": 11,
+    "arch": 12,
+    "archive": 13,
+    "arrival gate outdoor": 14,
+    "art gallery": 15,
+    "art school": 16,
+    "art studio": 17,
+    "assembly line": 18,
+    "athletic field outdoor": 19,
+    "atrium public": 20,
+    "attic": 21,
+    "auditorium": 22,
+    "auto factory": 23,
+    "badlands": 24,
+    "badminton court indoor": 25,
+    "baggage claim": 26,
+    "bakery shop": 27,
+    "balcony exterior": 28,
+    "balcony interior": 29,
+    "ball pit": 30,
+    "ballroom": 31,
+    "bamboo forest": 32,
+    "banquet hall": 33,
+    "bar": 34,
+    "barn": 35,
+    "barndoor": 36,
+    "baseball field": 37,
+    "basement": 38,
+    "basilica": 39,
+    "basketball court outdoor": 40,
+    "bathroom": 41,
+    "batters box": 42,
+    "bayou": 43,
+    "bazaar indoor": 44,
+    "bazaar outdoor": 45,
+    "beach": 46,
+    "beauty salon": 47,
+    "bedroom": 48,
+    "berth": 49,
+    "biology laboratory": 50,
+    "bistro indoor": 51,
+    "boardwalk": 52,
+    "boat deck": 53,
+    "boathouse": 54,
+    "bookstore": 55,
+    "booth indoor": 56,
+    "botanical garden": 57,
+    "bow window indoor": 58,
+    "bow window outdoor": 59,
+    "bowling alley": 60,
+    "boxing ring": 61,
+    "brewery indoor": 62,
+    "bridge": 63,
+    "building facade": 64,
+    "bullring": 65,
+    "burial chamber": 66,
+    "bus interior": 67,
+    "butchers shop": 68,
+    "butte": 69,
+    "cabin outdoor": 70,
+    "cafeteria": 71,
+    "campsite": 72,
+    "campus": 73,
+    "canal natural": 74,
+    "canal urban": 75,
+    "candy store": 76,
+    "canyon": 77,
+    "car interior backseat": 78,
+    "car interior frontseat": 79,
+    "carrousel": 80,
+    "casino indoor": 81,
+    "castle": 82,
+    "catacomb": 83,
+    "cathedral indoor": 84,
+    "cathedral outdoor": 85,
+    "cavern indoor": 86,
+    "cemetery": 87,
+    "chalet": 88,
+    "cheese factory": 89,
+    "chemistry lab": 90,
+    "chicken coop indoor": 91,
+    "chicken coop outdoor": 92,
+    "childs room": 93,
+    "church indoor": 94,
+    "church outdoor": 95,
+    "classroom": 96,
+    "clean room": 97,
+    "cliff": 98,
+    "cloister indoor": 99,
+    "closet": 100,
+    "clothing store": 101,
+    "coast": 102,
+    "cockpit": 103,
+    "coffee shop": 104,
+    "computer room": 105,
+    "conference center": 106,
+    "conference room": 107,
+    "construction site": 108,
+    "control room": 109,
+    "control tower outdoor": 110,
+    "corn field": 111,
+    "corral": 112,
+    "corridor": 113,
+    "cottage garden": 114,
+    "courthouse": 115,
+    "courtroom": 116,
+    "courtyard": 117,
+    "covered bridge exterior": 118,
+    "creek": 119,
+    "crevasse": 120,
+    "crosswalk": 121,
+    "cubicle office": 122,
+    "dam": 123,
+    "delicatessen": 124,
+    "dentists office": 125,
+    "desert sand": 126,
+    "desert vegetation": 127,
+    "diner indoor": 128,
+    "diner outdoor": 129,
+    "dinette home": 130,
+    "dinette vehicle": 131,
+    "dining car": 132,
+    "dining room": 133,
+    "discotheque": 134,
+    "dock": 135,
+    "doorway outdoor": 136,
+    "dorm room": 137,
+    "driveway": 138,
+    "driving range outdoor": 139,
+    "drugstore": 140,
+    "electrical substation": 141,
+    "elevator door": 142,
+    "elevator interior": 143,
+    "elevator shaft": 144,
+    "engine room": 145,
+    "escalator indoor": 146,
+    "excavation": 147,
+    "factory indoor": 148,
+    "fairway": 149,
+    "fastfood restaurant": 150,
+    "field cultivated": 151,
+    "field wild": 152,
+    "fire escape": 153,
+    "fire station": 154,
+    "firing range indoor": 155,
+    "fishpond": 156,
+    "florist shop indoor": 157,
+    "food court": 158,
+    "forest broadleaf": 159,
+    "forest needleleaf": 160,
+    "forest path": 161,
+    "forest road": 162,
+    "formal garden": 163,
+    "fountain": 164,
+    "galley": 165,
+    "game room": 166,
+    "garage indoor": 167,
+    "garbage dump": 168,
+    "gas station": 169,
+    "gazebo exterior": 170,
+    "general store indoor": 171,
+    "general store outdoor": 172,
+    "gift shop": 173,
+    "golf course": 174,
+    "greenhouse indoor": 175,
+    "greenhouse outdoor": 176,
+    "gymnasium indoor": 177,
+    "hangar indoor": 178,
+    "hangar outdoor": 179,
+    "harbor": 180,
+    "hayfield": 181,
+    "heliport": 182,
+    "herb garden": 183,
+    "highway": 184,
+    "hill": 185,
+    "home office": 186,
+    "hospital": 187,
+    "hospital room": 188,
+    "hot spring": 189,
+    "hot tub outdoor": 190,
+    "hotel outdoor": 191,
+    "hotel room": 192,
+    "house": 193,
+    "hunting lodge outdoor": 194,
+    "ice cream parlor": 195,
+    "ice floe": 196,
+    "ice shelf": 197,
+    "ice skating rink indoor": 198,
+    "ice skating rink outdoor": 199,
+    "iceberg": 200,
+    "igloo": 201,
+    "industrial area": 202,
+    "inn outdoor": 203,
+    "islet": 204,
+    "jacuzzi indoor": 205,
+    "jail cell": 206,
+    "jail indoor": 207,
+    "jewelry shop": 208,
+    "kasbah": 209,
+    "kennel indoor": 210,
+    "kennel outdoor": 211,
+    "kindergarden classroom": 212,
+    "kitchen": 213,
+    "kitchenette": 214,
+    "labyrinth outdoor": 215,
+    "lake natural": 216,
+    "landfill": 217,
+    "landing deck": 218,
+    "laundromat": 219,
+    "lecture room": 220,
+    "library indoor": 221,
+    "library outdoor": 222,
+    "lido deck outdoor": 223,
+    "lift bridge": 224,
+    "lighthouse": 225,
+    "limousine interior": 226,
+    "living room": 227,
+    "lobby": 228,
+    "lock chamber": 229,
+    "locker room": 230,
+    "mansion": 231,
+    "manufactured home": 232,
+    "market indoor": 233,
+    "market outdoor": 234,
+    "marsh": 235,
+    "martial arts gym": 236,
+    "mausoleum": 237,
+    "medina": 238,
+    "moat water": 239,
+    "monastery outdoor": 240,
+    "mosque indoor": 241,
+    "mosque outdoor": 242,
+    "motel": 243,
+    "mountain": 244,
+    "mountain snowy": 245,
+    "movie theater indoor": 246,
+    "museum indoor": 247,
+    "music store": 248,
+    "music studio": 249,
+    "nuclear power plant outdoor": 250,
+    "nursery": 251,
+    "oast house": 252,
+    "observatory outdoor": 253,
+    "ocean": 254,
+    "office": 255,
+    "office building": 256,
+    "oil refinery outdoor": 257,
+    "oilrig": 258,
+    "operating room": 259,
+    "orchard": 260,
+    "outhouse outdoor": 261,
+    "pagoda": 262,
+    "palace": 263,
+    "pantry": 264,
+    "park": 265,
+    "parking garage indoor": 266,
+    "parking garage outdoor": 267,
+    "parking lot": 268,
+    "parlor": 269,
+    "pasture": 270,
+    "patio": 271,
+    "pavilion": 272,
+    "pharmacy": 273,
+    "phone booth": 274,
+    "physics laboratory": 275,
+    "picnic area": 276,
+    "pilothouse indoor": 277,
+    "planetarium outdoor": 278,
+    "playground": 279,
+    "playroom": 280,
+    "plaza": 281,
+    "podium indoor": 282,
+    "podium outdoor": 283,
+    "pond": 284,
+    "poolroom establishment": 285,
+    "poolroom home": 286,
+    "power plant outdoor": 287,
+    "promenade deck": 288,
+    "pub indoor": 289,
+    "pulpit": 290,
+    "putting green": 291,
+    "racecourse": 292,
+    "raceway": 293,
+    "raft": 294,
+    "railroad track": 295,
+    "rainforest": 296,
+    "reception": 297,
+    "recreation room": 298,
+    "residential neighborhood": 299,
+    "restaurant": 300,
+    "restaurant kitchen": 301,
+    "restaurant patio": 302,
+    "rice paddy": 303,
+    "riding arena": 304,
+    "river": 305,
+    "rock arch": 306,
+    "rope bridge": 307,
+    "ruin": 308,
+    "runway": 309,
+    "sandbar": 310,
+    "sandbox": 311,
+    "sauna": 312,
+    "schoolhouse": 313,
+    "sea cliff": 314,
+    "server room": 315,
+    "shed": 316,
+    "shoe shop": 317,
+    "shopfront": 318,
+    "shopping mall indoor": 319,
+    "shower": 320,
+    "skatepark": 321,
+    "ski lodge": 322,
+    "ski resort": 323,
+    "ski slope": 324,
+    "sky": 325,
+    "skyscraper": 326,
+    "slum": 327,
+    "snowfield": 328,
+    "squash court": 329,
+    "stable": 330,
+    "stadium baseball": 331,
+    "stadium football": 332,
+    "stage indoor": 333,
+    "staircase": 334,
+    "street": 335,
+    "subway interior": 336,
+    "subway station platform": 337,
+    "supermarket": 338,
+    "sushi bar": 339,
+    "swamp": 340,
+    "swimming pool indoor": 341,
+    "swimming pool outdoor": 342,
+    "synagogue indoor": 343,
+    "synagogue outdoor": 344,
+    "television studio": 345,
+    "temple east asia": 346,
+    "temple south asia": 347,
+    "tennis court indoor": 348,
+    "tennis court outdoor": 349,
+    "tent outdoor": 350,
+    "theater indoor procenium": 351,
+    "theater indoor seats": 352,
+    "thriftshop": 353,
+    "throne room": 354,
+    "ticket booth": 355,
+    "toll plaza": 356,
+    "topiary garden": 357,
+    "tower": 358,
+    "toyshop": 359,
+    "track outdoor": 360,
+    "train railway": 361,
+    "train station platform": 362,
+    "tree farm": 363,
+    "tree house": 364,
+    "trench": 365,
+    "underwater coral reef": 366,
+    "utility room": 367,
+    "valley": 368,
+    "van interior": 369,
+    "vegetable garden": 370,
+    "veranda": 371,
+    "veterinarians office": 372,
+    "viaduct": 373,
+    "videostore": 374,
+    "village": 375,
+    "vineyard": 376,
+    "volcano": 377,
+    "volleyball court indoor": 378,
+    "volleyball court outdoor": 379,
+    "waiting room": 380,
+    "warehouse indoor": 381,
+    "water tower": 382,
+    "waterfall block": 383,
+    "waterfall fan": 384,
+    "waterfall plunge": 385,
+    "watering hole": 386,
+    "wave": 387,
+    "wet bar": 388,
+    "wheat field": 389,
+    "wind farm": 390,
+    "windmill": 391,
+    "wine cellar barrel storage": 392,
+    "wine cellar bottle storage": 393,
+    "wrestling ring indoor": 394,
+    "yard": 395,
+    "youth hostel": 396
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-sun397-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet152-sun397-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-sun397-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/README.md b/resnet152-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..2b92d238a3351a9276143f5595826b3dbcf5dbc4
--- /dev/null
+++ b/resnet152-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset sun397.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: sun397
+    pretrained: true
+test_datasets: null
+train_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: train
+type: transformers
+val_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: test
+```
+
diff --git a/resnet152-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/config.json b/resnet152-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..235472e739b23ead2b88b4266434b8f42502d7ea
--- /dev/null
+++ b/resnet152-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,837 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "abbey",
+    "1": "airplane cabin",
+    "2": "airport terminal",
+    "3": "alley",
+    "4": "amphitheater",
+    "5": "amusement arcade",
+    "6": "amusement park",
+    "7": "anechoic chamber",
+    "8": "apartment building outdoor",
+    "9": "apse indoor",
+    "10": "aquarium",
+    "11": "aqueduct",
+    "12": "arch",
+    "13": "archive",
+    "14": "arrival gate outdoor",
+    "15": "art gallery",
+    "16": "art school",
+    "17": "art studio",
+    "18": "assembly line",
+    "19": "athletic field outdoor",
+    "20": "atrium public",
+    "21": "attic",
+    "22": "auditorium",
+    "23": "auto factory",
+    "24": "badlands",
+    "25": "badminton court indoor",
+    "26": "baggage claim",
+    "27": "bakery shop",
+    "28": "balcony exterior",
+    "29": "balcony interior",
+    "30": "ball pit",
+    "31": "ballroom",
+    "32": "bamboo forest",
+    "33": "banquet hall",
+    "34": "bar",
+    "35": "barn",
+    "36": "barndoor",
+    "37": "baseball field",
+    "38": "basement",
+    "39": "basilica",
+    "40": "basketball court outdoor",
+    "41": "bathroom",
+    "42": "batters box",
+    "43": "bayou",
+    "44": "bazaar indoor",
+    "45": "bazaar outdoor",
+    "46": "beach",
+    "47": "beauty salon",
+    "48": "bedroom",
+    "49": "berth",
+    "50": "biology laboratory",
+    "51": "bistro indoor",
+    "52": "boardwalk",
+    "53": "boat deck",
+    "54": "boathouse",
+    "55": "bookstore",
+    "56": "booth indoor",
+    "57": "botanical garden",
+    "58": "bow window indoor",
+    "59": "bow window outdoor",
+    "60": "bowling alley",
+    "61": "boxing ring",
+    "62": "brewery indoor",
+    "63": "bridge",
+    "64": "building facade",
+    "65": "bullring",
+    "66": "burial chamber",
+    "67": "bus interior",
+    "68": "butchers shop",
+    "69": "butte",
+    "70": "cabin outdoor",
+    "71": "cafeteria",
+    "72": "campsite",
+    "73": "campus",
+    "74": "canal natural",
+    "75": "canal urban",
+    "76": "candy store",
+    "77": "canyon",
+    "78": "car interior backseat",
+    "79": "car interior frontseat",
+    "80": "carrousel",
+    "81": "casino indoor",
+    "82": "castle",
+    "83": "catacomb",
+    "84": "cathedral indoor",
+    "85": "cathedral outdoor",
+    "86": "cavern indoor",
+    "87": "cemetery",
+    "88": "chalet",
+    "89": "cheese factory",
+    "90": "chemistry lab",
+    "91": "chicken coop indoor",
+    "92": "chicken coop outdoor",
+    "93": "childs room",
+    "94": "church indoor",
+    "95": "church outdoor",
+    "96": "classroom",
+    "97": "clean room",
+    "98": "cliff",
+    "99": "cloister indoor",
+    "100": "closet",
+    "101": "clothing store",
+    "102": "coast",
+    "103": "cockpit",
+    "104": "coffee shop",
+    "105": "computer room",
+    "106": "conference center",
+    "107": "conference room",
+    "108": "construction site",
+    "109": "control room",
+    "110": "control tower outdoor",
+    "111": "corn field",
+    "112": "corral",
+    "113": "corridor",
+    "114": "cottage garden",
+    "115": "courthouse",
+    "116": "courtroom",
+    "117": "courtyard",
+    "118": "covered bridge exterior",
+    "119": "creek",
+    "120": "crevasse",
+    "121": "crosswalk",
+    "122": "cubicle office",
+    "123": "dam",
+    "124": "delicatessen",
+    "125": "dentists office",
+    "126": "desert sand",
+    "127": "desert vegetation",
+    "128": "diner indoor",
+    "129": "diner outdoor",
+    "130": "dinette home",
+    "131": "dinette vehicle",
+    "132": "dining car",
+    "133": "dining room",
+    "134": "discotheque",
+    "135": "dock",
+    "136": "doorway outdoor",
+    "137": "dorm room",
+    "138": "driveway",
+    "139": "driving range outdoor",
+    "140": "drugstore",
+    "141": "electrical substation",
+    "142": "elevator door",
+    "143": "elevator interior",
+    "144": "elevator shaft",
+    "145": "engine room",
+    "146": "escalator indoor",
+    "147": "excavation",
+    "148": "factory indoor",
+    "149": "fairway",
+    "150": "fastfood restaurant",
+    "151": "field cultivated",
+    "152": "field wild",
+    "153": "fire escape",
+    "154": "fire station",
+    "155": "firing range indoor",
+    "156": "fishpond",
+    "157": "florist shop indoor",
+    "158": "food court",
+    "159": "forest broadleaf",
+    "160": "forest needleleaf",
+    "161": "forest path",
+    "162": "forest road",
+    "163": "formal garden",
+    "164": "fountain",
+    "165": "galley",
+    "166": "game room",
+    "167": "garage indoor",
+    "168": "garbage dump",
+    "169": "gas station",
+    "170": "gazebo exterior",
+    "171": "general store indoor",
+    "172": "general store outdoor",
+    "173": "gift shop",
+    "174": "golf course",
+    "175": "greenhouse indoor",
+    "176": "greenhouse outdoor",
+    "177": "gymnasium indoor",
+    "178": "hangar indoor",
+    "179": "hangar outdoor",
+    "180": "harbor",
+    "181": "hayfield",
+    "182": "heliport",
+    "183": "herb garden",
+    "184": "highway",
+    "185": "hill",
+    "186": "home office",
+    "187": "hospital",
+    "188": "hospital room",
+    "189": "hot spring",
+    "190": "hot tub outdoor",
+    "191": "hotel outdoor",
+    "192": "hotel room",
+    "193": "house",
+    "194": "hunting lodge outdoor",
+    "195": "ice cream parlor",
+    "196": "ice floe",
+    "197": "ice shelf",
+    "198": "ice skating rink indoor",
+    "199": "ice skating rink outdoor",
+    "200": "iceberg",
+    "201": "igloo",
+    "202": "industrial area",
+    "203": "inn outdoor",
+    "204": "islet",
+    "205": "jacuzzi indoor",
+    "206": "jail cell",
+    "207": "jail indoor",
+    "208": "jewelry shop",
+    "209": "kasbah",
+    "210": "kennel indoor",
+    "211": "kennel outdoor",
+    "212": "kindergarden classroom",
+    "213": "kitchen",
+    "214": "kitchenette",
+    "215": "labyrinth outdoor",
+    "216": "lake natural",
+    "217": "landfill",
+    "218": "landing deck",
+    "219": "laundromat",
+    "220": "lecture room",
+    "221": "library indoor",
+    "222": "library outdoor",
+    "223": "lido deck outdoor",
+    "224": "lift bridge",
+    "225": "lighthouse",
+    "226": "limousine interior",
+    "227": "living room",
+    "228": "lobby",
+    "229": "lock chamber",
+    "230": "locker room",
+    "231": "mansion",
+    "232": "manufactured home",
+    "233": "market indoor",
+    "234": "market outdoor",
+    "235": "marsh",
+    "236": "martial arts gym",
+    "237": "mausoleum",
+    "238": "medina",
+    "239": "moat water",
+    "240": "monastery outdoor",
+    "241": "mosque indoor",
+    "242": "mosque outdoor",
+    "243": "motel",
+    "244": "mountain",
+    "245": "mountain snowy",
+    "246": "movie theater indoor",
+    "247": "museum indoor",
+    "248": "music store",
+    "249": "music studio",
+    "250": "nuclear power plant outdoor",
+    "251": "nursery",
+    "252": "oast house",
+    "253": "observatory outdoor",
+    "254": "ocean",
+    "255": "office",
+    "256": "office building",
+    "257": "oil refinery outdoor",
+    "258": "oilrig",
+    "259": "operating room",
+    "260": "orchard",
+    "261": "outhouse outdoor",
+    "262": "pagoda",
+    "263": "palace",
+    "264": "pantry",
+    "265": "park",
+    "266": "parking garage indoor",
+    "267": "parking garage outdoor",
+    "268": "parking lot",
+    "269": "parlor",
+    "270": "pasture",
+    "271": "patio",
+    "272": "pavilion",
+    "273": "pharmacy",
+    "274": "phone booth",
+    "275": "physics laboratory",
+    "276": "picnic area",
+    "277": "pilothouse indoor",
+    "278": "planetarium outdoor",
+    "279": "playground",
+    "280": "playroom",
+    "281": "plaza",
+    "282": "podium indoor",
+    "283": "podium outdoor",
+    "284": "pond",
+    "285": "poolroom establishment",
+    "286": "poolroom home",
+    "287": "power plant outdoor",
+    "288": "promenade deck",
+    "289": "pub indoor",
+    "290": "pulpit",
+    "291": "putting green",
+    "292": "racecourse",
+    "293": "raceway",
+    "294": "raft",
+    "295": "railroad track",
+    "296": "rainforest",
+    "297": "reception",
+    "298": "recreation room",
+    "299": "residential neighborhood",
+    "300": "restaurant",
+    "301": "restaurant kitchen",
+    "302": "restaurant patio",
+    "303": "rice paddy",
+    "304": "riding arena",
+    "305": "river",
+    "306": "rock arch",
+    "307": "rope bridge",
+    "308": "ruin",
+    "309": "runway",
+    "310": "sandbar",
+    "311": "sandbox",
+    "312": "sauna",
+    "313": "schoolhouse",
+    "314": "sea cliff",
+    "315": "server room",
+    "316": "shed",
+    "317": "shoe shop",
+    "318": "shopfront",
+    "319": "shopping mall indoor",
+    "320": "shower",
+    "321": "skatepark",
+    "322": "ski lodge",
+    "323": "ski resort",
+    "324": "ski slope",
+    "325": "sky",
+    "326": "skyscraper",
+    "327": "slum",
+    "328": "snowfield",
+    "329": "squash court",
+    "330": "stable",
+    "331": "stadium baseball",
+    "332": "stadium football",
+    "333": "stage indoor",
+    "334": "staircase",
+    "335": "street",
+    "336": "subway interior",
+    "337": "subway station platform",
+    "338": "supermarket",
+    "339": "sushi bar",
+    "340": "swamp",
+    "341": "swimming pool indoor",
+    "342": "swimming pool outdoor",
+    "343": "synagogue indoor",
+    "344": "synagogue outdoor",
+    "345": "television studio",
+    "346": "temple east asia",
+    "347": "temple south asia",
+    "348": "tennis court indoor",
+    "349": "tennis court outdoor",
+    "350": "tent outdoor",
+    "351": "theater indoor procenium",
+    "352": "theater indoor seats",
+    "353": "thriftshop",
+    "354": "throne room",
+    "355": "ticket booth",
+    "356": "toll plaza",
+    "357": "topiary garden",
+    "358": "tower",
+    "359": "toyshop",
+    "360": "track outdoor",
+    "361": "train railway",
+    "362": "train station platform",
+    "363": "tree farm",
+    "364": "tree house",
+    "365": "trench",
+    "366": "underwater coral reef",
+    "367": "utility room",
+    "368": "valley",
+    "369": "van interior",
+    "370": "vegetable garden",
+    "371": "veranda",
+    "372": "veterinarians office",
+    "373": "viaduct",
+    "374": "videostore",
+    "375": "village",
+    "376": "vineyard",
+    "377": "volcano",
+    "378": "volleyball court indoor",
+    "379": "volleyball court outdoor",
+    "380": "waiting room",
+    "381": "warehouse indoor",
+    "382": "water tower",
+    "383": "waterfall block",
+    "384": "waterfall fan",
+    "385": "waterfall plunge",
+    "386": "watering hole",
+    "387": "wave",
+    "388": "wet bar",
+    "389": "wheat field",
+    "390": "wind farm",
+    "391": "windmill",
+    "392": "wine cellar barrel storage",
+    "393": "wine cellar bottle storage",
+    "394": "wrestling ring indoor",
+    "395": "yard",
+    "396": "youth hostel"
+  },
+  "label2id": {
+    "abbey": 0,
+    "airplane cabin": 1,
+    "airport terminal": 2,
+    "alley": 3,
+    "amphitheater": 4,
+    "amusement arcade": 5,
+    "amusement park": 6,
+    "anechoic chamber": 7,
+    "apartment building outdoor": 8,
+    "apse indoor": 9,
+    "aquarium": 10,
+    "aqueduct": 11,
+    "arch": 12,
+    "archive": 13,
+    "arrival gate outdoor": 14,
+    "art gallery": 15,
+    "art school": 16,
+    "art studio": 17,
+    "assembly line": 18,
+    "athletic field outdoor": 19,
+    "atrium public": 20,
+    "attic": 21,
+    "auditorium": 22,
+    "auto factory": 23,
+    "badlands": 24,
+    "badminton court indoor": 25,
+    "baggage claim": 26,
+    "bakery shop": 27,
+    "balcony exterior": 28,
+    "balcony interior": 29,
+    "ball pit": 30,
+    "ballroom": 31,
+    "bamboo forest": 32,
+    "banquet hall": 33,
+    "bar": 34,
+    "barn": 35,
+    "barndoor": 36,
+    "baseball field": 37,
+    "basement": 38,
+    "basilica": 39,
+    "basketball court outdoor": 40,
+    "bathroom": 41,
+    "batters box": 42,
+    "bayou": 43,
+    "bazaar indoor": 44,
+    "bazaar outdoor": 45,
+    "beach": 46,
+    "beauty salon": 47,
+    "bedroom": 48,
+    "berth": 49,
+    "biology laboratory": 50,
+    "bistro indoor": 51,
+    "boardwalk": 52,
+    "boat deck": 53,
+    "boathouse": 54,
+    "bookstore": 55,
+    "booth indoor": 56,
+    "botanical garden": 57,
+    "bow window indoor": 58,
+    "bow window outdoor": 59,
+    "bowling alley": 60,
+    "boxing ring": 61,
+    "brewery indoor": 62,
+    "bridge": 63,
+    "building facade": 64,
+    "bullring": 65,
+    "burial chamber": 66,
+    "bus interior": 67,
+    "butchers shop": 68,
+    "butte": 69,
+    "cabin outdoor": 70,
+    "cafeteria": 71,
+    "campsite": 72,
+    "campus": 73,
+    "canal natural": 74,
+    "canal urban": 75,
+    "candy store": 76,
+    "canyon": 77,
+    "car interior backseat": 78,
+    "car interior frontseat": 79,
+    "carrousel": 80,
+    "casino indoor": 81,
+    "castle": 82,
+    "catacomb": 83,
+    "cathedral indoor": 84,
+    "cathedral outdoor": 85,
+    "cavern indoor": 86,
+    "cemetery": 87,
+    "chalet": 88,
+    "cheese factory": 89,
+    "chemistry lab": 90,
+    "chicken coop indoor": 91,
+    "chicken coop outdoor": 92,
+    "childs room": 93,
+    "church indoor": 94,
+    "church outdoor": 95,
+    "classroom": 96,
+    "clean room": 97,
+    "cliff": 98,
+    "cloister indoor": 99,
+    "closet": 100,
+    "clothing store": 101,
+    "coast": 102,
+    "cockpit": 103,
+    "coffee shop": 104,
+    "computer room": 105,
+    "conference center": 106,
+    "conference room": 107,
+    "construction site": 108,
+    "control room": 109,
+    "control tower outdoor": 110,
+    "corn field": 111,
+    "corral": 112,
+    "corridor": 113,
+    "cottage garden": 114,
+    "courthouse": 115,
+    "courtroom": 116,
+    "courtyard": 117,
+    "covered bridge exterior": 118,
+    "creek": 119,
+    "crevasse": 120,
+    "crosswalk": 121,
+    "cubicle office": 122,
+    "dam": 123,
+    "delicatessen": 124,
+    "dentists office": 125,
+    "desert sand": 126,
+    "desert vegetation": 127,
+    "diner indoor": 128,
+    "diner outdoor": 129,
+    "dinette home": 130,
+    "dinette vehicle": 131,
+    "dining car": 132,
+    "dining room": 133,
+    "discotheque": 134,
+    "dock": 135,
+    "doorway outdoor": 136,
+    "dorm room": 137,
+    "driveway": 138,
+    "driving range outdoor": 139,
+    "drugstore": 140,
+    "electrical substation": 141,
+    "elevator door": 142,
+    "elevator interior": 143,
+    "elevator shaft": 144,
+    "engine room": 145,
+    "escalator indoor": 146,
+    "excavation": 147,
+    "factory indoor": 148,
+    "fairway": 149,
+    "fastfood restaurant": 150,
+    "field cultivated": 151,
+    "field wild": 152,
+    "fire escape": 153,
+    "fire station": 154,
+    "firing range indoor": 155,
+    "fishpond": 156,
+    "florist shop indoor": 157,
+    "food court": 158,
+    "forest broadleaf": 159,
+    "forest needleleaf": 160,
+    "forest path": 161,
+    "forest road": 162,
+    "formal garden": 163,
+    "fountain": 164,
+    "galley": 165,
+    "game room": 166,
+    "garage indoor": 167,
+    "garbage dump": 168,
+    "gas station": 169,
+    "gazebo exterior": 170,
+    "general store indoor": 171,
+    "general store outdoor": 172,
+    "gift shop": 173,
+    "golf course": 174,
+    "greenhouse indoor": 175,
+    "greenhouse outdoor": 176,
+    "gymnasium indoor": 177,
+    "hangar indoor": 178,
+    "hangar outdoor": 179,
+    "harbor": 180,
+    "hayfield": 181,
+    "heliport": 182,
+    "herb garden": 183,
+    "highway": 184,
+    "hill": 185,
+    "home office": 186,
+    "hospital": 187,
+    "hospital room": 188,
+    "hot spring": 189,
+    "hot tub outdoor": 190,
+    "hotel outdoor": 191,
+    "hotel room": 192,
+    "house": 193,
+    "hunting lodge outdoor": 194,
+    "ice cream parlor": 195,
+    "ice floe": 196,
+    "ice shelf": 197,
+    "ice skating rink indoor": 198,
+    "ice skating rink outdoor": 199,
+    "iceberg": 200,
+    "igloo": 201,
+    "industrial area": 202,
+    "inn outdoor": 203,
+    "islet": 204,
+    "jacuzzi indoor": 205,
+    "jail cell": 206,
+    "jail indoor": 207,
+    "jewelry shop": 208,
+    "kasbah": 209,
+    "kennel indoor": 210,
+    "kennel outdoor": 211,
+    "kindergarden classroom": 212,
+    "kitchen": 213,
+    "kitchenette": 214,
+    "labyrinth outdoor": 215,
+    "lake natural": 216,
+    "landfill": 217,
+    "landing deck": 218,
+    "laundromat": 219,
+    "lecture room": 220,
+    "library indoor": 221,
+    "library outdoor": 222,
+    "lido deck outdoor": 223,
+    "lift bridge": 224,
+    "lighthouse": 225,
+    "limousine interior": 226,
+    "living room": 227,
+    "lobby": 228,
+    "lock chamber": 229,
+    "locker room": 230,
+    "mansion": 231,
+    "manufactured home": 232,
+    "market indoor": 233,
+    "market outdoor": 234,
+    "marsh": 235,
+    "martial arts gym": 236,
+    "mausoleum": 237,
+    "medina": 238,
+    "moat water": 239,
+    "monastery outdoor": 240,
+    "mosque indoor": 241,
+    "mosque outdoor": 242,
+    "motel": 243,
+    "mountain": 244,
+    "mountain snowy": 245,
+    "movie theater indoor": 246,
+    "museum indoor": 247,
+    "music store": 248,
+    "music studio": 249,
+    "nuclear power plant outdoor": 250,
+    "nursery": 251,
+    "oast house": 252,
+    "observatory outdoor": 253,
+    "ocean": 254,
+    "office": 255,
+    "office building": 256,
+    "oil refinery outdoor": 257,
+    "oilrig": 258,
+    "operating room": 259,
+    "orchard": 260,
+    "outhouse outdoor": 261,
+    "pagoda": 262,
+    "palace": 263,
+    "pantry": 264,
+    "park": 265,
+    "parking garage indoor": 266,
+    "parking garage outdoor": 267,
+    "parking lot": 268,
+    "parlor": 269,
+    "pasture": 270,
+    "patio": 271,
+    "pavilion": 272,
+    "pharmacy": 273,
+    "phone booth": 274,
+    "physics laboratory": 275,
+    "picnic area": 276,
+    "pilothouse indoor": 277,
+    "planetarium outdoor": 278,
+    "playground": 279,
+    "playroom": 280,
+    "plaza": 281,
+    "podium indoor": 282,
+    "podium outdoor": 283,
+    "pond": 284,
+    "poolroom establishment": 285,
+    "poolroom home": 286,
+    "power plant outdoor": 287,
+    "promenade deck": 288,
+    "pub indoor": 289,
+    "pulpit": 290,
+    "putting green": 291,
+    "racecourse": 292,
+    "raceway": 293,
+    "raft": 294,
+    "railroad track": 295,
+    "rainforest": 296,
+    "reception": 297,
+    "recreation room": 298,
+    "residential neighborhood": 299,
+    "restaurant": 300,
+    "restaurant kitchen": 301,
+    "restaurant patio": 302,
+    "rice paddy": 303,
+    "riding arena": 304,
+    "river": 305,
+    "rock arch": 306,
+    "rope bridge": 307,
+    "ruin": 308,
+    "runway": 309,
+    "sandbar": 310,
+    "sandbox": 311,
+    "sauna": 312,
+    "schoolhouse": 313,
+    "sea cliff": 314,
+    "server room": 315,
+    "shed": 316,
+    "shoe shop": 317,
+    "shopfront": 318,
+    "shopping mall indoor": 319,
+    "shower": 320,
+    "skatepark": 321,
+    "ski lodge": 322,
+    "ski resort": 323,
+    "ski slope": 324,
+    "sky": 325,
+    "skyscraper": 326,
+    "slum": 327,
+    "snowfield": 328,
+    "squash court": 329,
+    "stable": 330,
+    "stadium baseball": 331,
+    "stadium football": 332,
+    "stage indoor": 333,
+    "staircase": 334,
+    "street": 335,
+    "subway interior": 336,
+    "subway station platform": 337,
+    "supermarket": 338,
+    "sushi bar": 339,
+    "swamp": 340,
+    "swimming pool indoor": 341,
+    "swimming pool outdoor": 342,
+    "synagogue indoor": 343,
+    "synagogue outdoor": 344,
+    "television studio": 345,
+    "temple east asia": 346,
+    "temple south asia": 347,
+    "tennis court indoor": 348,
+    "tennis court outdoor": 349,
+    "tent outdoor": 350,
+    "theater indoor procenium": 351,
+    "theater indoor seats": 352,
+    "thriftshop": 353,
+    "throne room": 354,
+    "ticket booth": 355,
+    "toll plaza": 356,
+    "topiary garden": 357,
+    "tower": 358,
+    "toyshop": 359,
+    "track outdoor": 360,
+    "train railway": 361,
+    "train station platform": 362,
+    "tree farm": 363,
+    "tree house": 364,
+    "trench": 365,
+    "underwater coral reef": 366,
+    "utility room": 367,
+    "valley": 368,
+    "van interior": 369,
+    "vegetable garden": 370,
+    "veranda": 371,
+    "veterinarians office": 372,
+    "viaduct": 373,
+    "videostore": 374,
+    "village": 375,
+    "vineyard": 376,
+    "volcano": 377,
+    "volleyball court indoor": 378,
+    "volleyball court outdoor": 379,
+    "waiting room": 380,
+    "warehouse indoor": 381,
+    "water tower": 382,
+    "waterfall block": 383,
+    "waterfall fan": 384,
+    "waterfall plunge": 385,
+    "watering hole": 386,
+    "wave": 387,
+    "wet bar": 388,
+    "wheat field": 389,
+    "wind farm": 390,
+    "windmill": 391,
+    "wine cellar barrel storage": 392,
+    "wine cellar bottle storage": 393,
+    "wrestling ring indoor": 394,
+    "yard": 395,
+    "youth hostel": 396
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet152-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-svhn-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/README.md b/resnet152-svhn-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..8290ba24346dad9acbc878625c7b3f6747bd980b
--- /dev/null
+++ b/resnet152-svhn-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/README.md
@@ -0,0 +1,80 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset svhn.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: svhn
+    pretrained: true
+test_datasets: null
+train_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: train
+type: transformers
+val_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: test
+```
+
diff --git a/resnet152-svhn-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/config.json b/resnet152-svhn-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..499ddc3e4e5dc0456a3110b1e6f22201afc1936e
--- /dev/null
+++ b/resnet152-svhn-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-svhn-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet152-svhn-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-svhn-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-svhn-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/README.md b/resnet152-svhn-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..fd4b0b904594035ae92cd818046860f0fe7833ab
--- /dev/null
+++ b/resnet152-svhn-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/README.md
@@ -0,0 +1,80 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset svhn.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: svhn
+    pretrained: true
+test_datasets: null
+train_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: train
+type: transformers
+val_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: test
+```
+
diff --git a/resnet152-svhn-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/config.json b/resnet152-svhn-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..499ddc3e4e5dc0456a3110b1e6f22201afc1936e
--- /dev/null
+++ b/resnet152-svhn-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-svhn-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet152-svhn-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-svhn-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet152-svhn-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/README.md b/resnet152-svhn-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..8407c6c756b42a31a58d980d556fd730c18724b0
--- /dev/null
+++ b/resnet152-svhn-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,80 @@
+---
+base_model: microsoft/resnet-152
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset svhn.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-152
+    dataset_name: svhn
+    pretrained: true
+test_datasets: null
+train_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: train
+type: transformers
+val_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: test
+```
+
diff --git a/resnet152-svhn-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/config.json b/resnet152-svhn-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..499ddc3e4e5dc0456a3110b1e6f22201afc1936e
--- /dev/null
+++ b/resnet152-svhn-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    8,
+    36,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet152-svhn-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet152-svhn-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet152-svhn-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-cifar10-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/README.md b/resnet18-cifar10-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..eecbe28648261c5a191fdd6a609462d098aeef16
--- /dev/null
+++ b/resnet18-cifar10-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: cifar10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: train
+type: transformers
+val_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: test
+```
+
diff --git a/resnet18-cifar10-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/config.json b/resnet18-cifar10-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..a6fd7768d9fade7e7d7df7ed5cd1e93ae4baec32
--- /dev/null
+++ b/resnet18-cifar10-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "automobile",
+    "2": "bird",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "frog",
+    "7": "horse",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "automobile": 1,
+    "bird": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "frog": 6,
+    "horse": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-cifar10-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet18-cifar10-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-cifar10-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-cifar10-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/README.md b/resnet18-cifar10-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..96a63f55452f4a962f0c0d97ea337eb12c354891
--- /dev/null
+++ b/resnet18-cifar10-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: cifar10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: train
+type: transformers
+val_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: test
+```
+
diff --git a/resnet18-cifar10-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/config.json b/resnet18-cifar10-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..a6fd7768d9fade7e7d7df7ed5cd1e93ae4baec32
--- /dev/null
+++ b/resnet18-cifar10-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "automobile",
+    "2": "bird",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "frog",
+    "7": "horse",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "automobile": 1,
+    "bird": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "frog": 6,
+    "horse": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-cifar10-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet18-cifar10-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-cifar10-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-cifar10-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/README.md b/resnet18-cifar10-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..6dcea2c63f8144f57ec8d047dc28ae88bb9a04e0
--- /dev/null
+++ b/resnet18-cifar10-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: cifar10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: train
+type: transformers
+val_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: test
+```
+
diff --git a/resnet18-cifar10-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/config.json b/resnet18-cifar10-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..a6fd7768d9fade7e7d7df7ed5cd1e93ae4baec32
--- /dev/null
+++ b/resnet18-cifar10-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "automobile",
+    "2": "bird",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "frog",
+    "7": "horse",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "automobile": 1,
+    "bird": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "frog": 6,
+    "horse": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-cifar10-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet18-cifar10-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-cifar10-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-cifar100-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/README.md b/resnet18-cifar100-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..300973acb0b6f068c2fedfebf31ee1515822619a
--- /dev/null
+++ b/resnet18-cifar100-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar100.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: cifar100
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: train
+type: transformers
+val_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: test
+```
+
diff --git a/resnet18-cifar100-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/config.json b/resnet18-cifar100-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..5c3f41b9ed6c00df33ffaef448e5b6c8ac8a8d65
--- /dev/null
+++ b/resnet18-cifar100-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,243 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "apple",
+    "1": "aquarium_fish",
+    "2": "baby",
+    "3": "bear",
+    "4": "beaver",
+    "5": "bed",
+    "6": "bee",
+    "7": "beetle",
+    "8": "bicycle",
+    "9": "bottle",
+    "10": "bowl",
+    "11": "boy",
+    "12": "bridge",
+    "13": "bus",
+    "14": "butterfly",
+    "15": "camel",
+    "16": "can",
+    "17": "castle",
+    "18": "caterpillar",
+    "19": "cattle",
+    "20": "chair",
+    "21": "chimpanzee",
+    "22": "clock",
+    "23": "cloud",
+    "24": "cockroach",
+    "25": "couch",
+    "26": "cra",
+    "27": "crocodile",
+    "28": "cup",
+    "29": "dinosaur",
+    "30": "dolphin",
+    "31": "elephant",
+    "32": "flatfish",
+    "33": "forest",
+    "34": "fox",
+    "35": "girl",
+    "36": "hamster",
+    "37": "house",
+    "38": "kangaroo",
+    "39": "keyboard",
+    "40": "lamp",
+    "41": "lawn_mower",
+    "42": "leopard",
+    "43": "lion",
+    "44": "lizard",
+    "45": "lobster",
+    "46": "man",
+    "47": "maple_tree",
+    "48": "motorcycle",
+    "49": "mountain",
+    "50": "mouse",
+    "51": "mushroom",
+    "52": "oak_tree",
+    "53": "orange",
+    "54": "orchid",
+    "55": "otter",
+    "56": "palm_tree",
+    "57": "pear",
+    "58": "pickup_truck",
+    "59": "pine_tree",
+    "60": "plain",
+    "61": "plate",
+    "62": "poppy",
+    "63": "porcupine",
+    "64": "possum",
+    "65": "rabbit",
+    "66": "raccoon",
+    "67": "ray",
+    "68": "road",
+    "69": "rocket",
+    "70": "rose",
+    "71": "sea",
+    "72": "seal",
+    "73": "shark",
+    "74": "shrew",
+    "75": "skunk",
+    "76": "skyscraper",
+    "77": "snail",
+    "78": "snake",
+    "79": "spider",
+    "80": "squirrel",
+    "81": "streetcar",
+    "82": "sunflower",
+    "83": "sweet_pepper",
+    "84": "table",
+    "85": "tank",
+    "86": "telephone",
+    "87": "television",
+    "88": "tiger",
+    "89": "tractor",
+    "90": "train",
+    "91": "trout",
+    "92": "tulip",
+    "93": "turtle",
+    "94": "wardrobe",
+    "95": "whale",
+    "96": "willow_tree",
+    "97": "wolf",
+    "98": "woman",
+    "99": "worm"
+  },
+  "label2id": {
+    "apple": 0,
+    "aquarium_fish": 1,
+    "baby": 2,
+    "bear": 3,
+    "beaver": 4,
+    "bed": 5,
+    "bee": 6,
+    "beetle": 7,
+    "bicycle": 8,
+    "bottle": 9,
+    "bowl": 10,
+    "boy": 11,
+    "bridge": 12,
+    "bus": 13,
+    "butterfly": 14,
+    "camel": 15,
+    "can": 16,
+    "castle": 17,
+    "caterpillar": 18,
+    "cattle": 19,
+    "chair": 20,
+    "chimpanzee": 21,
+    "clock": 22,
+    "cloud": 23,
+    "cockroach": 24,
+    "couch": 25,
+    "cra": 26,
+    "crocodile": 27,
+    "cup": 28,
+    "dinosaur": 29,
+    "dolphin": 30,
+    "elephant": 31,
+    "flatfish": 32,
+    "forest": 33,
+    "fox": 34,
+    "girl": 35,
+    "hamster": 36,
+    "house": 37,
+    "kangaroo": 38,
+    "keyboard": 39,
+    "lamp": 40,
+    "lawn_mower": 41,
+    "leopard": 42,
+    "lion": 43,
+    "lizard": 44,
+    "lobster": 45,
+    "man": 46,
+    "maple_tree": 47,
+    "motorcycle": 48,
+    "mountain": 49,
+    "mouse": 50,
+    "mushroom": 51,
+    "oak_tree": 52,
+    "orange": 53,
+    "orchid": 54,
+    "otter": 55,
+    "palm_tree": 56,
+    "pear": 57,
+    "pickup_truck": 58,
+    "pine_tree": 59,
+    "plain": 60,
+    "plate": 61,
+    "poppy": 62,
+    "porcupine": 63,
+    "possum": 64,
+    "rabbit": 65,
+    "raccoon": 66,
+    "ray": 67,
+    "road": 68,
+    "rocket": 69,
+    "rose": 70,
+    "sea": 71,
+    "seal": 72,
+    "shark": 73,
+    "shrew": 74,
+    "skunk": 75,
+    "skyscraper": 76,
+    "snail": 77,
+    "snake": 78,
+    "spider": 79,
+    "squirrel": 80,
+    "streetcar": 81,
+    "sunflower": 82,
+    "sweet_pepper": 83,
+    "table": 84,
+    "tank": 85,
+    "telephone": 86,
+    "television": 87,
+    "tiger": 88,
+    "tractor": 89,
+    "train": 90,
+    "trout": 91,
+    "tulip": 92,
+    "turtle": 93,
+    "wardrobe": 94,
+    "whale": 95,
+    "willow_tree": 96,
+    "wolf": 97,
+    "woman": 98,
+    "worm": 99
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-cifar100-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet18-cifar100-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-cifar100-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-cifar100-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/README.md b/resnet18-cifar100-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..300973acb0b6f068c2fedfebf31ee1515822619a
--- /dev/null
+++ b/resnet18-cifar100-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar100.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: cifar100
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: train
+type: transformers
+val_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: test
+```
+
diff --git a/resnet18-cifar100-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/config.json b/resnet18-cifar100-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..5c3f41b9ed6c00df33ffaef448e5b6c8ac8a8d65
--- /dev/null
+++ b/resnet18-cifar100-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,243 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "apple",
+    "1": "aquarium_fish",
+    "2": "baby",
+    "3": "bear",
+    "4": "beaver",
+    "5": "bed",
+    "6": "bee",
+    "7": "beetle",
+    "8": "bicycle",
+    "9": "bottle",
+    "10": "bowl",
+    "11": "boy",
+    "12": "bridge",
+    "13": "bus",
+    "14": "butterfly",
+    "15": "camel",
+    "16": "can",
+    "17": "castle",
+    "18": "caterpillar",
+    "19": "cattle",
+    "20": "chair",
+    "21": "chimpanzee",
+    "22": "clock",
+    "23": "cloud",
+    "24": "cockroach",
+    "25": "couch",
+    "26": "cra",
+    "27": "crocodile",
+    "28": "cup",
+    "29": "dinosaur",
+    "30": "dolphin",
+    "31": "elephant",
+    "32": "flatfish",
+    "33": "forest",
+    "34": "fox",
+    "35": "girl",
+    "36": "hamster",
+    "37": "house",
+    "38": "kangaroo",
+    "39": "keyboard",
+    "40": "lamp",
+    "41": "lawn_mower",
+    "42": "leopard",
+    "43": "lion",
+    "44": "lizard",
+    "45": "lobster",
+    "46": "man",
+    "47": "maple_tree",
+    "48": "motorcycle",
+    "49": "mountain",
+    "50": "mouse",
+    "51": "mushroom",
+    "52": "oak_tree",
+    "53": "orange",
+    "54": "orchid",
+    "55": "otter",
+    "56": "palm_tree",
+    "57": "pear",
+    "58": "pickup_truck",
+    "59": "pine_tree",
+    "60": "plain",
+    "61": "plate",
+    "62": "poppy",
+    "63": "porcupine",
+    "64": "possum",
+    "65": "rabbit",
+    "66": "raccoon",
+    "67": "ray",
+    "68": "road",
+    "69": "rocket",
+    "70": "rose",
+    "71": "sea",
+    "72": "seal",
+    "73": "shark",
+    "74": "shrew",
+    "75": "skunk",
+    "76": "skyscraper",
+    "77": "snail",
+    "78": "snake",
+    "79": "spider",
+    "80": "squirrel",
+    "81": "streetcar",
+    "82": "sunflower",
+    "83": "sweet_pepper",
+    "84": "table",
+    "85": "tank",
+    "86": "telephone",
+    "87": "television",
+    "88": "tiger",
+    "89": "tractor",
+    "90": "train",
+    "91": "trout",
+    "92": "tulip",
+    "93": "turtle",
+    "94": "wardrobe",
+    "95": "whale",
+    "96": "willow_tree",
+    "97": "wolf",
+    "98": "woman",
+    "99": "worm"
+  },
+  "label2id": {
+    "apple": 0,
+    "aquarium_fish": 1,
+    "baby": 2,
+    "bear": 3,
+    "beaver": 4,
+    "bed": 5,
+    "bee": 6,
+    "beetle": 7,
+    "bicycle": 8,
+    "bottle": 9,
+    "bowl": 10,
+    "boy": 11,
+    "bridge": 12,
+    "bus": 13,
+    "butterfly": 14,
+    "camel": 15,
+    "can": 16,
+    "castle": 17,
+    "caterpillar": 18,
+    "cattle": 19,
+    "chair": 20,
+    "chimpanzee": 21,
+    "clock": 22,
+    "cloud": 23,
+    "cockroach": 24,
+    "couch": 25,
+    "cra": 26,
+    "crocodile": 27,
+    "cup": 28,
+    "dinosaur": 29,
+    "dolphin": 30,
+    "elephant": 31,
+    "flatfish": 32,
+    "forest": 33,
+    "fox": 34,
+    "girl": 35,
+    "hamster": 36,
+    "house": 37,
+    "kangaroo": 38,
+    "keyboard": 39,
+    "lamp": 40,
+    "lawn_mower": 41,
+    "leopard": 42,
+    "lion": 43,
+    "lizard": 44,
+    "lobster": 45,
+    "man": 46,
+    "maple_tree": 47,
+    "motorcycle": 48,
+    "mountain": 49,
+    "mouse": 50,
+    "mushroom": 51,
+    "oak_tree": 52,
+    "orange": 53,
+    "orchid": 54,
+    "otter": 55,
+    "palm_tree": 56,
+    "pear": 57,
+    "pickup_truck": 58,
+    "pine_tree": 59,
+    "plain": 60,
+    "plate": 61,
+    "poppy": 62,
+    "porcupine": 63,
+    "possum": 64,
+    "rabbit": 65,
+    "raccoon": 66,
+    "ray": 67,
+    "road": 68,
+    "rocket": 69,
+    "rose": 70,
+    "sea": 71,
+    "seal": 72,
+    "shark": 73,
+    "shrew": 74,
+    "skunk": 75,
+    "skyscraper": 76,
+    "snail": 77,
+    "snake": 78,
+    "spider": 79,
+    "squirrel": 80,
+    "streetcar": 81,
+    "sunflower": 82,
+    "sweet_pepper": 83,
+    "table": 84,
+    "tank": 85,
+    "telephone": 86,
+    "television": 87,
+    "tiger": 88,
+    "tractor": 89,
+    "train": 90,
+    "trout": 91,
+    "tulip": 92,
+    "turtle": 93,
+    "wardrobe": 94,
+    "whale": 95,
+    "willow_tree": 96,
+    "wolf": 97,
+    "woman": 98,
+    "worm": 99
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-cifar100-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet18-cifar100-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-cifar100-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-cifar100-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md b/resnet18-cifar100-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..8cfa76739476bc3085c9b7f6148cdadda80a912f
--- /dev/null
+++ b/resnet18-cifar100-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar100.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: cifar100
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: train
+type: transformers
+val_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: test
+```
+
diff --git a/resnet18-cifar100-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/config.json b/resnet18-cifar100-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..5c3f41b9ed6c00df33ffaef448e5b6c8ac8a8d65
--- /dev/null
+++ b/resnet18-cifar100-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,243 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "apple",
+    "1": "aquarium_fish",
+    "2": "baby",
+    "3": "bear",
+    "4": "beaver",
+    "5": "bed",
+    "6": "bee",
+    "7": "beetle",
+    "8": "bicycle",
+    "9": "bottle",
+    "10": "bowl",
+    "11": "boy",
+    "12": "bridge",
+    "13": "bus",
+    "14": "butterfly",
+    "15": "camel",
+    "16": "can",
+    "17": "castle",
+    "18": "caterpillar",
+    "19": "cattle",
+    "20": "chair",
+    "21": "chimpanzee",
+    "22": "clock",
+    "23": "cloud",
+    "24": "cockroach",
+    "25": "couch",
+    "26": "cra",
+    "27": "crocodile",
+    "28": "cup",
+    "29": "dinosaur",
+    "30": "dolphin",
+    "31": "elephant",
+    "32": "flatfish",
+    "33": "forest",
+    "34": "fox",
+    "35": "girl",
+    "36": "hamster",
+    "37": "house",
+    "38": "kangaroo",
+    "39": "keyboard",
+    "40": "lamp",
+    "41": "lawn_mower",
+    "42": "leopard",
+    "43": "lion",
+    "44": "lizard",
+    "45": "lobster",
+    "46": "man",
+    "47": "maple_tree",
+    "48": "motorcycle",
+    "49": "mountain",
+    "50": "mouse",
+    "51": "mushroom",
+    "52": "oak_tree",
+    "53": "orange",
+    "54": "orchid",
+    "55": "otter",
+    "56": "palm_tree",
+    "57": "pear",
+    "58": "pickup_truck",
+    "59": "pine_tree",
+    "60": "plain",
+    "61": "plate",
+    "62": "poppy",
+    "63": "porcupine",
+    "64": "possum",
+    "65": "rabbit",
+    "66": "raccoon",
+    "67": "ray",
+    "68": "road",
+    "69": "rocket",
+    "70": "rose",
+    "71": "sea",
+    "72": "seal",
+    "73": "shark",
+    "74": "shrew",
+    "75": "skunk",
+    "76": "skyscraper",
+    "77": "snail",
+    "78": "snake",
+    "79": "spider",
+    "80": "squirrel",
+    "81": "streetcar",
+    "82": "sunflower",
+    "83": "sweet_pepper",
+    "84": "table",
+    "85": "tank",
+    "86": "telephone",
+    "87": "television",
+    "88": "tiger",
+    "89": "tractor",
+    "90": "train",
+    "91": "trout",
+    "92": "tulip",
+    "93": "turtle",
+    "94": "wardrobe",
+    "95": "whale",
+    "96": "willow_tree",
+    "97": "wolf",
+    "98": "woman",
+    "99": "worm"
+  },
+  "label2id": {
+    "apple": 0,
+    "aquarium_fish": 1,
+    "baby": 2,
+    "bear": 3,
+    "beaver": 4,
+    "bed": 5,
+    "bee": 6,
+    "beetle": 7,
+    "bicycle": 8,
+    "bottle": 9,
+    "bowl": 10,
+    "boy": 11,
+    "bridge": 12,
+    "bus": 13,
+    "butterfly": 14,
+    "camel": 15,
+    "can": 16,
+    "castle": 17,
+    "caterpillar": 18,
+    "cattle": 19,
+    "chair": 20,
+    "chimpanzee": 21,
+    "clock": 22,
+    "cloud": 23,
+    "cockroach": 24,
+    "couch": 25,
+    "cra": 26,
+    "crocodile": 27,
+    "cup": 28,
+    "dinosaur": 29,
+    "dolphin": 30,
+    "elephant": 31,
+    "flatfish": 32,
+    "forest": 33,
+    "fox": 34,
+    "girl": 35,
+    "hamster": 36,
+    "house": 37,
+    "kangaroo": 38,
+    "keyboard": 39,
+    "lamp": 40,
+    "lawn_mower": 41,
+    "leopard": 42,
+    "lion": 43,
+    "lizard": 44,
+    "lobster": 45,
+    "man": 46,
+    "maple_tree": 47,
+    "motorcycle": 48,
+    "mountain": 49,
+    "mouse": 50,
+    "mushroom": 51,
+    "oak_tree": 52,
+    "orange": 53,
+    "orchid": 54,
+    "otter": 55,
+    "palm_tree": 56,
+    "pear": 57,
+    "pickup_truck": 58,
+    "pine_tree": 59,
+    "plain": 60,
+    "plate": 61,
+    "poppy": 62,
+    "porcupine": 63,
+    "possum": 64,
+    "rabbit": 65,
+    "raccoon": 66,
+    "ray": 67,
+    "road": 68,
+    "rocket": 69,
+    "rose": 70,
+    "sea": 71,
+    "seal": 72,
+    "shark": 73,
+    "shrew": 74,
+    "skunk": 75,
+    "skyscraper": 76,
+    "snail": 77,
+    "snake": 78,
+    "spider": 79,
+    "squirrel": 80,
+    "streetcar": 81,
+    "sunflower": 82,
+    "sweet_pepper": 83,
+    "table": 84,
+    "tank": 85,
+    "telephone": 86,
+    "television": 87,
+    "tiger": 88,
+    "tractor": 89,
+    "train": 90,
+    "trout": 91,
+    "tulip": 92,
+    "turtle": 93,
+    "wardrobe": 94,
+    "whale": 95,
+    "willow_tree": 96,
+    "wolf": 97,
+    "woman": 98,
+    "worm": 99
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-cifar100-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet18-cifar100-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-cifar100-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-cifar100-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/README.md b/resnet18-cifar100-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..3fa142b2049c64c95234119ce05fa6e9e4cfa9fb
--- /dev/null
+++ b/resnet18-cifar100-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar100.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: cifar100
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: train
+type: transformers
+val_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: test
+```
+
diff --git a/resnet18-cifar100-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/config.json b/resnet18-cifar100-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..5c3f41b9ed6c00df33ffaef448e5b6c8ac8a8d65
--- /dev/null
+++ b/resnet18-cifar100-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,243 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "apple",
+    "1": "aquarium_fish",
+    "2": "baby",
+    "3": "bear",
+    "4": "beaver",
+    "5": "bed",
+    "6": "bee",
+    "7": "beetle",
+    "8": "bicycle",
+    "9": "bottle",
+    "10": "bowl",
+    "11": "boy",
+    "12": "bridge",
+    "13": "bus",
+    "14": "butterfly",
+    "15": "camel",
+    "16": "can",
+    "17": "castle",
+    "18": "caterpillar",
+    "19": "cattle",
+    "20": "chair",
+    "21": "chimpanzee",
+    "22": "clock",
+    "23": "cloud",
+    "24": "cockroach",
+    "25": "couch",
+    "26": "cra",
+    "27": "crocodile",
+    "28": "cup",
+    "29": "dinosaur",
+    "30": "dolphin",
+    "31": "elephant",
+    "32": "flatfish",
+    "33": "forest",
+    "34": "fox",
+    "35": "girl",
+    "36": "hamster",
+    "37": "house",
+    "38": "kangaroo",
+    "39": "keyboard",
+    "40": "lamp",
+    "41": "lawn_mower",
+    "42": "leopard",
+    "43": "lion",
+    "44": "lizard",
+    "45": "lobster",
+    "46": "man",
+    "47": "maple_tree",
+    "48": "motorcycle",
+    "49": "mountain",
+    "50": "mouse",
+    "51": "mushroom",
+    "52": "oak_tree",
+    "53": "orange",
+    "54": "orchid",
+    "55": "otter",
+    "56": "palm_tree",
+    "57": "pear",
+    "58": "pickup_truck",
+    "59": "pine_tree",
+    "60": "plain",
+    "61": "plate",
+    "62": "poppy",
+    "63": "porcupine",
+    "64": "possum",
+    "65": "rabbit",
+    "66": "raccoon",
+    "67": "ray",
+    "68": "road",
+    "69": "rocket",
+    "70": "rose",
+    "71": "sea",
+    "72": "seal",
+    "73": "shark",
+    "74": "shrew",
+    "75": "skunk",
+    "76": "skyscraper",
+    "77": "snail",
+    "78": "snake",
+    "79": "spider",
+    "80": "squirrel",
+    "81": "streetcar",
+    "82": "sunflower",
+    "83": "sweet_pepper",
+    "84": "table",
+    "85": "tank",
+    "86": "telephone",
+    "87": "television",
+    "88": "tiger",
+    "89": "tractor",
+    "90": "train",
+    "91": "trout",
+    "92": "tulip",
+    "93": "turtle",
+    "94": "wardrobe",
+    "95": "whale",
+    "96": "willow_tree",
+    "97": "wolf",
+    "98": "woman",
+    "99": "worm"
+  },
+  "label2id": {
+    "apple": 0,
+    "aquarium_fish": 1,
+    "baby": 2,
+    "bear": 3,
+    "beaver": 4,
+    "bed": 5,
+    "bee": 6,
+    "beetle": 7,
+    "bicycle": 8,
+    "bottle": 9,
+    "bowl": 10,
+    "boy": 11,
+    "bridge": 12,
+    "bus": 13,
+    "butterfly": 14,
+    "camel": 15,
+    "can": 16,
+    "castle": 17,
+    "caterpillar": 18,
+    "cattle": 19,
+    "chair": 20,
+    "chimpanzee": 21,
+    "clock": 22,
+    "cloud": 23,
+    "cockroach": 24,
+    "couch": 25,
+    "cra": 26,
+    "crocodile": 27,
+    "cup": 28,
+    "dinosaur": 29,
+    "dolphin": 30,
+    "elephant": 31,
+    "flatfish": 32,
+    "forest": 33,
+    "fox": 34,
+    "girl": 35,
+    "hamster": 36,
+    "house": 37,
+    "kangaroo": 38,
+    "keyboard": 39,
+    "lamp": 40,
+    "lawn_mower": 41,
+    "leopard": 42,
+    "lion": 43,
+    "lizard": 44,
+    "lobster": 45,
+    "man": 46,
+    "maple_tree": 47,
+    "motorcycle": 48,
+    "mountain": 49,
+    "mouse": 50,
+    "mushroom": 51,
+    "oak_tree": 52,
+    "orange": 53,
+    "orchid": 54,
+    "otter": 55,
+    "palm_tree": 56,
+    "pear": 57,
+    "pickup_truck": 58,
+    "pine_tree": 59,
+    "plain": 60,
+    "plate": 61,
+    "poppy": 62,
+    "porcupine": 63,
+    "possum": 64,
+    "rabbit": 65,
+    "raccoon": 66,
+    "ray": 67,
+    "road": 68,
+    "rocket": 69,
+    "rose": 70,
+    "sea": 71,
+    "seal": 72,
+    "shark": 73,
+    "shrew": 74,
+    "skunk": 75,
+    "skyscraper": 76,
+    "snail": 77,
+    "snake": 78,
+    "spider": 79,
+    "squirrel": 80,
+    "streetcar": 81,
+    "sunflower": 82,
+    "sweet_pepper": 83,
+    "table": 84,
+    "tank": 85,
+    "telephone": 86,
+    "television": 87,
+    "tiger": 88,
+    "tractor": 89,
+    "train": 90,
+    "trout": 91,
+    "tulip": 92,
+    "turtle": 93,
+    "wardrobe": 94,
+    "whale": 95,
+    "willow_tree": 96,
+    "wolf": 97,
+    "woman": 98,
+    "worm": 99
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-cifar100-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet18-cifar100-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-cifar100-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.8-4000/README.md b/resnet18-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.8-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..a7f40b79c93196b16faec66aef791f8d4c02aefb
--- /dev/null
+++ b/resnet18-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.8-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar100.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: cifar100
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: train
+type: transformers
+val_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: test
+```
+
diff --git a/resnet18-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.8-4000/config.json b/resnet18-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.8-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..5c3f41b9ed6c00df33ffaef448e5b6c8ac8a8d65
--- /dev/null
+++ b/resnet18-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.8-4000/config.json
@@ -0,0 +1,243 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "apple",
+    "1": "aquarium_fish",
+    "2": "baby",
+    "3": "bear",
+    "4": "beaver",
+    "5": "bed",
+    "6": "bee",
+    "7": "beetle",
+    "8": "bicycle",
+    "9": "bottle",
+    "10": "bowl",
+    "11": "boy",
+    "12": "bridge",
+    "13": "bus",
+    "14": "butterfly",
+    "15": "camel",
+    "16": "can",
+    "17": "castle",
+    "18": "caterpillar",
+    "19": "cattle",
+    "20": "chair",
+    "21": "chimpanzee",
+    "22": "clock",
+    "23": "cloud",
+    "24": "cockroach",
+    "25": "couch",
+    "26": "cra",
+    "27": "crocodile",
+    "28": "cup",
+    "29": "dinosaur",
+    "30": "dolphin",
+    "31": "elephant",
+    "32": "flatfish",
+    "33": "forest",
+    "34": "fox",
+    "35": "girl",
+    "36": "hamster",
+    "37": "house",
+    "38": "kangaroo",
+    "39": "keyboard",
+    "40": "lamp",
+    "41": "lawn_mower",
+    "42": "leopard",
+    "43": "lion",
+    "44": "lizard",
+    "45": "lobster",
+    "46": "man",
+    "47": "maple_tree",
+    "48": "motorcycle",
+    "49": "mountain",
+    "50": "mouse",
+    "51": "mushroom",
+    "52": "oak_tree",
+    "53": "orange",
+    "54": "orchid",
+    "55": "otter",
+    "56": "palm_tree",
+    "57": "pear",
+    "58": "pickup_truck",
+    "59": "pine_tree",
+    "60": "plain",
+    "61": "plate",
+    "62": "poppy",
+    "63": "porcupine",
+    "64": "possum",
+    "65": "rabbit",
+    "66": "raccoon",
+    "67": "ray",
+    "68": "road",
+    "69": "rocket",
+    "70": "rose",
+    "71": "sea",
+    "72": "seal",
+    "73": "shark",
+    "74": "shrew",
+    "75": "skunk",
+    "76": "skyscraper",
+    "77": "snail",
+    "78": "snake",
+    "79": "spider",
+    "80": "squirrel",
+    "81": "streetcar",
+    "82": "sunflower",
+    "83": "sweet_pepper",
+    "84": "table",
+    "85": "tank",
+    "86": "telephone",
+    "87": "television",
+    "88": "tiger",
+    "89": "tractor",
+    "90": "train",
+    "91": "trout",
+    "92": "tulip",
+    "93": "turtle",
+    "94": "wardrobe",
+    "95": "whale",
+    "96": "willow_tree",
+    "97": "wolf",
+    "98": "woman",
+    "99": "worm"
+  },
+  "label2id": {
+    "apple": 0,
+    "aquarium_fish": 1,
+    "baby": 2,
+    "bear": 3,
+    "beaver": 4,
+    "bed": 5,
+    "bee": 6,
+    "beetle": 7,
+    "bicycle": 8,
+    "bottle": 9,
+    "bowl": 10,
+    "boy": 11,
+    "bridge": 12,
+    "bus": 13,
+    "butterfly": 14,
+    "camel": 15,
+    "can": 16,
+    "castle": 17,
+    "caterpillar": 18,
+    "cattle": 19,
+    "chair": 20,
+    "chimpanzee": 21,
+    "clock": 22,
+    "cloud": 23,
+    "cockroach": 24,
+    "couch": 25,
+    "cra": 26,
+    "crocodile": 27,
+    "cup": 28,
+    "dinosaur": 29,
+    "dolphin": 30,
+    "elephant": 31,
+    "flatfish": 32,
+    "forest": 33,
+    "fox": 34,
+    "girl": 35,
+    "hamster": 36,
+    "house": 37,
+    "kangaroo": 38,
+    "keyboard": 39,
+    "lamp": 40,
+    "lawn_mower": 41,
+    "leopard": 42,
+    "lion": 43,
+    "lizard": 44,
+    "lobster": 45,
+    "man": 46,
+    "maple_tree": 47,
+    "motorcycle": 48,
+    "mountain": 49,
+    "mouse": 50,
+    "mushroom": 51,
+    "oak_tree": 52,
+    "orange": 53,
+    "orchid": 54,
+    "otter": 55,
+    "palm_tree": 56,
+    "pear": 57,
+    "pickup_truck": 58,
+    "pine_tree": 59,
+    "plain": 60,
+    "plate": 61,
+    "poppy": 62,
+    "porcupine": 63,
+    "possum": 64,
+    "rabbit": 65,
+    "raccoon": 66,
+    "ray": 67,
+    "road": 68,
+    "rocket": 69,
+    "rose": 70,
+    "sea": 71,
+    "seal": 72,
+    "shark": 73,
+    "shrew": 74,
+    "skunk": 75,
+    "skyscraper": 76,
+    "snail": 77,
+    "snake": 78,
+    "spider": 79,
+    "squirrel": 80,
+    "streetcar": 81,
+    "sunflower": 82,
+    "sweet_pepper": 83,
+    "table": 84,
+    "tank": 85,
+    "telephone": 86,
+    "television": 87,
+    "tiger": 88,
+    "tractor": 89,
+    "train": 90,
+    "trout": 91,
+    "tulip": 92,
+    "turtle": 93,
+    "wardrobe": 94,
+    "whale": 95,
+    "willow_tree": 96,
+    "wolf": 97,
+    "woman": 98,
+    "worm": 99
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet18-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.8-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.8-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-cifar100-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/README.md b/resnet18-cifar100-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..f91c1f2e2c2032398259faa7de0c6e3c77a005b4
--- /dev/null
+++ b/resnet18-cifar100-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar100.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: cifar100
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: train
+type: transformers
+val_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: test
+```
+
diff --git a/resnet18-cifar100-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/config.json b/resnet18-cifar100-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..5c3f41b9ed6c00df33ffaef448e5b6c8ac8a8d65
--- /dev/null
+++ b/resnet18-cifar100-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/config.json
@@ -0,0 +1,243 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "apple",
+    "1": "aquarium_fish",
+    "2": "baby",
+    "3": "bear",
+    "4": "beaver",
+    "5": "bed",
+    "6": "bee",
+    "7": "beetle",
+    "8": "bicycle",
+    "9": "bottle",
+    "10": "bowl",
+    "11": "boy",
+    "12": "bridge",
+    "13": "bus",
+    "14": "butterfly",
+    "15": "camel",
+    "16": "can",
+    "17": "castle",
+    "18": "caterpillar",
+    "19": "cattle",
+    "20": "chair",
+    "21": "chimpanzee",
+    "22": "clock",
+    "23": "cloud",
+    "24": "cockroach",
+    "25": "couch",
+    "26": "cra",
+    "27": "crocodile",
+    "28": "cup",
+    "29": "dinosaur",
+    "30": "dolphin",
+    "31": "elephant",
+    "32": "flatfish",
+    "33": "forest",
+    "34": "fox",
+    "35": "girl",
+    "36": "hamster",
+    "37": "house",
+    "38": "kangaroo",
+    "39": "keyboard",
+    "40": "lamp",
+    "41": "lawn_mower",
+    "42": "leopard",
+    "43": "lion",
+    "44": "lizard",
+    "45": "lobster",
+    "46": "man",
+    "47": "maple_tree",
+    "48": "motorcycle",
+    "49": "mountain",
+    "50": "mouse",
+    "51": "mushroom",
+    "52": "oak_tree",
+    "53": "orange",
+    "54": "orchid",
+    "55": "otter",
+    "56": "palm_tree",
+    "57": "pear",
+    "58": "pickup_truck",
+    "59": "pine_tree",
+    "60": "plain",
+    "61": "plate",
+    "62": "poppy",
+    "63": "porcupine",
+    "64": "possum",
+    "65": "rabbit",
+    "66": "raccoon",
+    "67": "ray",
+    "68": "road",
+    "69": "rocket",
+    "70": "rose",
+    "71": "sea",
+    "72": "seal",
+    "73": "shark",
+    "74": "shrew",
+    "75": "skunk",
+    "76": "skyscraper",
+    "77": "snail",
+    "78": "snake",
+    "79": "spider",
+    "80": "squirrel",
+    "81": "streetcar",
+    "82": "sunflower",
+    "83": "sweet_pepper",
+    "84": "table",
+    "85": "tank",
+    "86": "telephone",
+    "87": "television",
+    "88": "tiger",
+    "89": "tractor",
+    "90": "train",
+    "91": "trout",
+    "92": "tulip",
+    "93": "turtle",
+    "94": "wardrobe",
+    "95": "whale",
+    "96": "willow_tree",
+    "97": "wolf",
+    "98": "woman",
+    "99": "worm"
+  },
+  "label2id": {
+    "apple": 0,
+    "aquarium_fish": 1,
+    "baby": 2,
+    "bear": 3,
+    "beaver": 4,
+    "bed": 5,
+    "bee": 6,
+    "beetle": 7,
+    "bicycle": 8,
+    "bottle": 9,
+    "bowl": 10,
+    "boy": 11,
+    "bridge": 12,
+    "bus": 13,
+    "butterfly": 14,
+    "camel": 15,
+    "can": 16,
+    "castle": 17,
+    "caterpillar": 18,
+    "cattle": 19,
+    "chair": 20,
+    "chimpanzee": 21,
+    "clock": 22,
+    "cloud": 23,
+    "cockroach": 24,
+    "couch": 25,
+    "cra": 26,
+    "crocodile": 27,
+    "cup": 28,
+    "dinosaur": 29,
+    "dolphin": 30,
+    "elephant": 31,
+    "flatfish": 32,
+    "forest": 33,
+    "fox": 34,
+    "girl": 35,
+    "hamster": 36,
+    "house": 37,
+    "kangaroo": 38,
+    "keyboard": 39,
+    "lamp": 40,
+    "lawn_mower": 41,
+    "leopard": 42,
+    "lion": 43,
+    "lizard": 44,
+    "lobster": 45,
+    "man": 46,
+    "maple_tree": 47,
+    "motorcycle": 48,
+    "mountain": 49,
+    "mouse": 50,
+    "mushroom": 51,
+    "oak_tree": 52,
+    "orange": 53,
+    "orchid": 54,
+    "otter": 55,
+    "palm_tree": 56,
+    "pear": 57,
+    "pickup_truck": 58,
+    "pine_tree": 59,
+    "plain": 60,
+    "plate": 61,
+    "poppy": 62,
+    "porcupine": 63,
+    "possum": 64,
+    "rabbit": 65,
+    "raccoon": 66,
+    "ray": 67,
+    "road": 68,
+    "rocket": 69,
+    "rose": 70,
+    "sea": 71,
+    "seal": 72,
+    "shark": 73,
+    "shrew": 74,
+    "skunk": 75,
+    "skyscraper": 76,
+    "snail": 77,
+    "snake": 78,
+    "spider": 79,
+    "squirrel": 80,
+    "streetcar": 81,
+    "sunflower": 82,
+    "sweet_pepper": 83,
+    "table": 84,
+    "tank": 85,
+    "telephone": 86,
+    "television": 87,
+    "tiger": 88,
+    "tractor": 89,
+    "train": 90,
+    "trout": 91,
+    "tulip": 92,
+    "turtle": 93,
+    "wardrobe": 94,
+    "whale": 95,
+    "willow_tree": 96,
+    "wolf": 97,
+    "woman": 98,
+    "worm": 99
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-cifar100-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet18-cifar100-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-cifar100-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-dtd-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/README.md b/resnet18-dtd-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..4d6608089a42cbf9b27dfc5c59cedd4e5c0011e1
--- /dev/null
+++ b/resnet18-dtd-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset dtd.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: dtd
+    pretrained: true
+test_datasets: null
+train_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: train
+type: transformers
+val_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: test
+```
+
diff --git a/resnet18-dtd-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/config.json b/resnet18-dtd-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..f2ce6cd6d95d0a7c1905aabe792d0a5c4e2f515a
--- /dev/null
+++ b/resnet18-dtd-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,137 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "banded",
+    "1": "blotchy",
+    "2": "braided",
+    "3": "bubbly",
+    "4": "bumpy",
+    "5": "chequered",
+    "6": "cobwebbed",
+    "7": "cracked",
+    "8": "crosshatched",
+    "9": "crystalline",
+    "10": "dotted",
+    "11": "fibrous",
+    "12": "flecked",
+    "13": "freckled",
+    "14": "frilly",
+    "15": "gauzy",
+    "16": "grid",
+    "17": "grooved",
+    "18": "honeycombed",
+    "19": "interlaced",
+    "20": "knitted",
+    "21": "lacelike",
+    "22": "lined",
+    "23": "marbled",
+    "24": "matted",
+    "25": "meshed",
+    "26": "paisley",
+    "27": "perforated",
+    "28": "pitted",
+    "29": "pleated",
+    "30": "polka-dotted",
+    "31": "porous",
+    "32": "potholed",
+    "33": "scaly",
+    "34": "smeared",
+    "35": "spiralled",
+    "36": "sprinkled",
+    "37": "stained",
+    "38": "stratified",
+    "39": "striped",
+    "40": "studded",
+    "41": "swirly",
+    "42": "veined",
+    "43": "waffled",
+    "44": "woven",
+    "45": "wrinkled",
+    "46": "zigzagged"
+  },
+  "label2id": {
+    "banded": 0,
+    "blotchy": 1,
+    "braided": 2,
+    "bubbly": 3,
+    "bumpy": 4,
+    "chequered": 5,
+    "cobwebbed": 6,
+    "cracked": 7,
+    "crosshatched": 8,
+    "crystalline": 9,
+    "dotted": 10,
+    "fibrous": 11,
+    "flecked": 12,
+    "freckled": 13,
+    "frilly": 14,
+    "gauzy": 15,
+    "grid": 16,
+    "grooved": 17,
+    "honeycombed": 18,
+    "interlaced": 19,
+    "knitted": 20,
+    "lacelike": 21,
+    "lined": 22,
+    "marbled": 23,
+    "matted": 24,
+    "meshed": 25,
+    "paisley": 26,
+    "perforated": 27,
+    "pitted": 28,
+    "pleated": 29,
+    "polka-dotted": 30,
+    "porous": 31,
+    "potholed": 32,
+    "scaly": 33,
+    "smeared": 34,
+    "spiralled": 35,
+    "sprinkled": 36,
+    "stained": 37,
+    "stratified": 38,
+    "striped": 39,
+    "studded": 40,
+    "swirly": 41,
+    "veined": 42,
+    "waffled": 43,
+    "woven": 44,
+    "wrinkled": 45,
+    "zigzagged": 46
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-dtd-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet18-dtd-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-dtd-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-dtd-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/README.md b/resnet18-dtd-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..eb156b47429d691d2e9b9b313a3876f724e75687
--- /dev/null
+++ b/resnet18-dtd-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset dtd.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: dtd
+    pretrained: true
+test_datasets: null
+train_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: train
+type: transformers
+val_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: test
+```
+
diff --git a/resnet18-dtd-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/config.json b/resnet18-dtd-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..f2ce6cd6d95d0a7c1905aabe792d0a5c4e2f515a
--- /dev/null
+++ b/resnet18-dtd-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,137 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "banded",
+    "1": "blotchy",
+    "2": "braided",
+    "3": "bubbly",
+    "4": "bumpy",
+    "5": "chequered",
+    "6": "cobwebbed",
+    "7": "cracked",
+    "8": "crosshatched",
+    "9": "crystalline",
+    "10": "dotted",
+    "11": "fibrous",
+    "12": "flecked",
+    "13": "freckled",
+    "14": "frilly",
+    "15": "gauzy",
+    "16": "grid",
+    "17": "grooved",
+    "18": "honeycombed",
+    "19": "interlaced",
+    "20": "knitted",
+    "21": "lacelike",
+    "22": "lined",
+    "23": "marbled",
+    "24": "matted",
+    "25": "meshed",
+    "26": "paisley",
+    "27": "perforated",
+    "28": "pitted",
+    "29": "pleated",
+    "30": "polka-dotted",
+    "31": "porous",
+    "32": "potholed",
+    "33": "scaly",
+    "34": "smeared",
+    "35": "spiralled",
+    "36": "sprinkled",
+    "37": "stained",
+    "38": "stratified",
+    "39": "striped",
+    "40": "studded",
+    "41": "swirly",
+    "42": "veined",
+    "43": "waffled",
+    "44": "woven",
+    "45": "wrinkled",
+    "46": "zigzagged"
+  },
+  "label2id": {
+    "banded": 0,
+    "blotchy": 1,
+    "braided": 2,
+    "bubbly": 3,
+    "bumpy": 4,
+    "chequered": 5,
+    "cobwebbed": 6,
+    "cracked": 7,
+    "crosshatched": 8,
+    "crystalline": 9,
+    "dotted": 10,
+    "fibrous": 11,
+    "flecked": 12,
+    "freckled": 13,
+    "frilly": 14,
+    "gauzy": 15,
+    "grid": 16,
+    "grooved": 17,
+    "honeycombed": 18,
+    "interlaced": 19,
+    "knitted": 20,
+    "lacelike": 21,
+    "lined": 22,
+    "marbled": 23,
+    "matted": 24,
+    "meshed": 25,
+    "paisley": 26,
+    "perforated": 27,
+    "pitted": 28,
+    "pleated": 29,
+    "polka-dotted": 30,
+    "porous": 31,
+    "potholed": 32,
+    "scaly": 33,
+    "smeared": 34,
+    "spiralled": 35,
+    "sprinkled": 36,
+    "stained": 37,
+    "stratified": 38,
+    "striped": 39,
+    "studded": 40,
+    "swirly": 41,
+    "veined": 42,
+    "waffled": 43,
+    "woven": 44,
+    "wrinkled": 45,
+    "zigzagged": 46
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-dtd-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet18-dtd-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-dtd-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-dtd-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/README.md b/resnet18-dtd-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..7f0c77a8398e0772a527ba0ac38896a128beb8cb
--- /dev/null
+++ b/resnet18-dtd-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset dtd.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: dtd
+    pretrained: true
+test_datasets: null
+train_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: train
+type: transformers
+val_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: test
+```
+
diff --git a/resnet18-dtd-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/config.json b/resnet18-dtd-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..f2ce6cd6d95d0a7c1905aabe792d0a5c4e2f515a
--- /dev/null
+++ b/resnet18-dtd-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/config.json
@@ -0,0 +1,137 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "banded",
+    "1": "blotchy",
+    "2": "braided",
+    "3": "bubbly",
+    "4": "bumpy",
+    "5": "chequered",
+    "6": "cobwebbed",
+    "7": "cracked",
+    "8": "crosshatched",
+    "9": "crystalline",
+    "10": "dotted",
+    "11": "fibrous",
+    "12": "flecked",
+    "13": "freckled",
+    "14": "frilly",
+    "15": "gauzy",
+    "16": "grid",
+    "17": "grooved",
+    "18": "honeycombed",
+    "19": "interlaced",
+    "20": "knitted",
+    "21": "lacelike",
+    "22": "lined",
+    "23": "marbled",
+    "24": "matted",
+    "25": "meshed",
+    "26": "paisley",
+    "27": "perforated",
+    "28": "pitted",
+    "29": "pleated",
+    "30": "polka-dotted",
+    "31": "porous",
+    "32": "potholed",
+    "33": "scaly",
+    "34": "smeared",
+    "35": "spiralled",
+    "36": "sprinkled",
+    "37": "stained",
+    "38": "stratified",
+    "39": "striped",
+    "40": "studded",
+    "41": "swirly",
+    "42": "veined",
+    "43": "waffled",
+    "44": "woven",
+    "45": "wrinkled",
+    "46": "zigzagged"
+  },
+  "label2id": {
+    "banded": 0,
+    "blotchy": 1,
+    "braided": 2,
+    "bubbly": 3,
+    "bumpy": 4,
+    "chequered": 5,
+    "cobwebbed": 6,
+    "cracked": 7,
+    "crosshatched": 8,
+    "crystalline": 9,
+    "dotted": 10,
+    "fibrous": 11,
+    "flecked": 12,
+    "freckled": 13,
+    "frilly": 14,
+    "gauzy": 15,
+    "grid": 16,
+    "grooved": 17,
+    "honeycombed": 18,
+    "interlaced": 19,
+    "knitted": 20,
+    "lacelike": 21,
+    "lined": 22,
+    "marbled": 23,
+    "matted": 24,
+    "meshed": 25,
+    "paisley": 26,
+    "perforated": 27,
+    "pitted": 28,
+    "pleated": 29,
+    "polka-dotted": 30,
+    "porous": 31,
+    "potholed": 32,
+    "scaly": 33,
+    "smeared": 34,
+    "spiralled": 35,
+    "sprinkled": 36,
+    "stained": 37,
+    "stratified": 38,
+    "striped": 39,
+    "studded": 40,
+    "swirly": 41,
+    "veined": 42,
+    "waffled": 43,
+    "woven": 44,
+    "wrinkled": 45,
+    "zigzagged": 46
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-dtd-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet18-dtd-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-dtd-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-dtd-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/README.md b/resnet18-dtd-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..6047184262550b35cc6bb9bef168e64b546a9804
--- /dev/null
+++ b/resnet18-dtd-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset dtd.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: dtd
+    pretrained: true
+test_datasets: null
+train_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: train
+type: transformers
+val_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: test
+```
+
diff --git a/resnet18-dtd-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/config.json b/resnet18-dtd-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..f2ce6cd6d95d0a7c1905aabe792d0a5c4e2f515a
--- /dev/null
+++ b/resnet18-dtd-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,137 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "banded",
+    "1": "blotchy",
+    "2": "braided",
+    "3": "bubbly",
+    "4": "bumpy",
+    "5": "chequered",
+    "6": "cobwebbed",
+    "7": "cracked",
+    "8": "crosshatched",
+    "9": "crystalline",
+    "10": "dotted",
+    "11": "fibrous",
+    "12": "flecked",
+    "13": "freckled",
+    "14": "frilly",
+    "15": "gauzy",
+    "16": "grid",
+    "17": "grooved",
+    "18": "honeycombed",
+    "19": "interlaced",
+    "20": "knitted",
+    "21": "lacelike",
+    "22": "lined",
+    "23": "marbled",
+    "24": "matted",
+    "25": "meshed",
+    "26": "paisley",
+    "27": "perforated",
+    "28": "pitted",
+    "29": "pleated",
+    "30": "polka-dotted",
+    "31": "porous",
+    "32": "potholed",
+    "33": "scaly",
+    "34": "smeared",
+    "35": "spiralled",
+    "36": "sprinkled",
+    "37": "stained",
+    "38": "stratified",
+    "39": "striped",
+    "40": "studded",
+    "41": "swirly",
+    "42": "veined",
+    "43": "waffled",
+    "44": "woven",
+    "45": "wrinkled",
+    "46": "zigzagged"
+  },
+  "label2id": {
+    "banded": 0,
+    "blotchy": 1,
+    "braided": 2,
+    "bubbly": 3,
+    "bumpy": 4,
+    "chequered": 5,
+    "cobwebbed": 6,
+    "cracked": 7,
+    "crosshatched": 8,
+    "crystalline": 9,
+    "dotted": 10,
+    "fibrous": 11,
+    "flecked": 12,
+    "freckled": 13,
+    "frilly": 14,
+    "gauzy": 15,
+    "grid": 16,
+    "grooved": 17,
+    "honeycombed": 18,
+    "interlaced": 19,
+    "knitted": 20,
+    "lacelike": 21,
+    "lined": 22,
+    "marbled": 23,
+    "matted": 24,
+    "meshed": 25,
+    "paisley": 26,
+    "perforated": 27,
+    "pitted": 28,
+    "pleated": 29,
+    "polka-dotted": 30,
+    "porous": 31,
+    "potholed": 32,
+    "scaly": 33,
+    "smeared": 34,
+    "spiralled": 35,
+    "sprinkled": 36,
+    "stained": 37,
+    "stratified": 38,
+    "striped": 39,
+    "studded": 40,
+    "swirly": 41,
+    "veined": 42,
+    "waffled": 43,
+    "woven": 44,
+    "wrinkled": 45,
+    "zigzagged": 46
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-dtd-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet18-dtd-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-dtd-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-dtd-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/README.md b/resnet18-dtd-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..159e4c887b3a318c51428571f2609be8875899cd
--- /dev/null
+++ b/resnet18-dtd-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset dtd.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: dtd
+    pretrained: true
+test_datasets: null
+train_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: train
+type: transformers
+val_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: test
+```
+
diff --git a/resnet18-dtd-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/config.json b/resnet18-dtd-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..f2ce6cd6d95d0a7c1905aabe792d0a5c4e2f515a
--- /dev/null
+++ b/resnet18-dtd-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/config.json
@@ -0,0 +1,137 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "banded",
+    "1": "blotchy",
+    "2": "braided",
+    "3": "bubbly",
+    "4": "bumpy",
+    "5": "chequered",
+    "6": "cobwebbed",
+    "7": "cracked",
+    "8": "crosshatched",
+    "9": "crystalline",
+    "10": "dotted",
+    "11": "fibrous",
+    "12": "flecked",
+    "13": "freckled",
+    "14": "frilly",
+    "15": "gauzy",
+    "16": "grid",
+    "17": "grooved",
+    "18": "honeycombed",
+    "19": "interlaced",
+    "20": "knitted",
+    "21": "lacelike",
+    "22": "lined",
+    "23": "marbled",
+    "24": "matted",
+    "25": "meshed",
+    "26": "paisley",
+    "27": "perforated",
+    "28": "pitted",
+    "29": "pleated",
+    "30": "polka-dotted",
+    "31": "porous",
+    "32": "potholed",
+    "33": "scaly",
+    "34": "smeared",
+    "35": "spiralled",
+    "36": "sprinkled",
+    "37": "stained",
+    "38": "stratified",
+    "39": "striped",
+    "40": "studded",
+    "41": "swirly",
+    "42": "veined",
+    "43": "waffled",
+    "44": "woven",
+    "45": "wrinkled",
+    "46": "zigzagged"
+  },
+  "label2id": {
+    "banded": 0,
+    "blotchy": 1,
+    "braided": 2,
+    "bubbly": 3,
+    "bumpy": 4,
+    "chequered": 5,
+    "cobwebbed": 6,
+    "cracked": 7,
+    "crosshatched": 8,
+    "crystalline": 9,
+    "dotted": 10,
+    "fibrous": 11,
+    "flecked": 12,
+    "freckled": 13,
+    "frilly": 14,
+    "gauzy": 15,
+    "grid": 16,
+    "grooved": 17,
+    "honeycombed": 18,
+    "interlaced": 19,
+    "knitted": 20,
+    "lacelike": 21,
+    "lined": 22,
+    "marbled": 23,
+    "matted": 24,
+    "meshed": 25,
+    "paisley": 26,
+    "perforated": 27,
+    "pitted": 28,
+    "pleated": 29,
+    "polka-dotted": 30,
+    "porous": 31,
+    "potholed": 32,
+    "scaly": 33,
+    "smeared": 34,
+    "spiralled": 35,
+    "sprinkled": 36,
+    "stained": 37,
+    "stratified": 38,
+    "striped": 39,
+    "studded": 40,
+    "swirly": 41,
+    "veined": 42,
+    "waffled": 43,
+    "woven": 44,
+    "wrinkled": 45,
+    "zigzagged": 46
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-dtd-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet18-dtd-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-dtd-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/README.md b/resnet18-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..39acef3b25709613adf9ffd078b2af300ec1eec3
--- /dev/null
+++ b/resnet18-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset dtd.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: dtd
+    pretrained: true
+test_datasets: null
+train_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: train
+type: transformers
+val_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: test
+```
+
diff --git a/resnet18-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/config.json b/resnet18-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..f2ce6cd6d95d0a7c1905aabe792d0a5c4e2f515a
--- /dev/null
+++ b/resnet18-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,137 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "banded",
+    "1": "blotchy",
+    "2": "braided",
+    "3": "bubbly",
+    "4": "bumpy",
+    "5": "chequered",
+    "6": "cobwebbed",
+    "7": "cracked",
+    "8": "crosshatched",
+    "9": "crystalline",
+    "10": "dotted",
+    "11": "fibrous",
+    "12": "flecked",
+    "13": "freckled",
+    "14": "frilly",
+    "15": "gauzy",
+    "16": "grid",
+    "17": "grooved",
+    "18": "honeycombed",
+    "19": "interlaced",
+    "20": "knitted",
+    "21": "lacelike",
+    "22": "lined",
+    "23": "marbled",
+    "24": "matted",
+    "25": "meshed",
+    "26": "paisley",
+    "27": "perforated",
+    "28": "pitted",
+    "29": "pleated",
+    "30": "polka-dotted",
+    "31": "porous",
+    "32": "potholed",
+    "33": "scaly",
+    "34": "smeared",
+    "35": "spiralled",
+    "36": "sprinkled",
+    "37": "stained",
+    "38": "stratified",
+    "39": "striped",
+    "40": "studded",
+    "41": "swirly",
+    "42": "veined",
+    "43": "waffled",
+    "44": "woven",
+    "45": "wrinkled",
+    "46": "zigzagged"
+  },
+  "label2id": {
+    "banded": 0,
+    "blotchy": 1,
+    "braided": 2,
+    "bubbly": 3,
+    "bumpy": 4,
+    "chequered": 5,
+    "cobwebbed": 6,
+    "cracked": 7,
+    "crosshatched": 8,
+    "crystalline": 9,
+    "dotted": 10,
+    "fibrous": 11,
+    "flecked": 12,
+    "freckled": 13,
+    "frilly": 14,
+    "gauzy": 15,
+    "grid": 16,
+    "grooved": 17,
+    "honeycombed": 18,
+    "interlaced": 19,
+    "knitted": 20,
+    "lacelike": 21,
+    "lined": 22,
+    "marbled": 23,
+    "matted": 24,
+    "meshed": 25,
+    "paisley": 26,
+    "perforated": 27,
+    "pitted": 28,
+    "pleated": 29,
+    "polka-dotted": 30,
+    "porous": 31,
+    "potholed": 32,
+    "scaly": 33,
+    "smeared": 34,
+    "spiralled": 35,
+    "sprinkled": 36,
+    "stained": 37,
+    "stratified": 38,
+    "striped": 39,
+    "studded": 40,
+    "swirly": 41,
+    "veined": 42,
+    "waffled": 43,
+    "woven": 44,
+    "wrinkled": 45,
+    "zigzagged": 46
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet18-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-dtd-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-dtd-batch_size_64_lr_0.005_training_data_ratio_0.5-2000/README.md b/resnet18-dtd-batch_size_64_lr_0.005_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..11f8c92415116f6c5f2ba8250ce7913f2db05df7
--- /dev/null
+++ b/resnet18-dtd-batch_size_64_lr_0.005_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset dtd.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: dtd
+    pretrained: true
+test_datasets: null
+train_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: train
+type: transformers
+val_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: test
+```
+
diff --git a/resnet18-dtd-batch_size_64_lr_0.005_training_data_ratio_0.5-2000/config.json b/resnet18-dtd-batch_size_64_lr_0.005_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..f2ce6cd6d95d0a7c1905aabe792d0a5c4e2f515a
--- /dev/null
+++ b/resnet18-dtd-batch_size_64_lr_0.005_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,137 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "banded",
+    "1": "blotchy",
+    "2": "braided",
+    "3": "bubbly",
+    "4": "bumpy",
+    "5": "chequered",
+    "6": "cobwebbed",
+    "7": "cracked",
+    "8": "crosshatched",
+    "9": "crystalline",
+    "10": "dotted",
+    "11": "fibrous",
+    "12": "flecked",
+    "13": "freckled",
+    "14": "frilly",
+    "15": "gauzy",
+    "16": "grid",
+    "17": "grooved",
+    "18": "honeycombed",
+    "19": "interlaced",
+    "20": "knitted",
+    "21": "lacelike",
+    "22": "lined",
+    "23": "marbled",
+    "24": "matted",
+    "25": "meshed",
+    "26": "paisley",
+    "27": "perforated",
+    "28": "pitted",
+    "29": "pleated",
+    "30": "polka-dotted",
+    "31": "porous",
+    "32": "potholed",
+    "33": "scaly",
+    "34": "smeared",
+    "35": "spiralled",
+    "36": "sprinkled",
+    "37": "stained",
+    "38": "stratified",
+    "39": "striped",
+    "40": "studded",
+    "41": "swirly",
+    "42": "veined",
+    "43": "waffled",
+    "44": "woven",
+    "45": "wrinkled",
+    "46": "zigzagged"
+  },
+  "label2id": {
+    "banded": 0,
+    "blotchy": 1,
+    "braided": 2,
+    "bubbly": 3,
+    "bumpy": 4,
+    "chequered": 5,
+    "cobwebbed": 6,
+    "cracked": 7,
+    "crosshatched": 8,
+    "crystalline": 9,
+    "dotted": 10,
+    "fibrous": 11,
+    "flecked": 12,
+    "freckled": 13,
+    "frilly": 14,
+    "gauzy": 15,
+    "grid": 16,
+    "grooved": 17,
+    "honeycombed": 18,
+    "interlaced": 19,
+    "knitted": 20,
+    "lacelike": 21,
+    "lined": 22,
+    "marbled": 23,
+    "matted": 24,
+    "meshed": 25,
+    "paisley": 26,
+    "perforated": 27,
+    "pitted": 28,
+    "pleated": 29,
+    "polka-dotted": 30,
+    "porous": 31,
+    "potholed": 32,
+    "scaly": 33,
+    "smeared": 34,
+    "spiralled": 35,
+    "sprinkled": 36,
+    "stained": 37,
+    "stratified": 38,
+    "striped": 39,
+    "studded": 40,
+    "swirly": 41,
+    "veined": 42,
+    "waffled": 43,
+    "woven": 44,
+    "wrinkled": 45,
+    "zigzagged": 46
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-dtd-batch_size_64_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet18-dtd-batch_size_64_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-dtd-batch_size_64_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-emnist_letters-batch_size_128_lr_0.005_training_data_ratio_0.5-4000/README.md b/resnet18-emnist_letters-batch_size_128_lr_0.005_training_data_ratio_0.5-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..722439a0dea011686afb81156228d6c9acfee64d
--- /dev/null
+++ b/resnet18-emnist_letters-batch_size_128_lr_0.005_training_data_ratio_0.5-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset emnist_letters.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: emnist_letters
+    pretrained: true
+test_datasets: null
+train_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: train
+type: transformers
+val_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: test
+```
+
diff --git a/resnet18-emnist_letters-batch_size_128_lr_0.005_training_data_ratio_0.5-4000/config.json b/resnet18-emnist_letters-batch_size_128_lr_0.005_training_data_ratio_0.5-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..13f9e0905aba09ddfb07306023093f9a4322f7a7
--- /dev/null
+++ b/resnet18-emnist_letters-batch_size_128_lr_0.005_training_data_ratio_0.5-4000/config.json
@@ -0,0 +1,95 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "A",
+    "1": "B",
+    "2": "C",
+    "3": "D",
+    "4": "E",
+    "5": "F",
+    "6": "G",
+    "7": "H",
+    "8": "I",
+    "9": "J",
+    "10": "K",
+    "11": "L",
+    "12": "M",
+    "13": "N",
+    "14": "O",
+    "15": "P",
+    "16": "Q",
+    "17": "R",
+    "18": "S",
+    "19": "T",
+    "20": "U",
+    "21": "V",
+    "22": "W",
+    "23": "X",
+    "24": "Y",
+    "25": "Z"
+  },
+  "label2id": {
+    "A": 0,
+    "B": 1,
+    "C": 2,
+    "D": 3,
+    "E": 4,
+    "F": 5,
+    "G": 6,
+    "H": 7,
+    "I": 8,
+    "J": 9,
+    "K": 10,
+    "L": 11,
+    "M": 12,
+    "N": 13,
+    "O": 14,
+    "P": 15,
+    "Q": 16,
+    "R": 17,
+    "S": 18,
+    "T": 19,
+    "U": 20,
+    "V": 21,
+    "W": 22,
+    "X": 23,
+    "Y": 24,
+    "Z": 25
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-emnist_letters-batch_size_128_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet18-emnist_letters-batch_size_128_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-emnist_letters-batch_size_128_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-emnist_letters-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/README.md b/resnet18-emnist_letters-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..3c6a86067cd5df061444cdd2d7820e78a7b40e20
--- /dev/null
+++ b/resnet18-emnist_letters-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset emnist_letters.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: emnist_letters
+    pretrained: true
+test_datasets: null
+train_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: train
+type: transformers
+val_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: test
+```
+
diff --git a/resnet18-emnist_letters-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/config.json b/resnet18-emnist_letters-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..13f9e0905aba09ddfb07306023093f9a4322f7a7
--- /dev/null
+++ b/resnet18-emnist_letters-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,95 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "A",
+    "1": "B",
+    "2": "C",
+    "3": "D",
+    "4": "E",
+    "5": "F",
+    "6": "G",
+    "7": "H",
+    "8": "I",
+    "9": "J",
+    "10": "K",
+    "11": "L",
+    "12": "M",
+    "13": "N",
+    "14": "O",
+    "15": "P",
+    "16": "Q",
+    "17": "R",
+    "18": "S",
+    "19": "T",
+    "20": "U",
+    "21": "V",
+    "22": "W",
+    "23": "X",
+    "24": "Y",
+    "25": "Z"
+  },
+  "label2id": {
+    "A": 0,
+    "B": 1,
+    "C": 2,
+    "D": 3,
+    "E": 4,
+    "F": 5,
+    "G": 6,
+    "H": 7,
+    "I": 8,
+    "J": 9,
+    "K": 10,
+    "L": 11,
+    "M": 12,
+    "N": 13,
+    "O": 14,
+    "P": 15,
+    "Q": 16,
+    "R": 17,
+    "S": 18,
+    "T": 19,
+    "U": 20,
+    "V": 21,
+    "W": 22,
+    "X": 23,
+    "Y": 24,
+    "Z": 25
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-emnist_letters-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet18-emnist_letters-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-emnist_letters-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-emnist_letters-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/README.md b/resnet18-emnist_letters-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..3aa7a61ee53d0a5f7f0a93bb9b93a5e907010582
--- /dev/null
+++ b/resnet18-emnist_letters-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset emnist_letters.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: emnist_letters
+    pretrained: true
+test_datasets: null
+train_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: train
+type: transformers
+val_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: test
+```
+
diff --git a/resnet18-emnist_letters-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/config.json b/resnet18-emnist_letters-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..13f9e0905aba09ddfb07306023093f9a4322f7a7
--- /dev/null
+++ b/resnet18-emnist_letters-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/config.json
@@ -0,0 +1,95 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "A",
+    "1": "B",
+    "2": "C",
+    "3": "D",
+    "4": "E",
+    "5": "F",
+    "6": "G",
+    "7": "H",
+    "8": "I",
+    "9": "J",
+    "10": "K",
+    "11": "L",
+    "12": "M",
+    "13": "N",
+    "14": "O",
+    "15": "P",
+    "16": "Q",
+    "17": "R",
+    "18": "S",
+    "19": "T",
+    "20": "U",
+    "21": "V",
+    "22": "W",
+    "23": "X",
+    "24": "Y",
+    "25": "Z"
+  },
+  "label2id": {
+    "A": 0,
+    "B": 1,
+    "C": 2,
+    "D": 3,
+    "E": 4,
+    "F": 5,
+    "G": 6,
+    "H": 7,
+    "I": 8,
+    "J": 9,
+    "K": 10,
+    "L": 11,
+    "M": 12,
+    "N": 13,
+    "O": 14,
+    "P": 15,
+    "Q": 16,
+    "R": 17,
+    "S": 18,
+    "T": 19,
+    "U": 20,
+    "V": 21,
+    "W": 22,
+    "X": 23,
+    "Y": 24,
+    "Z": 25
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-emnist_letters-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet18-emnist_letters-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-emnist_letters-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/README.md b/resnet18-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..10fcbaa6928c6397b00f87354a15d35b23f62399
--- /dev/null
+++ b/resnet18-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset emnist_letters.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: emnist_letters
+    pretrained: true
+test_datasets: null
+train_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: train
+type: transformers
+val_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: test
+```
+
diff --git a/resnet18-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/config.json b/resnet18-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..13f9e0905aba09ddfb07306023093f9a4322f7a7
--- /dev/null
+++ b/resnet18-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/config.json
@@ -0,0 +1,95 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "A",
+    "1": "B",
+    "2": "C",
+    "3": "D",
+    "4": "E",
+    "5": "F",
+    "6": "G",
+    "7": "H",
+    "8": "I",
+    "9": "J",
+    "10": "K",
+    "11": "L",
+    "12": "M",
+    "13": "N",
+    "14": "O",
+    "15": "P",
+    "16": "Q",
+    "17": "R",
+    "18": "S",
+    "19": "T",
+    "20": "U",
+    "21": "V",
+    "22": "W",
+    "23": "X",
+    "24": "Y",
+    "25": "Z"
+  },
+  "label2id": {
+    "A": 0,
+    "B": 1,
+    "C": 2,
+    "D": 3,
+    "E": 4,
+    "F": 5,
+    "G": 6,
+    "H": 7,
+    "I": 8,
+    "J": 9,
+    "K": 10,
+    "L": 11,
+    "M": 12,
+    "N": 13,
+    "O": 14,
+    "P": 15,
+    "Q": 16,
+    "R": 17,
+    "S": 18,
+    "T": 19,
+    "U": 20,
+    "V": 21,
+    "W": 22,
+    "X": 23,
+    "Y": 24,
+    "Z": 25
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet18-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/README.md b/resnet18-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..541a1acdf74e8e74c6c6ae2c0407ad5a257e668d
--- /dev/null
+++ b/resnet18-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset emnist_letters.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: emnist_letters
+    pretrained: true
+test_datasets: null
+train_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: train
+type: transformers
+val_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: test
+```
+
diff --git a/resnet18-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/config.json b/resnet18-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..13f9e0905aba09ddfb07306023093f9a4322f7a7
--- /dev/null
+++ b/resnet18-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,95 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "A",
+    "1": "B",
+    "2": "C",
+    "3": "D",
+    "4": "E",
+    "5": "F",
+    "6": "G",
+    "7": "H",
+    "8": "I",
+    "9": "J",
+    "10": "K",
+    "11": "L",
+    "12": "M",
+    "13": "N",
+    "14": "O",
+    "15": "P",
+    "16": "Q",
+    "17": "R",
+    "18": "S",
+    "19": "T",
+    "20": "U",
+    "21": "V",
+    "22": "W",
+    "23": "X",
+    "24": "Y",
+    "25": "Z"
+  },
+  "label2id": {
+    "A": 0,
+    "B": 1,
+    "C": 2,
+    "D": 3,
+    "E": 4,
+    "F": 5,
+    "G": 6,
+    "H": 7,
+    "I": 8,
+    "J": 9,
+    "K": 10,
+    "L": 11,
+    "M": 12,
+    "N": 13,
+    "O": 14,
+    "P": 15,
+    "Q": 16,
+    "R": 17,
+    "S": 18,
+    "T": 19,
+    "U": 20,
+    "V": 21,
+    "W": 22,
+    "X": 23,
+    "Y": 24,
+    "Z": 25
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet18-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-eurosat-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/README.md b/resnet18-eurosat-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..867d03b03deb546d1dcc41581261b832dc942860
--- /dev/null
+++ b/resnet18-eurosat-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset eurosat.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: eurosat
+    pretrained: true
+test_datasets: null
+train_datasets:
+  eurosat:
+    _target_: datasets.load_dataset
+    path: tanganke/eurosat
+    split: train
+type: transformers
+val_datasets:
+  eurosat:
+    _target_: datasets.load_dataset
+    path: tanganke/eurosat
+    split: test
+```
+
diff --git a/resnet18-eurosat-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/config.json b/resnet18-eurosat-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..cf61d0357a8d4fef0a1593df0f7b561cb9c545a1
--- /dev/null
+++ b/resnet18-eurosat-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "annual crop land",
+    "1": "forest",
+    "2": "brushland or shrubland",
+    "3": "highway or road",
+    "4": "industrial buildings or commercial buildings",
+    "5": "pasture land",
+    "6": "permanent crop land",
+    "7": "residential buildings or homes or apartments",
+    "8": "river",
+    "9": "lake or sea"
+  },
+  "label2id": {
+    "annual crop land": 0,
+    "brushland or shrubland": 2,
+    "forest": 1,
+    "highway or road": 3,
+    "industrial buildings or commercial buildings": 4,
+    "lake or sea": 9,
+    "pasture land": 5,
+    "permanent crop land": 6,
+    "residential buildings or homes or apartments": 7,
+    "river": 8
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-eurosat-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet18-eurosat-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-eurosat-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-eurosat-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/README.md b/resnet18-eurosat-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..4eaf2a863eebebd178d475a96a04c40a9af5439f
--- /dev/null
+++ b/resnet18-eurosat-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset eurosat.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: eurosat
+    pretrained: true
+test_datasets: null
+train_datasets:
+  eurosat:
+    _target_: datasets.load_dataset
+    path: tanganke/eurosat
+    split: train
+type: transformers
+val_datasets:
+  eurosat:
+    _target_: datasets.load_dataset
+    path: tanganke/eurosat
+    split: test
+```
+
diff --git a/resnet18-eurosat-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/config.json b/resnet18-eurosat-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..cf61d0357a8d4fef0a1593df0f7b561cb9c545a1
--- /dev/null
+++ b/resnet18-eurosat-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "annual crop land",
+    "1": "forest",
+    "2": "brushland or shrubland",
+    "3": "highway or road",
+    "4": "industrial buildings or commercial buildings",
+    "5": "pasture land",
+    "6": "permanent crop land",
+    "7": "residential buildings or homes or apartments",
+    "8": "river",
+    "9": "lake or sea"
+  },
+  "label2id": {
+    "annual crop land": 0,
+    "brushland or shrubland": 2,
+    "forest": 1,
+    "highway or road": 3,
+    "industrial buildings or commercial buildings": 4,
+    "lake or sea": 9,
+    "pasture land": 5,
+    "permanent crop land": 6,
+    "residential buildings or homes or apartments": 7,
+    "river": 8
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-eurosat-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet18-eurosat-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-eurosat-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-eurosat-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/README.md b/resnet18-eurosat-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..bee47ff6642c992d0b9e45395371630d58a7f083
--- /dev/null
+++ b/resnet18-eurosat-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset eurosat.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: eurosat
+    pretrained: true
+test_datasets: null
+train_datasets:
+  eurosat:
+    _target_: datasets.load_dataset
+    path: tanganke/eurosat
+    split: train
+type: transformers
+val_datasets:
+  eurosat:
+    _target_: datasets.load_dataset
+    path: tanganke/eurosat
+    split: test
+```
+
diff --git a/resnet18-eurosat-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/config.json b/resnet18-eurosat-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..cf61d0357a8d4fef0a1593df0f7b561cb9c545a1
--- /dev/null
+++ b/resnet18-eurosat-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "annual crop land",
+    "1": "forest",
+    "2": "brushland or shrubland",
+    "3": "highway or road",
+    "4": "industrial buildings or commercial buildings",
+    "5": "pasture land",
+    "6": "permanent crop land",
+    "7": "residential buildings or homes or apartments",
+    "8": "river",
+    "9": "lake or sea"
+  },
+  "label2id": {
+    "annual crop land": 0,
+    "brushland or shrubland": 2,
+    "forest": 1,
+    "highway or road": 3,
+    "industrial buildings or commercial buildings": 4,
+    "lake or sea": 9,
+    "pasture land": 5,
+    "permanent crop land": 6,
+    "residential buildings or homes or apartments": 7,
+    "river": 8
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-eurosat-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet18-eurosat-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-eurosat-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/README.md b/resnet18-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..f4ad62b069334bd91570c1bb6174777619a57488
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fashion_mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: fashion_mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: train
+type: transformers
+val_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: test
+```
+
diff --git a/resnet18-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/config.json b/resnet18-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..95053393425e99bf8747d9695556f752509f4b0b
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "T - shirt / top",
+    "1": "Trouser",
+    "2": "Pullover",
+    "3": "Dress",
+    "4": "Coat",
+    "5": "Sandal",
+    "6": "Shirt",
+    "7": "Sneaker",
+    "8": "Bag",
+    "9": "Ankle boot"
+  },
+  "label2id": {
+    "Ankle boot": 9,
+    "Bag": 8,
+    "Coat": 4,
+    "Dress": 3,
+    "Pullover": 2,
+    "Sandal": 5,
+    "Shirt": 6,
+    "Sneaker": 7,
+    "T - shirt / top": 0,
+    "Trouser": 1
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet18-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/README.md b/resnet18-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..7b988a51da52e8c4e7b6ed76a8dbdbf3e43b14e3
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fashion_mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: fashion_mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: train
+type: transformers
+val_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: test
+```
+
diff --git a/resnet18-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/config.json b/resnet18-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..95053393425e99bf8747d9695556f752509f4b0b
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "T - shirt / top",
+    "1": "Trouser",
+    "2": "Pullover",
+    "3": "Dress",
+    "4": "Coat",
+    "5": "Sandal",
+    "6": "Shirt",
+    "7": "Sneaker",
+    "8": "Bag",
+    "9": "Ankle boot"
+  },
+  "label2id": {
+    "Ankle boot": 9,
+    "Bag": 8,
+    "Coat": 4,
+    "Dress": 3,
+    "Pullover": 2,
+    "Sandal": 5,
+    "Shirt": 6,
+    "Sneaker": 7,
+    "T - shirt / top": 0,
+    "Trouser": 1
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet18-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-1000/README.md b/resnet18-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..970304d6671d2eb0ab63d2469e2a59ba49aa6f71
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fashion_mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: fashion_mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: train
+type: transformers
+val_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: test
+```
+
diff --git a/resnet18-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-1000/config.json b/resnet18-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..95053393425e99bf8747d9695556f752509f4b0b
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-1000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "T - shirt / top",
+    "1": "Trouser",
+    "2": "Pullover",
+    "3": "Dress",
+    "4": "Coat",
+    "5": "Sandal",
+    "6": "Shirt",
+    "7": "Sneaker",
+    "8": "Bag",
+    "9": "Ankle boot"
+  },
+  "label2id": {
+    "Ankle boot": 9,
+    "Bag": 8,
+    "Coat": 4,
+    "Dress": 3,
+    "Pullover": 2,
+    "Sandal": 5,
+    "Shirt": 6,
+    "Sneaker": 7,
+    "T - shirt / top": 0,
+    "Trouser": 1
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet18-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/README.md b/resnet18-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..faa4c433abf98cfda3da48d2b29b46813fc268f7
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fashion_mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: fashion_mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: train
+type: transformers
+val_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: test
+```
+
diff --git a/resnet18-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/config.json b/resnet18-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..95053393425e99bf8747d9695556f752509f4b0b
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "T - shirt / top",
+    "1": "Trouser",
+    "2": "Pullover",
+    "3": "Dress",
+    "4": "Coat",
+    "5": "Sandal",
+    "6": "Shirt",
+    "7": "Sneaker",
+    "8": "Bag",
+    "9": "Ankle boot"
+  },
+  "label2id": {
+    "Ankle boot": 9,
+    "Bag": 8,
+    "Coat": 4,
+    "Dress": 3,
+    "Pullover": 2,
+    "Sandal": 5,
+    "Shirt": 6,
+    "Sneaker": 7,
+    "T - shirt / top": 0,
+    "Trouser": 1
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet18-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-fashion_mnist-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/README.md b/resnet18-fashion_mnist-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..abbf9a5e76ce68492b6bda21819b21d806df15de
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fashion_mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: fashion_mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: train
+type: transformers
+val_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: test
+```
+
diff --git a/resnet18-fashion_mnist-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/config.json b/resnet18-fashion_mnist-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..95053393425e99bf8747d9695556f752509f4b0b
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "T - shirt / top",
+    "1": "Trouser",
+    "2": "Pullover",
+    "3": "Dress",
+    "4": "Coat",
+    "5": "Sandal",
+    "6": "Shirt",
+    "7": "Sneaker",
+    "8": "Bag",
+    "9": "Ankle boot"
+  },
+  "label2id": {
+    "Ankle boot": 9,
+    "Bag": 8,
+    "Coat": 4,
+    "Dress": 3,
+    "Pullover": 2,
+    "Sandal": 5,
+    "Shirt": 6,
+    "Sneaker": 7,
+    "T - shirt / top": 0,
+    "Trouser": 1
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-fashion_mnist-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet18-fashion_mnist-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/README.md b/resnet18-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..1e646e825b9103c7d7c9316f55e19da0c70fcb98
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fashion_mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: fashion_mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: train
+type: transformers
+val_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: test
+```
+
diff --git a/resnet18-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/config.json b/resnet18-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..95053393425e99bf8747d9695556f752509f4b0b
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "T - shirt / top",
+    "1": "Trouser",
+    "2": "Pullover",
+    "3": "Dress",
+    "4": "Coat",
+    "5": "Sandal",
+    "6": "Shirt",
+    "7": "Sneaker",
+    "8": "Bag",
+    "9": "Ankle boot"
+  },
+  "label2id": {
+    "Ankle boot": 9,
+    "Bag": 8,
+    "Coat": 4,
+    "Dress": 3,
+    "Pullover": 2,
+    "Sandal": 5,
+    "Shirt": 6,
+    "Sneaker": 7,
+    "T - shirt / top": 0,
+    "Trouser": 1
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet18-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/README.md b/resnet18-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..37a0dc1ba661af0b8ca92c4418c52a6a3f125caa
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fashion_mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: fashion_mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: train
+type: transformers
+val_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: test
+```
+
diff --git a/resnet18-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/config.json b/resnet18-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..95053393425e99bf8747d9695556f752509f4b0b
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "T - shirt / top",
+    "1": "Trouser",
+    "2": "Pullover",
+    "3": "Dress",
+    "4": "Coat",
+    "5": "Sandal",
+    "6": "Shirt",
+    "7": "Sneaker",
+    "8": "Bag",
+    "9": "Ankle boot"
+  },
+  "label2id": {
+    "Ankle boot": 9,
+    "Bag": 8,
+    "Coat": 4,
+    "Dress": 3,
+    "Pullover": 2,
+    "Sandal": 5,
+    "Shirt": 6,
+    "Sneaker": 7,
+    "T - shirt / top": 0,
+    "Trouser": 1
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet18-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-fashion_mnist-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/README.md b/resnet18-fashion_mnist-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..9f0968fc31766e28e71bb513b33209e6afb66e93
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fashion_mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: fashion_mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: train
+type: transformers
+val_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: test
+```
+
diff --git a/resnet18-fashion_mnist-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/config.json b/resnet18-fashion_mnist-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..95053393425e99bf8747d9695556f752509f4b0b
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "T - shirt / top",
+    "1": "Trouser",
+    "2": "Pullover",
+    "3": "Dress",
+    "4": "Coat",
+    "5": "Sandal",
+    "6": "Shirt",
+    "7": "Sneaker",
+    "8": "Bag",
+    "9": "Ankle boot"
+  },
+  "label2id": {
+    "Ankle boot": 9,
+    "Bag": 8,
+    "Coat": 4,
+    "Dress": 3,
+    "Pullover": 2,
+    "Sandal": 5,
+    "Shirt": 6,
+    "Sneaker": 7,
+    "T - shirt / top": 0,
+    "Trouser": 1
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-fashion_mnist-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet18-fashion_mnist-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-fashion_mnist-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/README.md b/resnet18-fashion_mnist-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e3f6883d8df4149b18e96debdf86fdc76c2cc189
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fashion_mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: fashion_mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: train
+type: transformers
+val_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: test
+```
+
diff --git a/resnet18-fashion_mnist-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/config.json b/resnet18-fashion_mnist-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..95053393425e99bf8747d9695556f752509f4b0b
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "T - shirt / top",
+    "1": "Trouser",
+    "2": "Pullover",
+    "3": "Dress",
+    "4": "Coat",
+    "5": "Sandal",
+    "6": "Shirt",
+    "7": "Sneaker",
+    "8": "Bag",
+    "9": "Ankle boot"
+  },
+  "label2id": {
+    "Ankle boot": 9,
+    "Bag": 8,
+    "Coat": 4,
+    "Dress": 3,
+    "Pullover": 2,
+    "Sandal": 5,
+    "Shirt": 6,
+    "Sneaker": 7,
+    "T - shirt / top": 0,
+    "Trouser": 1
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-fashion_mnist-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet18-fashion_mnist-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-fashion_mnist-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-fer2013-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/README.md b/resnet18-fer2013-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..2062580452c7b5265a6c0b2196854379d150d098
--- /dev/null
+++ b/resnet18-fer2013-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,74 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fer2013.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: fer2013
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: train
+type: transformers
+val_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: test
+```
+
diff --git a/resnet18-fer2013-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/config.json b/resnet18-fer2013-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..ce988daea92558cbffcf8c943ef8039e1e9a5ec2
--- /dev/null
+++ b/resnet18-fer2013-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,57 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "angry",
+    "1": "disgusted",
+    "2": "fearful",
+    "3": "happy",
+    "4": "neutral",
+    "5": "sad",
+    "6": "surprised"
+  },
+  "label2id": {
+    "angry": 0,
+    "disgusted": 1,
+    "fearful": 2,
+    "happy": 3,
+    "neutral": 4,
+    "sad": 5,
+    "surprised": 6
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-fer2013-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet18-fer2013-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-fer2013-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-fer2013-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md b/resnet18-fer2013-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..86652ebc6e31ed317accb8760a126af16a5c4952
--- /dev/null
+++ b/resnet18-fer2013-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,74 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fer2013.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: fer2013
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: train
+type: transformers
+val_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: test
+```
+
diff --git a/resnet18-fer2013-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/config.json b/resnet18-fer2013-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..ce988daea92558cbffcf8c943ef8039e1e9a5ec2
--- /dev/null
+++ b/resnet18-fer2013-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,57 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "angry",
+    "1": "disgusted",
+    "2": "fearful",
+    "3": "happy",
+    "4": "neutral",
+    "5": "sad",
+    "6": "surprised"
+  },
+  "label2id": {
+    "angry": 0,
+    "disgusted": 1,
+    "fearful": 2,
+    "happy": 3,
+    "neutral": 4,
+    "sad": 5,
+    "surprised": 6
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-fer2013-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet18-fer2013-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-fer2013-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-fer2013-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/README.md b/resnet18-fer2013-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..72c74704a5e0b832cacb5000bd9955cf911c21aa
--- /dev/null
+++ b/resnet18-fer2013-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,74 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fer2013.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: fer2013
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: train
+type: transformers
+val_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: test
+```
+
diff --git a/resnet18-fer2013-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/config.json b/resnet18-fer2013-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..ce988daea92558cbffcf8c943ef8039e1e9a5ec2
--- /dev/null
+++ b/resnet18-fer2013-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,57 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "angry",
+    "1": "disgusted",
+    "2": "fearful",
+    "3": "happy",
+    "4": "neutral",
+    "5": "sad",
+    "6": "surprised"
+  },
+  "label2id": {
+    "angry": 0,
+    "disgusted": 1,
+    "fearful": 2,
+    "happy": 3,
+    "neutral": 4,
+    "sad": 5,
+    "surprised": 6
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-fer2013-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet18-fer2013-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-fer2013-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-fer2013-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/README.md b/resnet18-fer2013-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..99aa4c77f48a2dbd9cf0e9be65a01057e05d2eda
--- /dev/null
+++ b/resnet18-fer2013-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,74 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fer2013.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: fer2013
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: train
+type: transformers
+val_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: test
+```
+
diff --git a/resnet18-fer2013-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/config.json b/resnet18-fer2013-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..ce988daea92558cbffcf8c943ef8039e1e9a5ec2
--- /dev/null
+++ b/resnet18-fer2013-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,57 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "angry",
+    "1": "disgusted",
+    "2": "fearful",
+    "3": "happy",
+    "4": "neutral",
+    "5": "sad",
+    "6": "surprised"
+  },
+  "label2id": {
+    "angry": 0,
+    "disgusted": 1,
+    "fearful": 2,
+    "happy": 3,
+    "neutral": 4,
+    "sad": 5,
+    "surprised": 6
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-fer2013-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet18-fer2013-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-fer2013-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-fer2013-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/README.md b/resnet18-fer2013-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..48ad3d7e03e304c945c13b3f7df9e617b920f2a6
--- /dev/null
+++ b/resnet18-fer2013-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/README.md
@@ -0,0 +1,74 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fer2013.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: fer2013
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: train
+type: transformers
+val_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: test
+```
+
diff --git a/resnet18-fer2013-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/config.json b/resnet18-fer2013-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..ce988daea92558cbffcf8c943ef8039e1e9a5ec2
--- /dev/null
+++ b/resnet18-fer2013-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/config.json
@@ -0,0 +1,57 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "angry",
+    "1": "disgusted",
+    "2": "fearful",
+    "3": "happy",
+    "4": "neutral",
+    "5": "sad",
+    "6": "surprised"
+  },
+  "label2id": {
+    "angry": 0,
+    "disgusted": 1,
+    "fearful": 2,
+    "happy": 3,
+    "neutral": 4,
+    "sad": 5,
+    "surprised": 6
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-fer2013-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet18-fer2013-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-fer2013-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/README.md b/resnet18-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..184bba605850db574dae99b36aaa3f765f595589
--- /dev/null
+++ b/resnet18-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,74 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fer2013.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: fer2013
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: train
+type: transformers
+val_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: test
+```
+
diff --git a/resnet18-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/config.json b/resnet18-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..ce988daea92558cbffcf8c943ef8039e1e9a5ec2
--- /dev/null
+++ b/resnet18-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,57 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "angry",
+    "1": "disgusted",
+    "2": "fearful",
+    "3": "happy",
+    "4": "neutral",
+    "5": "sad",
+    "6": "surprised"
+  },
+  "label2id": {
+    "angry": 0,
+    "disgusted": 1,
+    "fearful": 2,
+    "happy": 3,
+    "neutral": 4,
+    "sad": 5,
+    "surprised": 6
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet18-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-food101-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/README.md b/resnet18-food101-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..12634c437e56efafac9d25575822dd0e4892cf04
--- /dev/null
+++ b/resnet18-food101-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset food101.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: food101
+    pretrained: true
+test_datasets: null
+train_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: train
+type: transformers
+val_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: validation
+```
+
diff --git a/resnet18-food101-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/config.json b/resnet18-food101-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2bba7874d0acf5076869a6fd62eb0fbe2d2041dc
--- /dev/null
+++ b/resnet18-food101-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,245 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "apple pie",
+    "1": "baby back ribs",
+    "2": "baklava",
+    "3": "beef carpaccio",
+    "4": "beef tartare",
+    "5": "beet salad",
+    "6": "beignets",
+    "7": "bibimbap",
+    "8": "bread pudding",
+    "9": "breakfast burrito",
+    "10": "bruschetta",
+    "11": "caesar salad",
+    "12": "cannoli",
+    "13": "caprese salad",
+    "14": "carrot cake",
+    "15": "ceviche",
+    "16": "cheese plate",
+    "17": "cheesecake",
+    "18": "chicken curry",
+    "19": "chicken quesadilla",
+    "20": "chicken wings",
+    "21": "chocolate cake",
+    "22": "chocolate mousse",
+    "23": "churros",
+    "24": "clam chowder",
+    "25": "club sandwich",
+    "26": "crab cakes",
+    "27": "creme brulee",
+    "28": "croque madame",
+    "29": "cup cakes",
+    "30": "deviled eggs",
+    "31": "donuts",
+    "32": "dumplings",
+    "33": "edamame",
+    "34": "eggs benedict",
+    "35": "escargots",
+    "36": "falafel",
+    "37": "filet mignon",
+    "38": "fish and chips",
+    "39": "foie gras",
+    "40": "french fries",
+    "41": "french onion soup",
+    "42": "french toast",
+    "43": "fried calamari",
+    "44": "fried rice",
+    "45": "frozen yogurt",
+    "46": "garlic bread",
+    "47": "gnocchi",
+    "48": "greek salad",
+    "49": "grilled cheese sandwich",
+    "50": "grilled salmon",
+    "51": "guacamole",
+    "52": "gyoza",
+    "53": "hamburger",
+    "54": "hot and sour soup",
+    "55": "hot dog",
+    "56": "huevos rancheros",
+    "57": "hummus",
+    "58": "ice cream",
+    "59": "lasagna",
+    "60": "lobster bisque",
+    "61": "lobster roll sandwich",
+    "62": "macaroni and cheese",
+    "63": "macarons",
+    "64": "miso soup",
+    "65": "mussels",
+    "66": "nachos",
+    "67": "omelette",
+    "68": "onion rings",
+    "69": "oysters",
+    "70": "pad thai",
+    "71": "paella",
+    "72": "pancakes",
+    "73": "panna cotta",
+    "74": "peking duck",
+    "75": "pho",
+    "76": "pizza",
+    "77": "pork chop",
+    "78": "poutine",
+    "79": "prime rib",
+    "80": "pulled pork sandwich",
+    "81": "ramen",
+    "82": "ravioli",
+    "83": "red velvet cake",
+    "84": "risotto",
+    "85": "samosa",
+    "86": "sashimi",
+    "87": "scallops",
+    "88": "seaweed salad",
+    "89": "shrimp and grits",
+    "90": "spaghetti bolognese",
+    "91": "spaghetti carbonara",
+    "92": "spring rolls",
+    "93": "steak",
+    "94": "strawberry shortcake",
+    "95": "sushi",
+    "96": "tacos",
+    "97": "takoyaki",
+    "98": "tiramisu",
+    "99": "tuna tartare",
+    "100": "waffles"
+  },
+  "label2id": {
+    "apple pie": 0,
+    "baby back ribs": 1,
+    "baklava": 2,
+    "beef carpaccio": 3,
+    "beef tartare": 4,
+    "beet salad": 5,
+    "beignets": 6,
+    "bibimbap": 7,
+    "bread pudding": 8,
+    "breakfast burrito": 9,
+    "bruschetta": 10,
+    "caesar salad": 11,
+    "cannoli": 12,
+    "caprese salad": 13,
+    "carrot cake": 14,
+    "ceviche": 15,
+    "cheese plate": 16,
+    "cheesecake": 17,
+    "chicken curry": 18,
+    "chicken quesadilla": 19,
+    "chicken wings": 20,
+    "chocolate cake": 21,
+    "chocolate mousse": 22,
+    "churros": 23,
+    "clam chowder": 24,
+    "club sandwich": 25,
+    "crab cakes": 26,
+    "creme brulee": 27,
+    "croque madame": 28,
+    "cup cakes": 29,
+    "deviled eggs": 30,
+    "donuts": 31,
+    "dumplings": 32,
+    "edamame": 33,
+    "eggs benedict": 34,
+    "escargots": 35,
+    "falafel": 36,
+    "filet mignon": 37,
+    "fish and chips": 38,
+    "foie gras": 39,
+    "french fries": 40,
+    "french onion soup": 41,
+    "french toast": 42,
+    "fried calamari": 43,
+    "fried rice": 44,
+    "frozen yogurt": 45,
+    "garlic bread": 46,
+    "gnocchi": 47,
+    "greek salad": 48,
+    "grilled cheese sandwich": 49,
+    "grilled salmon": 50,
+    "guacamole": 51,
+    "gyoza": 52,
+    "hamburger": 53,
+    "hot and sour soup": 54,
+    "hot dog": 55,
+    "huevos rancheros": 56,
+    "hummus": 57,
+    "ice cream": 58,
+    "lasagna": 59,
+    "lobster bisque": 60,
+    "lobster roll sandwich": 61,
+    "macaroni and cheese": 62,
+    "macarons": 63,
+    "miso soup": 64,
+    "mussels": 65,
+    "nachos": 66,
+    "omelette": 67,
+    "onion rings": 68,
+    "oysters": 69,
+    "pad thai": 70,
+    "paella": 71,
+    "pancakes": 72,
+    "panna cotta": 73,
+    "peking duck": 74,
+    "pho": 75,
+    "pizza": 76,
+    "pork chop": 77,
+    "poutine": 78,
+    "prime rib": 79,
+    "pulled pork sandwich": 80,
+    "ramen": 81,
+    "ravioli": 82,
+    "red velvet cake": 83,
+    "risotto": 84,
+    "samosa": 85,
+    "sashimi": 86,
+    "scallops": 87,
+    "seaweed salad": 88,
+    "shrimp and grits": 89,
+    "spaghetti bolognese": 90,
+    "spaghetti carbonara": 91,
+    "spring rolls": 92,
+    "steak": 93,
+    "strawberry shortcake": 94,
+    "sushi": 95,
+    "tacos": 96,
+    "takoyaki": 97,
+    "tiramisu": 98,
+    "tuna tartare": 99,
+    "waffles": 100
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-food101-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet18-food101-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-food101-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-food101-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/README.md b/resnet18-food101-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..12634c437e56efafac9d25575822dd0e4892cf04
--- /dev/null
+++ b/resnet18-food101-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset food101.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: food101
+    pretrained: true
+test_datasets: null
+train_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: train
+type: transformers
+val_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: validation
+```
+
diff --git a/resnet18-food101-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/config.json b/resnet18-food101-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2bba7874d0acf5076869a6fd62eb0fbe2d2041dc
--- /dev/null
+++ b/resnet18-food101-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,245 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "apple pie",
+    "1": "baby back ribs",
+    "2": "baklava",
+    "3": "beef carpaccio",
+    "4": "beef tartare",
+    "5": "beet salad",
+    "6": "beignets",
+    "7": "bibimbap",
+    "8": "bread pudding",
+    "9": "breakfast burrito",
+    "10": "bruschetta",
+    "11": "caesar salad",
+    "12": "cannoli",
+    "13": "caprese salad",
+    "14": "carrot cake",
+    "15": "ceviche",
+    "16": "cheese plate",
+    "17": "cheesecake",
+    "18": "chicken curry",
+    "19": "chicken quesadilla",
+    "20": "chicken wings",
+    "21": "chocolate cake",
+    "22": "chocolate mousse",
+    "23": "churros",
+    "24": "clam chowder",
+    "25": "club sandwich",
+    "26": "crab cakes",
+    "27": "creme brulee",
+    "28": "croque madame",
+    "29": "cup cakes",
+    "30": "deviled eggs",
+    "31": "donuts",
+    "32": "dumplings",
+    "33": "edamame",
+    "34": "eggs benedict",
+    "35": "escargots",
+    "36": "falafel",
+    "37": "filet mignon",
+    "38": "fish and chips",
+    "39": "foie gras",
+    "40": "french fries",
+    "41": "french onion soup",
+    "42": "french toast",
+    "43": "fried calamari",
+    "44": "fried rice",
+    "45": "frozen yogurt",
+    "46": "garlic bread",
+    "47": "gnocchi",
+    "48": "greek salad",
+    "49": "grilled cheese sandwich",
+    "50": "grilled salmon",
+    "51": "guacamole",
+    "52": "gyoza",
+    "53": "hamburger",
+    "54": "hot and sour soup",
+    "55": "hot dog",
+    "56": "huevos rancheros",
+    "57": "hummus",
+    "58": "ice cream",
+    "59": "lasagna",
+    "60": "lobster bisque",
+    "61": "lobster roll sandwich",
+    "62": "macaroni and cheese",
+    "63": "macarons",
+    "64": "miso soup",
+    "65": "mussels",
+    "66": "nachos",
+    "67": "omelette",
+    "68": "onion rings",
+    "69": "oysters",
+    "70": "pad thai",
+    "71": "paella",
+    "72": "pancakes",
+    "73": "panna cotta",
+    "74": "peking duck",
+    "75": "pho",
+    "76": "pizza",
+    "77": "pork chop",
+    "78": "poutine",
+    "79": "prime rib",
+    "80": "pulled pork sandwich",
+    "81": "ramen",
+    "82": "ravioli",
+    "83": "red velvet cake",
+    "84": "risotto",
+    "85": "samosa",
+    "86": "sashimi",
+    "87": "scallops",
+    "88": "seaweed salad",
+    "89": "shrimp and grits",
+    "90": "spaghetti bolognese",
+    "91": "spaghetti carbonara",
+    "92": "spring rolls",
+    "93": "steak",
+    "94": "strawberry shortcake",
+    "95": "sushi",
+    "96": "tacos",
+    "97": "takoyaki",
+    "98": "tiramisu",
+    "99": "tuna tartare",
+    "100": "waffles"
+  },
+  "label2id": {
+    "apple pie": 0,
+    "baby back ribs": 1,
+    "baklava": 2,
+    "beef carpaccio": 3,
+    "beef tartare": 4,
+    "beet salad": 5,
+    "beignets": 6,
+    "bibimbap": 7,
+    "bread pudding": 8,
+    "breakfast burrito": 9,
+    "bruschetta": 10,
+    "caesar salad": 11,
+    "cannoli": 12,
+    "caprese salad": 13,
+    "carrot cake": 14,
+    "ceviche": 15,
+    "cheese plate": 16,
+    "cheesecake": 17,
+    "chicken curry": 18,
+    "chicken quesadilla": 19,
+    "chicken wings": 20,
+    "chocolate cake": 21,
+    "chocolate mousse": 22,
+    "churros": 23,
+    "clam chowder": 24,
+    "club sandwich": 25,
+    "crab cakes": 26,
+    "creme brulee": 27,
+    "croque madame": 28,
+    "cup cakes": 29,
+    "deviled eggs": 30,
+    "donuts": 31,
+    "dumplings": 32,
+    "edamame": 33,
+    "eggs benedict": 34,
+    "escargots": 35,
+    "falafel": 36,
+    "filet mignon": 37,
+    "fish and chips": 38,
+    "foie gras": 39,
+    "french fries": 40,
+    "french onion soup": 41,
+    "french toast": 42,
+    "fried calamari": 43,
+    "fried rice": 44,
+    "frozen yogurt": 45,
+    "garlic bread": 46,
+    "gnocchi": 47,
+    "greek salad": 48,
+    "grilled cheese sandwich": 49,
+    "grilled salmon": 50,
+    "guacamole": 51,
+    "gyoza": 52,
+    "hamburger": 53,
+    "hot and sour soup": 54,
+    "hot dog": 55,
+    "huevos rancheros": 56,
+    "hummus": 57,
+    "ice cream": 58,
+    "lasagna": 59,
+    "lobster bisque": 60,
+    "lobster roll sandwich": 61,
+    "macaroni and cheese": 62,
+    "macarons": 63,
+    "miso soup": 64,
+    "mussels": 65,
+    "nachos": 66,
+    "omelette": 67,
+    "onion rings": 68,
+    "oysters": 69,
+    "pad thai": 70,
+    "paella": 71,
+    "pancakes": 72,
+    "panna cotta": 73,
+    "peking duck": 74,
+    "pho": 75,
+    "pizza": 76,
+    "pork chop": 77,
+    "poutine": 78,
+    "prime rib": 79,
+    "pulled pork sandwich": 80,
+    "ramen": 81,
+    "ravioli": 82,
+    "red velvet cake": 83,
+    "risotto": 84,
+    "samosa": 85,
+    "sashimi": 86,
+    "scallops": 87,
+    "seaweed salad": 88,
+    "shrimp and grits": 89,
+    "spaghetti bolognese": 90,
+    "spaghetti carbonara": 91,
+    "spring rolls": 92,
+    "steak": 93,
+    "strawberry shortcake": 94,
+    "sushi": 95,
+    "tacos": 96,
+    "takoyaki": 97,
+    "tiramisu": 98,
+    "tuna tartare": 99,
+    "waffles": 100
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-food101-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet18-food101-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-food101-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-food101-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/README.md b/resnet18-food101-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..b4d674c2de5d2f82246866380d728493ccb04310
--- /dev/null
+++ b/resnet18-food101-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset food101.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: food101
+    pretrained: true
+test_datasets: null
+train_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: train
+type: transformers
+val_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: validation
+```
+
diff --git a/resnet18-food101-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/config.json b/resnet18-food101-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2bba7874d0acf5076869a6fd62eb0fbe2d2041dc
--- /dev/null
+++ b/resnet18-food101-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,245 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "apple pie",
+    "1": "baby back ribs",
+    "2": "baklava",
+    "3": "beef carpaccio",
+    "4": "beef tartare",
+    "5": "beet salad",
+    "6": "beignets",
+    "7": "bibimbap",
+    "8": "bread pudding",
+    "9": "breakfast burrito",
+    "10": "bruschetta",
+    "11": "caesar salad",
+    "12": "cannoli",
+    "13": "caprese salad",
+    "14": "carrot cake",
+    "15": "ceviche",
+    "16": "cheese plate",
+    "17": "cheesecake",
+    "18": "chicken curry",
+    "19": "chicken quesadilla",
+    "20": "chicken wings",
+    "21": "chocolate cake",
+    "22": "chocolate mousse",
+    "23": "churros",
+    "24": "clam chowder",
+    "25": "club sandwich",
+    "26": "crab cakes",
+    "27": "creme brulee",
+    "28": "croque madame",
+    "29": "cup cakes",
+    "30": "deviled eggs",
+    "31": "donuts",
+    "32": "dumplings",
+    "33": "edamame",
+    "34": "eggs benedict",
+    "35": "escargots",
+    "36": "falafel",
+    "37": "filet mignon",
+    "38": "fish and chips",
+    "39": "foie gras",
+    "40": "french fries",
+    "41": "french onion soup",
+    "42": "french toast",
+    "43": "fried calamari",
+    "44": "fried rice",
+    "45": "frozen yogurt",
+    "46": "garlic bread",
+    "47": "gnocchi",
+    "48": "greek salad",
+    "49": "grilled cheese sandwich",
+    "50": "grilled salmon",
+    "51": "guacamole",
+    "52": "gyoza",
+    "53": "hamburger",
+    "54": "hot and sour soup",
+    "55": "hot dog",
+    "56": "huevos rancheros",
+    "57": "hummus",
+    "58": "ice cream",
+    "59": "lasagna",
+    "60": "lobster bisque",
+    "61": "lobster roll sandwich",
+    "62": "macaroni and cheese",
+    "63": "macarons",
+    "64": "miso soup",
+    "65": "mussels",
+    "66": "nachos",
+    "67": "omelette",
+    "68": "onion rings",
+    "69": "oysters",
+    "70": "pad thai",
+    "71": "paella",
+    "72": "pancakes",
+    "73": "panna cotta",
+    "74": "peking duck",
+    "75": "pho",
+    "76": "pizza",
+    "77": "pork chop",
+    "78": "poutine",
+    "79": "prime rib",
+    "80": "pulled pork sandwich",
+    "81": "ramen",
+    "82": "ravioli",
+    "83": "red velvet cake",
+    "84": "risotto",
+    "85": "samosa",
+    "86": "sashimi",
+    "87": "scallops",
+    "88": "seaweed salad",
+    "89": "shrimp and grits",
+    "90": "spaghetti bolognese",
+    "91": "spaghetti carbonara",
+    "92": "spring rolls",
+    "93": "steak",
+    "94": "strawberry shortcake",
+    "95": "sushi",
+    "96": "tacos",
+    "97": "takoyaki",
+    "98": "tiramisu",
+    "99": "tuna tartare",
+    "100": "waffles"
+  },
+  "label2id": {
+    "apple pie": 0,
+    "baby back ribs": 1,
+    "baklava": 2,
+    "beef carpaccio": 3,
+    "beef tartare": 4,
+    "beet salad": 5,
+    "beignets": 6,
+    "bibimbap": 7,
+    "bread pudding": 8,
+    "breakfast burrito": 9,
+    "bruschetta": 10,
+    "caesar salad": 11,
+    "cannoli": 12,
+    "caprese salad": 13,
+    "carrot cake": 14,
+    "ceviche": 15,
+    "cheese plate": 16,
+    "cheesecake": 17,
+    "chicken curry": 18,
+    "chicken quesadilla": 19,
+    "chicken wings": 20,
+    "chocolate cake": 21,
+    "chocolate mousse": 22,
+    "churros": 23,
+    "clam chowder": 24,
+    "club sandwich": 25,
+    "crab cakes": 26,
+    "creme brulee": 27,
+    "croque madame": 28,
+    "cup cakes": 29,
+    "deviled eggs": 30,
+    "donuts": 31,
+    "dumplings": 32,
+    "edamame": 33,
+    "eggs benedict": 34,
+    "escargots": 35,
+    "falafel": 36,
+    "filet mignon": 37,
+    "fish and chips": 38,
+    "foie gras": 39,
+    "french fries": 40,
+    "french onion soup": 41,
+    "french toast": 42,
+    "fried calamari": 43,
+    "fried rice": 44,
+    "frozen yogurt": 45,
+    "garlic bread": 46,
+    "gnocchi": 47,
+    "greek salad": 48,
+    "grilled cheese sandwich": 49,
+    "grilled salmon": 50,
+    "guacamole": 51,
+    "gyoza": 52,
+    "hamburger": 53,
+    "hot and sour soup": 54,
+    "hot dog": 55,
+    "huevos rancheros": 56,
+    "hummus": 57,
+    "ice cream": 58,
+    "lasagna": 59,
+    "lobster bisque": 60,
+    "lobster roll sandwich": 61,
+    "macaroni and cheese": 62,
+    "macarons": 63,
+    "miso soup": 64,
+    "mussels": 65,
+    "nachos": 66,
+    "omelette": 67,
+    "onion rings": 68,
+    "oysters": 69,
+    "pad thai": 70,
+    "paella": 71,
+    "pancakes": 72,
+    "panna cotta": 73,
+    "peking duck": 74,
+    "pho": 75,
+    "pizza": 76,
+    "pork chop": 77,
+    "poutine": 78,
+    "prime rib": 79,
+    "pulled pork sandwich": 80,
+    "ramen": 81,
+    "ravioli": 82,
+    "red velvet cake": 83,
+    "risotto": 84,
+    "samosa": 85,
+    "sashimi": 86,
+    "scallops": 87,
+    "seaweed salad": 88,
+    "shrimp and grits": 89,
+    "spaghetti bolognese": 90,
+    "spaghetti carbonara": 91,
+    "spring rolls": 92,
+    "steak": 93,
+    "strawberry shortcake": 94,
+    "sushi": 95,
+    "tacos": 96,
+    "takoyaki": 97,
+    "tiramisu": 98,
+    "tuna tartare": 99,
+    "waffles": 100
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-food101-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet18-food101-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-food101-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-food101-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/README.md b/resnet18-food101-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..7f9c110c1dced324ebee5a6c62949bf50c3fa71f
--- /dev/null
+++ b/resnet18-food101-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset food101.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: food101
+    pretrained: true
+test_datasets: null
+train_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: train
+type: transformers
+val_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: validation
+```
+
diff --git a/resnet18-food101-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/config.json b/resnet18-food101-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2bba7874d0acf5076869a6fd62eb0fbe2d2041dc
--- /dev/null
+++ b/resnet18-food101-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,245 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "apple pie",
+    "1": "baby back ribs",
+    "2": "baklava",
+    "3": "beef carpaccio",
+    "4": "beef tartare",
+    "5": "beet salad",
+    "6": "beignets",
+    "7": "bibimbap",
+    "8": "bread pudding",
+    "9": "breakfast burrito",
+    "10": "bruschetta",
+    "11": "caesar salad",
+    "12": "cannoli",
+    "13": "caprese salad",
+    "14": "carrot cake",
+    "15": "ceviche",
+    "16": "cheese plate",
+    "17": "cheesecake",
+    "18": "chicken curry",
+    "19": "chicken quesadilla",
+    "20": "chicken wings",
+    "21": "chocolate cake",
+    "22": "chocolate mousse",
+    "23": "churros",
+    "24": "clam chowder",
+    "25": "club sandwich",
+    "26": "crab cakes",
+    "27": "creme brulee",
+    "28": "croque madame",
+    "29": "cup cakes",
+    "30": "deviled eggs",
+    "31": "donuts",
+    "32": "dumplings",
+    "33": "edamame",
+    "34": "eggs benedict",
+    "35": "escargots",
+    "36": "falafel",
+    "37": "filet mignon",
+    "38": "fish and chips",
+    "39": "foie gras",
+    "40": "french fries",
+    "41": "french onion soup",
+    "42": "french toast",
+    "43": "fried calamari",
+    "44": "fried rice",
+    "45": "frozen yogurt",
+    "46": "garlic bread",
+    "47": "gnocchi",
+    "48": "greek salad",
+    "49": "grilled cheese sandwich",
+    "50": "grilled salmon",
+    "51": "guacamole",
+    "52": "gyoza",
+    "53": "hamburger",
+    "54": "hot and sour soup",
+    "55": "hot dog",
+    "56": "huevos rancheros",
+    "57": "hummus",
+    "58": "ice cream",
+    "59": "lasagna",
+    "60": "lobster bisque",
+    "61": "lobster roll sandwich",
+    "62": "macaroni and cheese",
+    "63": "macarons",
+    "64": "miso soup",
+    "65": "mussels",
+    "66": "nachos",
+    "67": "omelette",
+    "68": "onion rings",
+    "69": "oysters",
+    "70": "pad thai",
+    "71": "paella",
+    "72": "pancakes",
+    "73": "panna cotta",
+    "74": "peking duck",
+    "75": "pho",
+    "76": "pizza",
+    "77": "pork chop",
+    "78": "poutine",
+    "79": "prime rib",
+    "80": "pulled pork sandwich",
+    "81": "ramen",
+    "82": "ravioli",
+    "83": "red velvet cake",
+    "84": "risotto",
+    "85": "samosa",
+    "86": "sashimi",
+    "87": "scallops",
+    "88": "seaweed salad",
+    "89": "shrimp and grits",
+    "90": "spaghetti bolognese",
+    "91": "spaghetti carbonara",
+    "92": "spring rolls",
+    "93": "steak",
+    "94": "strawberry shortcake",
+    "95": "sushi",
+    "96": "tacos",
+    "97": "takoyaki",
+    "98": "tiramisu",
+    "99": "tuna tartare",
+    "100": "waffles"
+  },
+  "label2id": {
+    "apple pie": 0,
+    "baby back ribs": 1,
+    "baklava": 2,
+    "beef carpaccio": 3,
+    "beef tartare": 4,
+    "beet salad": 5,
+    "beignets": 6,
+    "bibimbap": 7,
+    "bread pudding": 8,
+    "breakfast burrito": 9,
+    "bruschetta": 10,
+    "caesar salad": 11,
+    "cannoli": 12,
+    "caprese salad": 13,
+    "carrot cake": 14,
+    "ceviche": 15,
+    "cheese plate": 16,
+    "cheesecake": 17,
+    "chicken curry": 18,
+    "chicken quesadilla": 19,
+    "chicken wings": 20,
+    "chocolate cake": 21,
+    "chocolate mousse": 22,
+    "churros": 23,
+    "clam chowder": 24,
+    "club sandwich": 25,
+    "crab cakes": 26,
+    "creme brulee": 27,
+    "croque madame": 28,
+    "cup cakes": 29,
+    "deviled eggs": 30,
+    "donuts": 31,
+    "dumplings": 32,
+    "edamame": 33,
+    "eggs benedict": 34,
+    "escargots": 35,
+    "falafel": 36,
+    "filet mignon": 37,
+    "fish and chips": 38,
+    "foie gras": 39,
+    "french fries": 40,
+    "french onion soup": 41,
+    "french toast": 42,
+    "fried calamari": 43,
+    "fried rice": 44,
+    "frozen yogurt": 45,
+    "garlic bread": 46,
+    "gnocchi": 47,
+    "greek salad": 48,
+    "grilled cheese sandwich": 49,
+    "grilled salmon": 50,
+    "guacamole": 51,
+    "gyoza": 52,
+    "hamburger": 53,
+    "hot and sour soup": 54,
+    "hot dog": 55,
+    "huevos rancheros": 56,
+    "hummus": 57,
+    "ice cream": 58,
+    "lasagna": 59,
+    "lobster bisque": 60,
+    "lobster roll sandwich": 61,
+    "macaroni and cheese": 62,
+    "macarons": 63,
+    "miso soup": 64,
+    "mussels": 65,
+    "nachos": 66,
+    "omelette": 67,
+    "onion rings": 68,
+    "oysters": 69,
+    "pad thai": 70,
+    "paella": 71,
+    "pancakes": 72,
+    "panna cotta": 73,
+    "peking duck": 74,
+    "pho": 75,
+    "pizza": 76,
+    "pork chop": 77,
+    "poutine": 78,
+    "prime rib": 79,
+    "pulled pork sandwich": 80,
+    "ramen": 81,
+    "ravioli": 82,
+    "red velvet cake": 83,
+    "risotto": 84,
+    "samosa": 85,
+    "sashimi": 86,
+    "scallops": 87,
+    "seaweed salad": 88,
+    "shrimp and grits": 89,
+    "spaghetti bolognese": 90,
+    "spaghetti carbonara": 91,
+    "spring rolls": 92,
+    "steak": 93,
+    "strawberry shortcake": 94,
+    "sushi": 95,
+    "tacos": 96,
+    "takoyaki": 97,
+    "tiramisu": 98,
+    "tuna tartare": 99,
+    "waffles": 100
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-food101-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet18-food101-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-food101-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-food101-batch_size_64_lr_0.001_training_data_ratio_0.8-1000/README.md b/resnet18-food101-batch_size_64_lr_0.001_training_data_ratio_0.8-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..fafef6980400d53d766b9fc8238f37fd8dd902aa
--- /dev/null
+++ b/resnet18-food101-batch_size_64_lr_0.001_training_data_ratio_0.8-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset food101.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: food101
+    pretrained: true
+test_datasets: null
+train_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: train
+type: transformers
+val_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: validation
+```
+
diff --git a/resnet18-food101-batch_size_64_lr_0.001_training_data_ratio_0.8-1000/config.json b/resnet18-food101-batch_size_64_lr_0.001_training_data_ratio_0.8-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2bba7874d0acf5076869a6fd62eb0fbe2d2041dc
--- /dev/null
+++ b/resnet18-food101-batch_size_64_lr_0.001_training_data_ratio_0.8-1000/config.json
@@ -0,0 +1,245 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "apple pie",
+    "1": "baby back ribs",
+    "2": "baklava",
+    "3": "beef carpaccio",
+    "4": "beef tartare",
+    "5": "beet salad",
+    "6": "beignets",
+    "7": "bibimbap",
+    "8": "bread pudding",
+    "9": "breakfast burrito",
+    "10": "bruschetta",
+    "11": "caesar salad",
+    "12": "cannoli",
+    "13": "caprese salad",
+    "14": "carrot cake",
+    "15": "ceviche",
+    "16": "cheese plate",
+    "17": "cheesecake",
+    "18": "chicken curry",
+    "19": "chicken quesadilla",
+    "20": "chicken wings",
+    "21": "chocolate cake",
+    "22": "chocolate mousse",
+    "23": "churros",
+    "24": "clam chowder",
+    "25": "club sandwich",
+    "26": "crab cakes",
+    "27": "creme brulee",
+    "28": "croque madame",
+    "29": "cup cakes",
+    "30": "deviled eggs",
+    "31": "donuts",
+    "32": "dumplings",
+    "33": "edamame",
+    "34": "eggs benedict",
+    "35": "escargots",
+    "36": "falafel",
+    "37": "filet mignon",
+    "38": "fish and chips",
+    "39": "foie gras",
+    "40": "french fries",
+    "41": "french onion soup",
+    "42": "french toast",
+    "43": "fried calamari",
+    "44": "fried rice",
+    "45": "frozen yogurt",
+    "46": "garlic bread",
+    "47": "gnocchi",
+    "48": "greek salad",
+    "49": "grilled cheese sandwich",
+    "50": "grilled salmon",
+    "51": "guacamole",
+    "52": "gyoza",
+    "53": "hamburger",
+    "54": "hot and sour soup",
+    "55": "hot dog",
+    "56": "huevos rancheros",
+    "57": "hummus",
+    "58": "ice cream",
+    "59": "lasagna",
+    "60": "lobster bisque",
+    "61": "lobster roll sandwich",
+    "62": "macaroni and cheese",
+    "63": "macarons",
+    "64": "miso soup",
+    "65": "mussels",
+    "66": "nachos",
+    "67": "omelette",
+    "68": "onion rings",
+    "69": "oysters",
+    "70": "pad thai",
+    "71": "paella",
+    "72": "pancakes",
+    "73": "panna cotta",
+    "74": "peking duck",
+    "75": "pho",
+    "76": "pizza",
+    "77": "pork chop",
+    "78": "poutine",
+    "79": "prime rib",
+    "80": "pulled pork sandwich",
+    "81": "ramen",
+    "82": "ravioli",
+    "83": "red velvet cake",
+    "84": "risotto",
+    "85": "samosa",
+    "86": "sashimi",
+    "87": "scallops",
+    "88": "seaweed salad",
+    "89": "shrimp and grits",
+    "90": "spaghetti bolognese",
+    "91": "spaghetti carbonara",
+    "92": "spring rolls",
+    "93": "steak",
+    "94": "strawberry shortcake",
+    "95": "sushi",
+    "96": "tacos",
+    "97": "takoyaki",
+    "98": "tiramisu",
+    "99": "tuna tartare",
+    "100": "waffles"
+  },
+  "label2id": {
+    "apple pie": 0,
+    "baby back ribs": 1,
+    "baklava": 2,
+    "beef carpaccio": 3,
+    "beef tartare": 4,
+    "beet salad": 5,
+    "beignets": 6,
+    "bibimbap": 7,
+    "bread pudding": 8,
+    "breakfast burrito": 9,
+    "bruschetta": 10,
+    "caesar salad": 11,
+    "cannoli": 12,
+    "caprese salad": 13,
+    "carrot cake": 14,
+    "ceviche": 15,
+    "cheese plate": 16,
+    "cheesecake": 17,
+    "chicken curry": 18,
+    "chicken quesadilla": 19,
+    "chicken wings": 20,
+    "chocolate cake": 21,
+    "chocolate mousse": 22,
+    "churros": 23,
+    "clam chowder": 24,
+    "club sandwich": 25,
+    "crab cakes": 26,
+    "creme brulee": 27,
+    "croque madame": 28,
+    "cup cakes": 29,
+    "deviled eggs": 30,
+    "donuts": 31,
+    "dumplings": 32,
+    "edamame": 33,
+    "eggs benedict": 34,
+    "escargots": 35,
+    "falafel": 36,
+    "filet mignon": 37,
+    "fish and chips": 38,
+    "foie gras": 39,
+    "french fries": 40,
+    "french onion soup": 41,
+    "french toast": 42,
+    "fried calamari": 43,
+    "fried rice": 44,
+    "frozen yogurt": 45,
+    "garlic bread": 46,
+    "gnocchi": 47,
+    "greek salad": 48,
+    "grilled cheese sandwich": 49,
+    "grilled salmon": 50,
+    "guacamole": 51,
+    "gyoza": 52,
+    "hamburger": 53,
+    "hot and sour soup": 54,
+    "hot dog": 55,
+    "huevos rancheros": 56,
+    "hummus": 57,
+    "ice cream": 58,
+    "lasagna": 59,
+    "lobster bisque": 60,
+    "lobster roll sandwich": 61,
+    "macaroni and cheese": 62,
+    "macarons": 63,
+    "miso soup": 64,
+    "mussels": 65,
+    "nachos": 66,
+    "omelette": 67,
+    "onion rings": 68,
+    "oysters": 69,
+    "pad thai": 70,
+    "paella": 71,
+    "pancakes": 72,
+    "panna cotta": 73,
+    "peking duck": 74,
+    "pho": 75,
+    "pizza": 76,
+    "pork chop": 77,
+    "poutine": 78,
+    "prime rib": 79,
+    "pulled pork sandwich": 80,
+    "ramen": 81,
+    "ravioli": 82,
+    "red velvet cake": 83,
+    "risotto": 84,
+    "samosa": 85,
+    "sashimi": 86,
+    "scallops": 87,
+    "seaweed salad": 88,
+    "shrimp and grits": 89,
+    "spaghetti bolognese": 90,
+    "spaghetti carbonara": 91,
+    "spring rolls": 92,
+    "steak": 93,
+    "strawberry shortcake": 94,
+    "sushi": 95,
+    "tacos": 96,
+    "takoyaki": 97,
+    "tiramisu": 98,
+    "tuna tartare": 99,
+    "waffles": 100
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-food101-batch_size_64_lr_0.001_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet18-food101-batch_size_64_lr_0.001_training_data_ratio_0.8-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-food101-batch_size_64_lr_0.001_training_data_ratio_0.8-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-food101-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/README.md b/resnet18-food101-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..dccece4d162132d62a0214a21ebc080075ce2eff
--- /dev/null
+++ b/resnet18-food101-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset food101.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: food101
+    pretrained: true
+test_datasets: null
+train_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: train
+type: transformers
+val_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: validation
+```
+
diff --git a/resnet18-food101-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/config.json b/resnet18-food101-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2bba7874d0acf5076869a6fd62eb0fbe2d2041dc
--- /dev/null
+++ b/resnet18-food101-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,245 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "apple pie",
+    "1": "baby back ribs",
+    "2": "baklava",
+    "3": "beef carpaccio",
+    "4": "beef tartare",
+    "5": "beet salad",
+    "6": "beignets",
+    "7": "bibimbap",
+    "8": "bread pudding",
+    "9": "breakfast burrito",
+    "10": "bruschetta",
+    "11": "caesar salad",
+    "12": "cannoli",
+    "13": "caprese salad",
+    "14": "carrot cake",
+    "15": "ceviche",
+    "16": "cheese plate",
+    "17": "cheesecake",
+    "18": "chicken curry",
+    "19": "chicken quesadilla",
+    "20": "chicken wings",
+    "21": "chocolate cake",
+    "22": "chocolate mousse",
+    "23": "churros",
+    "24": "clam chowder",
+    "25": "club sandwich",
+    "26": "crab cakes",
+    "27": "creme brulee",
+    "28": "croque madame",
+    "29": "cup cakes",
+    "30": "deviled eggs",
+    "31": "donuts",
+    "32": "dumplings",
+    "33": "edamame",
+    "34": "eggs benedict",
+    "35": "escargots",
+    "36": "falafel",
+    "37": "filet mignon",
+    "38": "fish and chips",
+    "39": "foie gras",
+    "40": "french fries",
+    "41": "french onion soup",
+    "42": "french toast",
+    "43": "fried calamari",
+    "44": "fried rice",
+    "45": "frozen yogurt",
+    "46": "garlic bread",
+    "47": "gnocchi",
+    "48": "greek salad",
+    "49": "grilled cheese sandwich",
+    "50": "grilled salmon",
+    "51": "guacamole",
+    "52": "gyoza",
+    "53": "hamburger",
+    "54": "hot and sour soup",
+    "55": "hot dog",
+    "56": "huevos rancheros",
+    "57": "hummus",
+    "58": "ice cream",
+    "59": "lasagna",
+    "60": "lobster bisque",
+    "61": "lobster roll sandwich",
+    "62": "macaroni and cheese",
+    "63": "macarons",
+    "64": "miso soup",
+    "65": "mussels",
+    "66": "nachos",
+    "67": "omelette",
+    "68": "onion rings",
+    "69": "oysters",
+    "70": "pad thai",
+    "71": "paella",
+    "72": "pancakes",
+    "73": "panna cotta",
+    "74": "peking duck",
+    "75": "pho",
+    "76": "pizza",
+    "77": "pork chop",
+    "78": "poutine",
+    "79": "prime rib",
+    "80": "pulled pork sandwich",
+    "81": "ramen",
+    "82": "ravioli",
+    "83": "red velvet cake",
+    "84": "risotto",
+    "85": "samosa",
+    "86": "sashimi",
+    "87": "scallops",
+    "88": "seaweed salad",
+    "89": "shrimp and grits",
+    "90": "spaghetti bolognese",
+    "91": "spaghetti carbonara",
+    "92": "spring rolls",
+    "93": "steak",
+    "94": "strawberry shortcake",
+    "95": "sushi",
+    "96": "tacos",
+    "97": "takoyaki",
+    "98": "tiramisu",
+    "99": "tuna tartare",
+    "100": "waffles"
+  },
+  "label2id": {
+    "apple pie": 0,
+    "baby back ribs": 1,
+    "baklava": 2,
+    "beef carpaccio": 3,
+    "beef tartare": 4,
+    "beet salad": 5,
+    "beignets": 6,
+    "bibimbap": 7,
+    "bread pudding": 8,
+    "breakfast burrito": 9,
+    "bruschetta": 10,
+    "caesar salad": 11,
+    "cannoli": 12,
+    "caprese salad": 13,
+    "carrot cake": 14,
+    "ceviche": 15,
+    "cheese plate": 16,
+    "cheesecake": 17,
+    "chicken curry": 18,
+    "chicken quesadilla": 19,
+    "chicken wings": 20,
+    "chocolate cake": 21,
+    "chocolate mousse": 22,
+    "churros": 23,
+    "clam chowder": 24,
+    "club sandwich": 25,
+    "crab cakes": 26,
+    "creme brulee": 27,
+    "croque madame": 28,
+    "cup cakes": 29,
+    "deviled eggs": 30,
+    "donuts": 31,
+    "dumplings": 32,
+    "edamame": 33,
+    "eggs benedict": 34,
+    "escargots": 35,
+    "falafel": 36,
+    "filet mignon": 37,
+    "fish and chips": 38,
+    "foie gras": 39,
+    "french fries": 40,
+    "french onion soup": 41,
+    "french toast": 42,
+    "fried calamari": 43,
+    "fried rice": 44,
+    "frozen yogurt": 45,
+    "garlic bread": 46,
+    "gnocchi": 47,
+    "greek salad": 48,
+    "grilled cheese sandwich": 49,
+    "grilled salmon": 50,
+    "guacamole": 51,
+    "gyoza": 52,
+    "hamburger": 53,
+    "hot and sour soup": 54,
+    "hot dog": 55,
+    "huevos rancheros": 56,
+    "hummus": 57,
+    "ice cream": 58,
+    "lasagna": 59,
+    "lobster bisque": 60,
+    "lobster roll sandwich": 61,
+    "macaroni and cheese": 62,
+    "macarons": 63,
+    "miso soup": 64,
+    "mussels": 65,
+    "nachos": 66,
+    "omelette": 67,
+    "onion rings": 68,
+    "oysters": 69,
+    "pad thai": 70,
+    "paella": 71,
+    "pancakes": 72,
+    "panna cotta": 73,
+    "peking duck": 74,
+    "pho": 75,
+    "pizza": 76,
+    "pork chop": 77,
+    "poutine": 78,
+    "prime rib": 79,
+    "pulled pork sandwich": 80,
+    "ramen": 81,
+    "ravioli": 82,
+    "red velvet cake": 83,
+    "risotto": 84,
+    "samosa": 85,
+    "sashimi": 86,
+    "scallops": 87,
+    "seaweed salad": 88,
+    "shrimp and grits": 89,
+    "spaghetti bolognese": 90,
+    "spaghetti carbonara": 91,
+    "spring rolls": 92,
+    "steak": 93,
+    "strawberry shortcake": 94,
+    "sushi": 95,
+    "tacos": 96,
+    "takoyaki": 97,
+    "tiramisu": 98,
+    "tuna tartare": 99,
+    "waffles": 100
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-food101-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet18-food101-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-food101-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-gtsrb-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/README.md b/resnet18-gtsrb-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..d9a3fe91a21e5c6d20975d7e2b03349b79bcaa76
--- /dev/null
+++ b/resnet18-gtsrb-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset gtsrb.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: gtsrb
+    pretrained: true
+test_datasets: null
+train_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: train
+type: transformers
+val_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: test
+```
+
diff --git a/resnet18-gtsrb-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/config.json b/resnet18-gtsrb-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..62569c7f31f507ee6f3882e2441b38c75ccc59f3
--- /dev/null
+++ b/resnet18-gtsrb-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,129 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "red and white circle 20 kph speed limit",
+    "1": "red and white circle 30 kph speed limit",
+    "2": "red and white circle 50 kph speed limit",
+    "3": "red and white circle 60 kph speed limit",
+    "4": "red and white circle 70 kph speed limit",
+    "5": "red and white circle 80 kph speed limit",
+    "6": "end / de-restriction of 80 kph speed limit",
+    "7": "red and white circle 100 kph speed limit",
+    "8": "red and white circle 120 kph speed limit",
+    "9": "red and white circle red car and black car no passing",
+    "10": "red and white circle red truck and black car no passing",
+    "11": "red and white triangle road intersection warning",
+    "12": "white and yellow diamond priority road",
+    "13": "red and white upside down triangle yield right-of-way",
+    "14": "stop",
+    "15": "empty red and white circle",
+    "16": "red and white circle no truck entry",
+    "17": "red circle with white horizonal stripe no entry",
+    "18": "red and white triangle with exclamation mark warning",
+    "19": "red and white triangle with black left curve approaching warning",
+    "20": "red and white triangle with black right curve approaching warning",
+    "21": "red and white triangle with black double curve approaching warning",
+    "22": "red and white triangle rough / bumpy road warning",
+    "23": "red and white triangle car skidding / slipping warning",
+    "24": "red and white triangle with merging / narrow lanes warning",
+    "25": "red and white triangle with person digging / construction / road work warning",
+    "26": "red and white triangle with traffic light approaching warning",
+    "27": "red and white triangle with person walking warning",
+    "28": "red and white triangle with child and person walking warning",
+    "29": "red and white triangle with bicyle warning",
+    "30": "red and white triangle with snowflake / ice warning",
+    "31": "red and white triangle with deer warning",
+    "32": "white circle with gray strike bar no speed limit",
+    "33": "blue circle with white right turn arrow mandatory",
+    "34": "blue circle with white left turn arrow mandatory",
+    "35": "blue circle with white forward arrow mandatory",
+    "36": "blue circle with white forward or right turn arrow mandatory",
+    "37": "blue circle with white forward or left turn arrow mandatory",
+    "38": "blue circle with white keep right arrow mandatory",
+    "39": "blue circle with white keep left arrow mandatory",
+    "40": "blue circle with white arrows indicating a traffic circle",
+    "41": "white circle with gray strike bar indicating no passing for cars has ended",
+    "42": "white circle with gray strike bar indicating no passing for trucks has ended"
+  },
+  "label2id": {
+    "blue circle with white arrows indicating a traffic circle": 40,
+    "blue circle with white forward arrow mandatory": 35,
+    "blue circle with white forward or left turn arrow mandatory": 37,
+    "blue circle with white forward or right turn arrow mandatory": 36,
+    "blue circle with white keep left arrow mandatory": 39,
+    "blue circle with white keep right arrow mandatory": 38,
+    "blue circle with white left turn arrow mandatory": 34,
+    "blue circle with white right turn arrow mandatory": 33,
+    "empty red and white circle": 15,
+    "end / de-restriction of 80 kph speed limit": 6,
+    "red and white circle 100 kph speed limit": 7,
+    "red and white circle 120 kph speed limit": 8,
+    "red and white circle 20 kph speed limit": 0,
+    "red and white circle 30 kph speed limit": 1,
+    "red and white circle 50 kph speed limit": 2,
+    "red and white circle 60 kph speed limit": 3,
+    "red and white circle 70 kph speed limit": 4,
+    "red and white circle 80 kph speed limit": 5,
+    "red and white circle no truck entry": 16,
+    "red and white circle red car and black car no passing": 9,
+    "red and white circle red truck and black car no passing": 10,
+    "red and white triangle car skidding / slipping warning": 23,
+    "red and white triangle road intersection warning": 11,
+    "red and white triangle rough / bumpy road warning": 22,
+    "red and white triangle with bicyle warning": 29,
+    "red and white triangle with black double curve approaching warning": 21,
+    "red and white triangle with black left curve approaching warning": 19,
+    "red and white triangle with black right curve approaching warning": 20,
+    "red and white triangle with child and person walking warning": 28,
+    "red and white triangle with deer warning": 31,
+    "red and white triangle with exclamation mark warning": 18,
+    "red and white triangle with merging / narrow lanes warning": 24,
+    "red and white triangle with person digging / construction / road work warning": 25,
+    "red and white triangle with person walking warning": 27,
+    "red and white triangle with snowflake / ice warning": 30,
+    "red and white triangle with traffic light approaching warning": 26,
+    "red and white upside down triangle yield right-of-way": 13,
+    "red circle with white horizonal stripe no entry": 17,
+    "stop": 14,
+    "white and yellow diamond priority road": 12,
+    "white circle with gray strike bar indicating no passing for cars has ended": 41,
+    "white circle with gray strike bar indicating no passing for trucks has ended": 42,
+    "white circle with gray strike bar no speed limit": 32
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-gtsrb-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet18-gtsrb-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-gtsrb-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-gtsrb-batch_size_128_lr_0.005_training_data_ratio_0.8-1000/README.md b/resnet18-gtsrb-batch_size_128_lr_0.005_training_data_ratio_0.8-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..b5a8f730e4c1761c1101bb34890b7c718e7419b6
--- /dev/null
+++ b/resnet18-gtsrb-batch_size_128_lr_0.005_training_data_ratio_0.8-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset gtsrb.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: gtsrb
+    pretrained: true
+test_datasets: null
+train_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: train
+type: transformers
+val_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: test
+```
+
diff --git a/resnet18-gtsrb-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/README.md b/resnet18-gtsrb-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..9b846b3f8aedce705ed8fd9671c4836fac5eab62
--- /dev/null
+++ b/resnet18-gtsrb-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset gtsrb.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: gtsrb
+    pretrained: true
+test_datasets: null
+train_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: train
+type: transformers
+val_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: test
+```
+
diff --git a/resnet18-gtsrb-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/config.json b/resnet18-gtsrb-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..62569c7f31f507ee6f3882e2441b38c75ccc59f3
--- /dev/null
+++ b/resnet18-gtsrb-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,129 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "red and white circle 20 kph speed limit",
+    "1": "red and white circle 30 kph speed limit",
+    "2": "red and white circle 50 kph speed limit",
+    "3": "red and white circle 60 kph speed limit",
+    "4": "red and white circle 70 kph speed limit",
+    "5": "red and white circle 80 kph speed limit",
+    "6": "end / de-restriction of 80 kph speed limit",
+    "7": "red and white circle 100 kph speed limit",
+    "8": "red and white circle 120 kph speed limit",
+    "9": "red and white circle red car and black car no passing",
+    "10": "red and white circle red truck and black car no passing",
+    "11": "red and white triangle road intersection warning",
+    "12": "white and yellow diamond priority road",
+    "13": "red and white upside down triangle yield right-of-way",
+    "14": "stop",
+    "15": "empty red and white circle",
+    "16": "red and white circle no truck entry",
+    "17": "red circle with white horizonal stripe no entry",
+    "18": "red and white triangle with exclamation mark warning",
+    "19": "red and white triangle with black left curve approaching warning",
+    "20": "red and white triangle with black right curve approaching warning",
+    "21": "red and white triangle with black double curve approaching warning",
+    "22": "red and white triangle rough / bumpy road warning",
+    "23": "red and white triangle car skidding / slipping warning",
+    "24": "red and white triangle with merging / narrow lanes warning",
+    "25": "red and white triangle with person digging / construction / road work warning",
+    "26": "red and white triangle with traffic light approaching warning",
+    "27": "red and white triangle with person walking warning",
+    "28": "red and white triangle with child and person walking warning",
+    "29": "red and white triangle with bicyle warning",
+    "30": "red and white triangle with snowflake / ice warning",
+    "31": "red and white triangle with deer warning",
+    "32": "white circle with gray strike bar no speed limit",
+    "33": "blue circle with white right turn arrow mandatory",
+    "34": "blue circle with white left turn arrow mandatory",
+    "35": "blue circle with white forward arrow mandatory",
+    "36": "blue circle with white forward or right turn arrow mandatory",
+    "37": "blue circle with white forward or left turn arrow mandatory",
+    "38": "blue circle with white keep right arrow mandatory",
+    "39": "blue circle with white keep left arrow mandatory",
+    "40": "blue circle with white arrows indicating a traffic circle",
+    "41": "white circle with gray strike bar indicating no passing for cars has ended",
+    "42": "white circle with gray strike bar indicating no passing for trucks has ended"
+  },
+  "label2id": {
+    "blue circle with white arrows indicating a traffic circle": 40,
+    "blue circle with white forward arrow mandatory": 35,
+    "blue circle with white forward or left turn arrow mandatory": 37,
+    "blue circle with white forward or right turn arrow mandatory": 36,
+    "blue circle with white keep left arrow mandatory": 39,
+    "blue circle with white keep right arrow mandatory": 38,
+    "blue circle with white left turn arrow mandatory": 34,
+    "blue circle with white right turn arrow mandatory": 33,
+    "empty red and white circle": 15,
+    "end / de-restriction of 80 kph speed limit": 6,
+    "red and white circle 100 kph speed limit": 7,
+    "red and white circle 120 kph speed limit": 8,
+    "red and white circle 20 kph speed limit": 0,
+    "red and white circle 30 kph speed limit": 1,
+    "red and white circle 50 kph speed limit": 2,
+    "red and white circle 60 kph speed limit": 3,
+    "red and white circle 70 kph speed limit": 4,
+    "red and white circle 80 kph speed limit": 5,
+    "red and white circle no truck entry": 16,
+    "red and white circle red car and black car no passing": 9,
+    "red and white circle red truck and black car no passing": 10,
+    "red and white triangle car skidding / slipping warning": 23,
+    "red and white triangle road intersection warning": 11,
+    "red and white triangle rough / bumpy road warning": 22,
+    "red and white triangle with bicyle warning": 29,
+    "red and white triangle with black double curve approaching warning": 21,
+    "red and white triangle with black left curve approaching warning": 19,
+    "red and white triangle with black right curve approaching warning": 20,
+    "red and white triangle with child and person walking warning": 28,
+    "red and white triangle with deer warning": 31,
+    "red and white triangle with exclamation mark warning": 18,
+    "red and white triangle with merging / narrow lanes warning": 24,
+    "red and white triangle with person digging / construction / road work warning": 25,
+    "red and white triangle with person walking warning": 27,
+    "red and white triangle with snowflake / ice warning": 30,
+    "red and white triangle with traffic light approaching warning": 26,
+    "red and white upside down triangle yield right-of-way": 13,
+    "red circle with white horizonal stripe no entry": 17,
+    "stop": 14,
+    "white and yellow diamond priority road": 12,
+    "white circle with gray strike bar indicating no passing for cars has ended": 41,
+    "white circle with gray strike bar indicating no passing for trucks has ended": 42,
+    "white circle with gray strike bar no speed limit": 32
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-gtsrb-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet18-gtsrb-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-gtsrb-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-gtsrb-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/README.md b/resnet18-gtsrb-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..bb270907bad7023e4886c270077e39dcb10b80da
--- /dev/null
+++ b/resnet18-gtsrb-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset gtsrb.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: gtsrb
+    pretrained: true
+test_datasets: null
+train_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: train
+type: transformers
+val_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: test
+```
+
diff --git a/resnet18-gtsrb-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/config.json b/resnet18-gtsrb-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..62569c7f31f507ee6f3882e2441b38c75ccc59f3
--- /dev/null
+++ b/resnet18-gtsrb-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,129 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "red and white circle 20 kph speed limit",
+    "1": "red and white circle 30 kph speed limit",
+    "2": "red and white circle 50 kph speed limit",
+    "3": "red and white circle 60 kph speed limit",
+    "4": "red and white circle 70 kph speed limit",
+    "5": "red and white circle 80 kph speed limit",
+    "6": "end / de-restriction of 80 kph speed limit",
+    "7": "red and white circle 100 kph speed limit",
+    "8": "red and white circle 120 kph speed limit",
+    "9": "red and white circle red car and black car no passing",
+    "10": "red and white circle red truck and black car no passing",
+    "11": "red and white triangle road intersection warning",
+    "12": "white and yellow diamond priority road",
+    "13": "red and white upside down triangle yield right-of-way",
+    "14": "stop",
+    "15": "empty red and white circle",
+    "16": "red and white circle no truck entry",
+    "17": "red circle with white horizonal stripe no entry",
+    "18": "red and white triangle with exclamation mark warning",
+    "19": "red and white triangle with black left curve approaching warning",
+    "20": "red and white triangle with black right curve approaching warning",
+    "21": "red and white triangle with black double curve approaching warning",
+    "22": "red and white triangle rough / bumpy road warning",
+    "23": "red and white triangle car skidding / slipping warning",
+    "24": "red and white triangle with merging / narrow lanes warning",
+    "25": "red and white triangle with person digging / construction / road work warning",
+    "26": "red and white triangle with traffic light approaching warning",
+    "27": "red and white triangle with person walking warning",
+    "28": "red and white triangle with child and person walking warning",
+    "29": "red and white triangle with bicyle warning",
+    "30": "red and white triangle with snowflake / ice warning",
+    "31": "red and white triangle with deer warning",
+    "32": "white circle with gray strike bar no speed limit",
+    "33": "blue circle with white right turn arrow mandatory",
+    "34": "blue circle with white left turn arrow mandatory",
+    "35": "blue circle with white forward arrow mandatory",
+    "36": "blue circle with white forward or right turn arrow mandatory",
+    "37": "blue circle with white forward or left turn arrow mandatory",
+    "38": "blue circle with white keep right arrow mandatory",
+    "39": "blue circle with white keep left arrow mandatory",
+    "40": "blue circle with white arrows indicating a traffic circle",
+    "41": "white circle with gray strike bar indicating no passing for cars has ended",
+    "42": "white circle with gray strike bar indicating no passing for trucks has ended"
+  },
+  "label2id": {
+    "blue circle with white arrows indicating a traffic circle": 40,
+    "blue circle with white forward arrow mandatory": 35,
+    "blue circle with white forward or left turn arrow mandatory": 37,
+    "blue circle with white forward or right turn arrow mandatory": 36,
+    "blue circle with white keep left arrow mandatory": 39,
+    "blue circle with white keep right arrow mandatory": 38,
+    "blue circle with white left turn arrow mandatory": 34,
+    "blue circle with white right turn arrow mandatory": 33,
+    "empty red and white circle": 15,
+    "end / de-restriction of 80 kph speed limit": 6,
+    "red and white circle 100 kph speed limit": 7,
+    "red and white circle 120 kph speed limit": 8,
+    "red and white circle 20 kph speed limit": 0,
+    "red and white circle 30 kph speed limit": 1,
+    "red and white circle 50 kph speed limit": 2,
+    "red and white circle 60 kph speed limit": 3,
+    "red and white circle 70 kph speed limit": 4,
+    "red and white circle 80 kph speed limit": 5,
+    "red and white circle no truck entry": 16,
+    "red and white circle red car and black car no passing": 9,
+    "red and white circle red truck and black car no passing": 10,
+    "red and white triangle car skidding / slipping warning": 23,
+    "red and white triangle road intersection warning": 11,
+    "red and white triangle rough / bumpy road warning": 22,
+    "red and white triangle with bicyle warning": 29,
+    "red and white triangle with black double curve approaching warning": 21,
+    "red and white triangle with black left curve approaching warning": 19,
+    "red and white triangle with black right curve approaching warning": 20,
+    "red and white triangle with child and person walking warning": 28,
+    "red and white triangle with deer warning": 31,
+    "red and white triangle with exclamation mark warning": 18,
+    "red and white triangle with merging / narrow lanes warning": 24,
+    "red and white triangle with person digging / construction / road work warning": 25,
+    "red and white triangle with person walking warning": 27,
+    "red and white triangle with snowflake / ice warning": 30,
+    "red and white triangle with traffic light approaching warning": 26,
+    "red and white upside down triangle yield right-of-way": 13,
+    "red circle with white horizonal stripe no entry": 17,
+    "stop": 14,
+    "white and yellow diamond priority road": 12,
+    "white circle with gray strike bar indicating no passing for cars has ended": 41,
+    "white circle with gray strike bar indicating no passing for trucks has ended": 42,
+    "white circle with gray strike bar no speed limit": 32
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-gtsrb-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet18-gtsrb-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-gtsrb-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-gtsrb-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/README.md b/resnet18-gtsrb-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..3ebcc6b5d5fc1f2b1c7cd1a8c585117909dbe99c
--- /dev/null
+++ b/resnet18-gtsrb-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset gtsrb.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: gtsrb
+    pretrained: true
+test_datasets: null
+train_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: train
+type: transformers
+val_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: test
+```
+
diff --git a/resnet18-gtsrb-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/config.json b/resnet18-gtsrb-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..62569c7f31f507ee6f3882e2441b38c75ccc59f3
--- /dev/null
+++ b/resnet18-gtsrb-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,129 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "red and white circle 20 kph speed limit",
+    "1": "red and white circle 30 kph speed limit",
+    "2": "red and white circle 50 kph speed limit",
+    "3": "red and white circle 60 kph speed limit",
+    "4": "red and white circle 70 kph speed limit",
+    "5": "red and white circle 80 kph speed limit",
+    "6": "end / de-restriction of 80 kph speed limit",
+    "7": "red and white circle 100 kph speed limit",
+    "8": "red and white circle 120 kph speed limit",
+    "9": "red and white circle red car and black car no passing",
+    "10": "red and white circle red truck and black car no passing",
+    "11": "red and white triangle road intersection warning",
+    "12": "white and yellow diamond priority road",
+    "13": "red and white upside down triangle yield right-of-way",
+    "14": "stop",
+    "15": "empty red and white circle",
+    "16": "red and white circle no truck entry",
+    "17": "red circle with white horizonal stripe no entry",
+    "18": "red and white triangle with exclamation mark warning",
+    "19": "red and white triangle with black left curve approaching warning",
+    "20": "red and white triangle with black right curve approaching warning",
+    "21": "red and white triangle with black double curve approaching warning",
+    "22": "red and white triangle rough / bumpy road warning",
+    "23": "red and white triangle car skidding / slipping warning",
+    "24": "red and white triangle with merging / narrow lanes warning",
+    "25": "red and white triangle with person digging / construction / road work warning",
+    "26": "red and white triangle with traffic light approaching warning",
+    "27": "red and white triangle with person walking warning",
+    "28": "red and white triangle with child and person walking warning",
+    "29": "red and white triangle with bicyle warning",
+    "30": "red and white triangle with snowflake / ice warning",
+    "31": "red and white triangle with deer warning",
+    "32": "white circle with gray strike bar no speed limit",
+    "33": "blue circle with white right turn arrow mandatory",
+    "34": "blue circle with white left turn arrow mandatory",
+    "35": "blue circle with white forward arrow mandatory",
+    "36": "blue circle with white forward or right turn arrow mandatory",
+    "37": "blue circle with white forward or left turn arrow mandatory",
+    "38": "blue circle with white keep right arrow mandatory",
+    "39": "blue circle with white keep left arrow mandatory",
+    "40": "blue circle with white arrows indicating a traffic circle",
+    "41": "white circle with gray strike bar indicating no passing for cars has ended",
+    "42": "white circle with gray strike bar indicating no passing for trucks has ended"
+  },
+  "label2id": {
+    "blue circle with white arrows indicating a traffic circle": 40,
+    "blue circle with white forward arrow mandatory": 35,
+    "blue circle with white forward or left turn arrow mandatory": 37,
+    "blue circle with white forward or right turn arrow mandatory": 36,
+    "blue circle with white keep left arrow mandatory": 39,
+    "blue circle with white keep right arrow mandatory": 38,
+    "blue circle with white left turn arrow mandatory": 34,
+    "blue circle with white right turn arrow mandatory": 33,
+    "empty red and white circle": 15,
+    "end / de-restriction of 80 kph speed limit": 6,
+    "red and white circle 100 kph speed limit": 7,
+    "red and white circle 120 kph speed limit": 8,
+    "red and white circle 20 kph speed limit": 0,
+    "red and white circle 30 kph speed limit": 1,
+    "red and white circle 50 kph speed limit": 2,
+    "red and white circle 60 kph speed limit": 3,
+    "red and white circle 70 kph speed limit": 4,
+    "red and white circle 80 kph speed limit": 5,
+    "red and white circle no truck entry": 16,
+    "red and white circle red car and black car no passing": 9,
+    "red and white circle red truck and black car no passing": 10,
+    "red and white triangle car skidding / slipping warning": 23,
+    "red and white triangle road intersection warning": 11,
+    "red and white triangle rough / bumpy road warning": 22,
+    "red and white triangle with bicyle warning": 29,
+    "red and white triangle with black double curve approaching warning": 21,
+    "red and white triangle with black left curve approaching warning": 19,
+    "red and white triangle with black right curve approaching warning": 20,
+    "red and white triangle with child and person walking warning": 28,
+    "red and white triangle with deer warning": 31,
+    "red and white triangle with exclamation mark warning": 18,
+    "red and white triangle with merging / narrow lanes warning": 24,
+    "red and white triangle with person digging / construction / road work warning": 25,
+    "red and white triangle with person walking warning": 27,
+    "red and white triangle with snowflake / ice warning": 30,
+    "red and white triangle with traffic light approaching warning": 26,
+    "red and white upside down triangle yield right-of-way": 13,
+    "red circle with white horizonal stripe no entry": 17,
+    "stop": 14,
+    "white and yellow diamond priority road": 12,
+    "white circle with gray strike bar indicating no passing for cars has ended": 41,
+    "white circle with gray strike bar indicating no passing for trucks has ended": 42,
+    "white circle with gray strike bar no speed limit": 32
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-gtsrb-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet18-gtsrb-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-gtsrb-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/README.md b/resnet18-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..4a9620883123aac01576429de1a508810a3f7425
--- /dev/null
+++ b/resnet18-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset gtsrb.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: gtsrb
+    pretrained: true
+test_datasets: null
+train_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: train
+type: transformers
+val_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: test
+```
+
diff --git a/resnet18-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/config.json b/resnet18-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..62569c7f31f507ee6f3882e2441b38c75ccc59f3
--- /dev/null
+++ b/resnet18-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,129 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "red and white circle 20 kph speed limit",
+    "1": "red and white circle 30 kph speed limit",
+    "2": "red and white circle 50 kph speed limit",
+    "3": "red and white circle 60 kph speed limit",
+    "4": "red and white circle 70 kph speed limit",
+    "5": "red and white circle 80 kph speed limit",
+    "6": "end / de-restriction of 80 kph speed limit",
+    "7": "red and white circle 100 kph speed limit",
+    "8": "red and white circle 120 kph speed limit",
+    "9": "red and white circle red car and black car no passing",
+    "10": "red and white circle red truck and black car no passing",
+    "11": "red and white triangle road intersection warning",
+    "12": "white and yellow diamond priority road",
+    "13": "red and white upside down triangle yield right-of-way",
+    "14": "stop",
+    "15": "empty red and white circle",
+    "16": "red and white circle no truck entry",
+    "17": "red circle with white horizonal stripe no entry",
+    "18": "red and white triangle with exclamation mark warning",
+    "19": "red and white triangle with black left curve approaching warning",
+    "20": "red and white triangle with black right curve approaching warning",
+    "21": "red and white triangle with black double curve approaching warning",
+    "22": "red and white triangle rough / bumpy road warning",
+    "23": "red and white triangle car skidding / slipping warning",
+    "24": "red and white triangle with merging / narrow lanes warning",
+    "25": "red and white triangle with person digging / construction / road work warning",
+    "26": "red and white triangle with traffic light approaching warning",
+    "27": "red and white triangle with person walking warning",
+    "28": "red and white triangle with child and person walking warning",
+    "29": "red and white triangle with bicyle warning",
+    "30": "red and white triangle with snowflake / ice warning",
+    "31": "red and white triangle with deer warning",
+    "32": "white circle with gray strike bar no speed limit",
+    "33": "blue circle with white right turn arrow mandatory",
+    "34": "blue circle with white left turn arrow mandatory",
+    "35": "blue circle with white forward arrow mandatory",
+    "36": "blue circle with white forward or right turn arrow mandatory",
+    "37": "blue circle with white forward or left turn arrow mandatory",
+    "38": "blue circle with white keep right arrow mandatory",
+    "39": "blue circle with white keep left arrow mandatory",
+    "40": "blue circle with white arrows indicating a traffic circle",
+    "41": "white circle with gray strike bar indicating no passing for cars has ended",
+    "42": "white circle with gray strike bar indicating no passing for trucks has ended"
+  },
+  "label2id": {
+    "blue circle with white arrows indicating a traffic circle": 40,
+    "blue circle with white forward arrow mandatory": 35,
+    "blue circle with white forward or left turn arrow mandatory": 37,
+    "blue circle with white forward or right turn arrow mandatory": 36,
+    "blue circle with white keep left arrow mandatory": 39,
+    "blue circle with white keep right arrow mandatory": 38,
+    "blue circle with white left turn arrow mandatory": 34,
+    "blue circle with white right turn arrow mandatory": 33,
+    "empty red and white circle": 15,
+    "end / de-restriction of 80 kph speed limit": 6,
+    "red and white circle 100 kph speed limit": 7,
+    "red and white circle 120 kph speed limit": 8,
+    "red and white circle 20 kph speed limit": 0,
+    "red and white circle 30 kph speed limit": 1,
+    "red and white circle 50 kph speed limit": 2,
+    "red and white circle 60 kph speed limit": 3,
+    "red and white circle 70 kph speed limit": 4,
+    "red and white circle 80 kph speed limit": 5,
+    "red and white circle no truck entry": 16,
+    "red and white circle red car and black car no passing": 9,
+    "red and white circle red truck and black car no passing": 10,
+    "red and white triangle car skidding / slipping warning": 23,
+    "red and white triangle road intersection warning": 11,
+    "red and white triangle rough / bumpy road warning": 22,
+    "red and white triangle with bicyle warning": 29,
+    "red and white triangle with black double curve approaching warning": 21,
+    "red and white triangle with black left curve approaching warning": 19,
+    "red and white triangle with black right curve approaching warning": 20,
+    "red and white triangle with child and person walking warning": 28,
+    "red and white triangle with deer warning": 31,
+    "red and white triangle with exclamation mark warning": 18,
+    "red and white triangle with merging / narrow lanes warning": 24,
+    "red and white triangle with person digging / construction / road work warning": 25,
+    "red and white triangle with person walking warning": 27,
+    "red and white triangle with snowflake / ice warning": 30,
+    "red and white triangle with traffic light approaching warning": 26,
+    "red and white upside down triangle yield right-of-way": 13,
+    "red circle with white horizonal stripe no entry": 17,
+    "stop": 14,
+    "white and yellow diamond priority road": 12,
+    "white circle with gray strike bar indicating no passing for cars has ended": 41,
+    "white circle with gray strike bar indicating no passing for trucks has ended": 42,
+    "white circle with gray strike bar no speed limit": 32
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet18-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/README.md b/resnet18-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..bd0fa88a93f315700a0973edb4e7184f89df10c4
--- /dev/null
+++ b/resnet18-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset gtsrb.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: gtsrb
+    pretrained: true
+test_datasets: null
+train_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: train
+type: transformers
+val_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: test
+```
+
diff --git a/resnet18-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/config.json b/resnet18-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..62569c7f31f507ee6f3882e2441b38c75ccc59f3
--- /dev/null
+++ b/resnet18-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,129 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "red and white circle 20 kph speed limit",
+    "1": "red and white circle 30 kph speed limit",
+    "2": "red and white circle 50 kph speed limit",
+    "3": "red and white circle 60 kph speed limit",
+    "4": "red and white circle 70 kph speed limit",
+    "5": "red and white circle 80 kph speed limit",
+    "6": "end / de-restriction of 80 kph speed limit",
+    "7": "red and white circle 100 kph speed limit",
+    "8": "red and white circle 120 kph speed limit",
+    "9": "red and white circle red car and black car no passing",
+    "10": "red and white circle red truck and black car no passing",
+    "11": "red and white triangle road intersection warning",
+    "12": "white and yellow diamond priority road",
+    "13": "red and white upside down triangle yield right-of-way",
+    "14": "stop",
+    "15": "empty red and white circle",
+    "16": "red and white circle no truck entry",
+    "17": "red circle with white horizonal stripe no entry",
+    "18": "red and white triangle with exclamation mark warning",
+    "19": "red and white triangle with black left curve approaching warning",
+    "20": "red and white triangle with black right curve approaching warning",
+    "21": "red and white triangle with black double curve approaching warning",
+    "22": "red and white triangle rough / bumpy road warning",
+    "23": "red and white triangle car skidding / slipping warning",
+    "24": "red and white triangle with merging / narrow lanes warning",
+    "25": "red and white triangle with person digging / construction / road work warning",
+    "26": "red and white triangle with traffic light approaching warning",
+    "27": "red and white triangle with person walking warning",
+    "28": "red and white triangle with child and person walking warning",
+    "29": "red and white triangle with bicyle warning",
+    "30": "red and white triangle with snowflake / ice warning",
+    "31": "red and white triangle with deer warning",
+    "32": "white circle with gray strike bar no speed limit",
+    "33": "blue circle with white right turn arrow mandatory",
+    "34": "blue circle with white left turn arrow mandatory",
+    "35": "blue circle with white forward arrow mandatory",
+    "36": "blue circle with white forward or right turn arrow mandatory",
+    "37": "blue circle with white forward or left turn arrow mandatory",
+    "38": "blue circle with white keep right arrow mandatory",
+    "39": "blue circle with white keep left arrow mandatory",
+    "40": "blue circle with white arrows indicating a traffic circle",
+    "41": "white circle with gray strike bar indicating no passing for cars has ended",
+    "42": "white circle with gray strike bar indicating no passing for trucks has ended"
+  },
+  "label2id": {
+    "blue circle with white arrows indicating a traffic circle": 40,
+    "blue circle with white forward arrow mandatory": 35,
+    "blue circle with white forward or left turn arrow mandatory": 37,
+    "blue circle with white forward or right turn arrow mandatory": 36,
+    "blue circle with white keep left arrow mandatory": 39,
+    "blue circle with white keep right arrow mandatory": 38,
+    "blue circle with white left turn arrow mandatory": 34,
+    "blue circle with white right turn arrow mandatory": 33,
+    "empty red and white circle": 15,
+    "end / de-restriction of 80 kph speed limit": 6,
+    "red and white circle 100 kph speed limit": 7,
+    "red and white circle 120 kph speed limit": 8,
+    "red and white circle 20 kph speed limit": 0,
+    "red and white circle 30 kph speed limit": 1,
+    "red and white circle 50 kph speed limit": 2,
+    "red and white circle 60 kph speed limit": 3,
+    "red and white circle 70 kph speed limit": 4,
+    "red and white circle 80 kph speed limit": 5,
+    "red and white circle no truck entry": 16,
+    "red and white circle red car and black car no passing": 9,
+    "red and white circle red truck and black car no passing": 10,
+    "red and white triangle car skidding / slipping warning": 23,
+    "red and white triangle road intersection warning": 11,
+    "red and white triangle rough / bumpy road warning": 22,
+    "red and white triangle with bicyle warning": 29,
+    "red and white triangle with black double curve approaching warning": 21,
+    "red and white triangle with black left curve approaching warning": 19,
+    "red and white triangle with black right curve approaching warning": 20,
+    "red and white triangle with child and person walking warning": 28,
+    "red and white triangle with deer warning": 31,
+    "red and white triangle with exclamation mark warning": 18,
+    "red and white triangle with merging / narrow lanes warning": 24,
+    "red and white triangle with person digging / construction / road work warning": 25,
+    "red and white triangle with person walking warning": 27,
+    "red and white triangle with snowflake / ice warning": 30,
+    "red and white triangle with traffic light approaching warning": 26,
+    "red and white upside down triangle yield right-of-way": 13,
+    "red circle with white horizonal stripe no entry": 17,
+    "stop": 14,
+    "white and yellow diamond priority road": 12,
+    "white circle with gray strike bar indicating no passing for cars has ended": 41,
+    "white circle with gray strike bar indicating no passing for trucks has ended": 42,
+    "white circle with gray strike bar no speed limit": 32
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet18-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-gtsrb-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/README.md b/resnet18-gtsrb-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..c18114b4de8d6aebd796d099e1ed0a8d9fc3e251
--- /dev/null
+++ b/resnet18-gtsrb-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset gtsrb.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: gtsrb
+    pretrained: true
+test_datasets: null
+train_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: train
+type: transformers
+val_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: test
+```
+
diff --git a/resnet18-gtsrb-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/config.json b/resnet18-gtsrb-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..62569c7f31f507ee6f3882e2441b38c75ccc59f3
--- /dev/null
+++ b/resnet18-gtsrb-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,129 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "red and white circle 20 kph speed limit",
+    "1": "red and white circle 30 kph speed limit",
+    "2": "red and white circle 50 kph speed limit",
+    "3": "red and white circle 60 kph speed limit",
+    "4": "red and white circle 70 kph speed limit",
+    "5": "red and white circle 80 kph speed limit",
+    "6": "end / de-restriction of 80 kph speed limit",
+    "7": "red and white circle 100 kph speed limit",
+    "8": "red and white circle 120 kph speed limit",
+    "9": "red and white circle red car and black car no passing",
+    "10": "red and white circle red truck and black car no passing",
+    "11": "red and white triangle road intersection warning",
+    "12": "white and yellow diamond priority road",
+    "13": "red and white upside down triangle yield right-of-way",
+    "14": "stop",
+    "15": "empty red and white circle",
+    "16": "red and white circle no truck entry",
+    "17": "red circle with white horizonal stripe no entry",
+    "18": "red and white triangle with exclamation mark warning",
+    "19": "red and white triangle with black left curve approaching warning",
+    "20": "red and white triangle with black right curve approaching warning",
+    "21": "red and white triangle with black double curve approaching warning",
+    "22": "red and white triangle rough / bumpy road warning",
+    "23": "red and white triangle car skidding / slipping warning",
+    "24": "red and white triangle with merging / narrow lanes warning",
+    "25": "red and white triangle with person digging / construction / road work warning",
+    "26": "red and white triangle with traffic light approaching warning",
+    "27": "red and white triangle with person walking warning",
+    "28": "red and white triangle with child and person walking warning",
+    "29": "red and white triangle with bicyle warning",
+    "30": "red and white triangle with snowflake / ice warning",
+    "31": "red and white triangle with deer warning",
+    "32": "white circle with gray strike bar no speed limit",
+    "33": "blue circle with white right turn arrow mandatory",
+    "34": "blue circle with white left turn arrow mandatory",
+    "35": "blue circle with white forward arrow mandatory",
+    "36": "blue circle with white forward or right turn arrow mandatory",
+    "37": "blue circle with white forward or left turn arrow mandatory",
+    "38": "blue circle with white keep right arrow mandatory",
+    "39": "blue circle with white keep left arrow mandatory",
+    "40": "blue circle with white arrows indicating a traffic circle",
+    "41": "white circle with gray strike bar indicating no passing for cars has ended",
+    "42": "white circle with gray strike bar indicating no passing for trucks has ended"
+  },
+  "label2id": {
+    "blue circle with white arrows indicating a traffic circle": 40,
+    "blue circle with white forward arrow mandatory": 35,
+    "blue circle with white forward or left turn arrow mandatory": 37,
+    "blue circle with white forward or right turn arrow mandatory": 36,
+    "blue circle with white keep left arrow mandatory": 39,
+    "blue circle with white keep right arrow mandatory": 38,
+    "blue circle with white left turn arrow mandatory": 34,
+    "blue circle with white right turn arrow mandatory": 33,
+    "empty red and white circle": 15,
+    "end / de-restriction of 80 kph speed limit": 6,
+    "red and white circle 100 kph speed limit": 7,
+    "red and white circle 120 kph speed limit": 8,
+    "red and white circle 20 kph speed limit": 0,
+    "red and white circle 30 kph speed limit": 1,
+    "red and white circle 50 kph speed limit": 2,
+    "red and white circle 60 kph speed limit": 3,
+    "red and white circle 70 kph speed limit": 4,
+    "red and white circle 80 kph speed limit": 5,
+    "red and white circle no truck entry": 16,
+    "red and white circle red car and black car no passing": 9,
+    "red and white circle red truck and black car no passing": 10,
+    "red and white triangle car skidding / slipping warning": 23,
+    "red and white triangle road intersection warning": 11,
+    "red and white triangle rough / bumpy road warning": 22,
+    "red and white triangle with bicyle warning": 29,
+    "red and white triangle with black double curve approaching warning": 21,
+    "red and white triangle with black left curve approaching warning": 19,
+    "red and white triangle with black right curve approaching warning": 20,
+    "red and white triangle with child and person walking warning": 28,
+    "red and white triangle with deer warning": 31,
+    "red and white triangle with exclamation mark warning": 18,
+    "red and white triangle with merging / narrow lanes warning": 24,
+    "red and white triangle with person digging / construction / road work warning": 25,
+    "red and white triangle with person walking warning": 27,
+    "red and white triangle with snowflake / ice warning": 30,
+    "red and white triangle with traffic light approaching warning": 26,
+    "red and white upside down triangle yield right-of-way": 13,
+    "red circle with white horizonal stripe no entry": 17,
+    "stop": 14,
+    "white and yellow diamond priority road": 12,
+    "white circle with gray strike bar indicating no passing for cars has ended": 41,
+    "white circle with gray strike bar indicating no passing for trucks has ended": 42,
+    "white circle with gray strike bar no speed limit": 32
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-gtsrb-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet18-gtsrb-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-gtsrb-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.8-1000/README.md b/resnet18-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.8-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..9de0aad1bc05bc7b91e5994c0e58446bbdc72606
--- /dev/null
+++ b/resnet18-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.8-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset kmnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: kmnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: train
+type: transformers
+val_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: test
+```
+
diff --git a/resnet18-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.8-1000/config.json b/resnet18-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.8-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..54cae3827bd20f790075f990d3712f8342d20c79
--- /dev/null
+++ b/resnet18-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.8-1000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "\u304a",
+    "1": "\u304d",
+    "2": "\u3059",
+    "3": "\u3064",
+    "4": "\u306a",
+    "5": "\u306f",
+    "6": "\u307e",
+    "7": "\u3084",
+    "8": "\u308c",
+    "9": "\u3092"
+  },
+  "label2id": {
+    "\u304a": 0,
+    "\u304d": 1,
+    "\u3059": 2,
+    "\u3064": 3,
+    "\u306a": 4,
+    "\u306f": 5,
+    "\u307e": 6,
+    "\u3084": 7,
+    "\u308c": 8,
+    "\u3092": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet18-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.8-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.8-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-kmnist-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/README.md b/resnet18-kmnist-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..ccc607e9824b2e1b01cbfb8ebe1aae87bb7e7325
--- /dev/null
+++ b/resnet18-kmnist-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset kmnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: kmnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: train
+type: transformers
+val_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: test
+```
+
diff --git a/resnet18-kmnist-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/config.json b/resnet18-kmnist-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..54cae3827bd20f790075f990d3712f8342d20c79
--- /dev/null
+++ b/resnet18-kmnist-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "\u304a",
+    "1": "\u304d",
+    "2": "\u3059",
+    "3": "\u3064",
+    "4": "\u306a",
+    "5": "\u306f",
+    "6": "\u307e",
+    "7": "\u3084",
+    "8": "\u308c",
+    "9": "\u3092"
+  },
+  "label2id": {
+    "\u304a": 0,
+    "\u304d": 1,
+    "\u3059": 2,
+    "\u3064": 3,
+    "\u306a": 4,
+    "\u306f": 5,
+    "\u307e": 6,
+    "\u3084": 7,
+    "\u308c": 8,
+    "\u3092": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-kmnist-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet18-kmnist-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-kmnist-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-kmnist-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/README.md b/resnet18-kmnist-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..308a78712588720dd4fe1f4060bf39fad6489f53
--- /dev/null
+++ b/resnet18-kmnist-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset kmnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: kmnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: train
+type: transformers
+val_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: test
+```
+
diff --git a/resnet18-kmnist-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/config.json b/resnet18-kmnist-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..54cae3827bd20f790075f990d3712f8342d20c79
--- /dev/null
+++ b/resnet18-kmnist-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "\u304a",
+    "1": "\u304d",
+    "2": "\u3059",
+    "3": "\u3064",
+    "4": "\u306a",
+    "5": "\u306f",
+    "6": "\u307e",
+    "7": "\u3084",
+    "8": "\u308c",
+    "9": "\u3092"
+  },
+  "label2id": {
+    "\u304a": 0,
+    "\u304d": 1,
+    "\u3059": 2,
+    "\u3064": 3,
+    "\u306a": 4,
+    "\u306f": 5,
+    "\u307e": 6,
+    "\u3084": 7,
+    "\u308c": 8,
+    "\u3092": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-kmnist-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet18-kmnist-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-kmnist-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-kmnist-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/README.md b/resnet18-kmnist-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..a317ebae6ab68d8c45e37c547948ae166b84623b
--- /dev/null
+++ b/resnet18-kmnist-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset kmnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: kmnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: train
+type: transformers
+val_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: test
+```
+
diff --git a/resnet18-kmnist-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/config.json b/resnet18-kmnist-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..54cae3827bd20f790075f990d3712f8342d20c79
--- /dev/null
+++ b/resnet18-kmnist-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "\u304a",
+    "1": "\u304d",
+    "2": "\u3059",
+    "3": "\u3064",
+    "4": "\u306a",
+    "5": "\u306f",
+    "6": "\u307e",
+    "7": "\u3084",
+    "8": "\u308c",
+    "9": "\u3092"
+  },
+  "label2id": {
+    "\u304a": 0,
+    "\u304d": 1,
+    "\u3059": 2,
+    "\u3064": 3,
+    "\u306a": 4,
+    "\u306f": 5,
+    "\u307e": 6,
+    "\u3084": 7,
+    "\u308c": 8,
+    "\u3092": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-kmnist-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet18-kmnist-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-kmnist-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-kmnist-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/README.md b/resnet18-kmnist-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..22fba3adf4826ec10d102618dfed50979214c417
--- /dev/null
+++ b/resnet18-kmnist-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset kmnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: kmnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: train
+type: transformers
+val_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: test
+```
+
diff --git a/resnet18-kmnist-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/config.json b/resnet18-kmnist-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..54cae3827bd20f790075f990d3712f8342d20c79
--- /dev/null
+++ b/resnet18-kmnist-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "\u304a",
+    "1": "\u304d",
+    "2": "\u3059",
+    "3": "\u3064",
+    "4": "\u306a",
+    "5": "\u306f",
+    "6": "\u307e",
+    "7": "\u3084",
+    "8": "\u308c",
+    "9": "\u3092"
+  },
+  "label2id": {
+    "\u304a": 0,
+    "\u304d": 1,
+    "\u3059": 2,
+    "\u3064": 3,
+    "\u306a": 4,
+    "\u306f": 5,
+    "\u307e": 6,
+    "\u3084": 7,
+    "\u308c": 8,
+    "\u3092": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-kmnist-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet18-kmnist-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-kmnist-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-kmnist-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/README.md b/resnet18-kmnist-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..77a338e2e7d7ba4406cf762e3636c76caf1d43ed
--- /dev/null
+++ b/resnet18-kmnist-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset kmnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: kmnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: train
+type: transformers
+val_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: test
+```
+
diff --git a/resnet18-kmnist-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/config.json b/resnet18-kmnist-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..54cae3827bd20f790075f990d3712f8342d20c79
--- /dev/null
+++ b/resnet18-kmnist-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "\u304a",
+    "1": "\u304d",
+    "2": "\u3059",
+    "3": "\u3064",
+    "4": "\u306a",
+    "5": "\u306f",
+    "6": "\u307e",
+    "7": "\u3084",
+    "8": "\u308c",
+    "9": "\u3092"
+  },
+  "label2id": {
+    "\u304a": 0,
+    "\u304d": 1,
+    "\u3059": 2,
+    "\u3064": 3,
+    "\u306a": 4,
+    "\u306f": 5,
+    "\u307e": 6,
+    "\u3084": 7,
+    "\u308c": 8,
+    "\u3092": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-kmnist-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet18-kmnist-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-kmnist-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-kmnist-batch_size_64_lr_0.01_training_data_ratio_1.0-2000/README.md b/resnet18-kmnist-batch_size_64_lr_0.01_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..d5967b851784f6320a0dbd1bff590a7f939969ad
--- /dev/null
+++ b/resnet18-kmnist-batch_size_64_lr_0.01_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset kmnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: kmnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: train
+type: transformers
+val_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: test
+```
+
diff --git a/resnet18-kmnist-batch_size_64_lr_0.01_training_data_ratio_1.0-2000/config.json b/resnet18-kmnist-batch_size_64_lr_0.01_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..54cae3827bd20f790075f990d3712f8342d20c79
--- /dev/null
+++ b/resnet18-kmnist-batch_size_64_lr_0.01_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "\u304a",
+    "1": "\u304d",
+    "2": "\u3059",
+    "3": "\u3064",
+    "4": "\u306a",
+    "5": "\u306f",
+    "6": "\u307e",
+    "7": "\u3084",
+    "8": "\u308c",
+    "9": "\u3092"
+  },
+  "label2id": {
+    "\u304a": 0,
+    "\u304d": 1,
+    "\u3059": 2,
+    "\u3064": 3,
+    "\u306a": 4,
+    "\u306f": 5,
+    "\u307e": 6,
+    "\u3084": 7,
+    "\u308c": 8,
+    "\u3092": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-kmnist-batch_size_64_lr_0.01_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet18-kmnist-batch_size_64_lr_0.01_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-kmnist-batch_size_64_lr_0.01_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-4000/README.md b/resnet18-mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..9609cad3aa6a83869438c1519f9ae419613a192b
--- /dev/null
+++ b/resnet18-mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: train
+type: transformers
+val_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: test
+```
+
diff --git a/resnet18-mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-4000/config.json b/resnet18-mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..018e7d4d1ef4a7995d309411e18d7bc5d8d5f4a9
--- /dev/null
+++ b/resnet18-mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet18-mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-mnist-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/README.md b/resnet18-mnist-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..21ca9af2c2066655c7b1351ac618e98222095f70
--- /dev/null
+++ b/resnet18-mnist-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: train
+type: transformers
+val_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: test
+```
+
diff --git a/resnet18-mnist-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/config.json b/resnet18-mnist-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..018e7d4d1ef4a7995d309411e18d7bc5d8d5f4a9
--- /dev/null
+++ b/resnet18-mnist-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-mnist-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet18-mnist-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-mnist-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-mnist-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/README.md b/resnet18-mnist-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..d02bd22f990bee047cebb74c40688f429b739c34
--- /dev/null
+++ b/resnet18-mnist-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: train
+type: transformers
+val_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: test
+```
+
diff --git a/resnet18-mnist-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/config.json b/resnet18-mnist-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..018e7d4d1ef4a7995d309411e18d7bc5d8d5f4a9
--- /dev/null
+++ b/resnet18-mnist-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-mnist-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet18-mnist-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-mnist-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/README.md b/resnet18-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..97ba07a37ba419802aa25cf0f58241992175c22f
--- /dev/null
+++ b/resnet18-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: train
+type: transformers
+val_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: test
+```
+
diff --git a/resnet18-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/config.json b/resnet18-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..018e7d4d1ef4a7995d309411e18d7bc5d8d5f4a9
--- /dev/null
+++ b/resnet18-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet18-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/README.md b/resnet18-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..97ba07a37ba419802aa25cf0f58241992175c22f
--- /dev/null
+++ b/resnet18-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: train
+type: transformers
+val_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: test
+```
+
diff --git a/resnet18-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/config.json b/resnet18-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..018e7d4d1ef4a7995d309411e18d7bc5d8d5f4a9
--- /dev/null
+++ b/resnet18-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet18-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-mnist-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/README.md b/resnet18-mnist-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..1982f5774d8536ddaf2b9474008333f066e6a8fa
--- /dev/null
+++ b/resnet18-mnist-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: train
+type: transformers
+val_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: test
+```
+
diff --git a/resnet18-mnist-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/config.json b/resnet18-mnist-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..018e7d4d1ef4a7995d309411e18d7bc5d8d5f4a9
--- /dev/null
+++ b/resnet18-mnist-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-mnist-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet18-mnist-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-mnist-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/README.md b/resnet18-mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..a9ed7c665c87d06f73ed9f7aada72afe05ceb0c7
--- /dev/null
+++ b/resnet18-mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: train
+type: transformers
+val_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: test
+```
+
diff --git a/resnet18-mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/config.json b/resnet18-mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..018e7d4d1ef4a7995d309411e18d7bc5d8d5f4a9
--- /dev/null
+++ b/resnet18-mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet18-mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-oxford-iiit-pet-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/README.md b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..150ce3db7db6c7071da43420d8ed6c450743dc38
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford-iiit-pet.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: oxford-iiit-pet
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford-iiit-pet:
+    _target_: datasets.load_dataset
+    path: timm/oxford-iiit-pet
+    split: train
+type: transformers
+val_datasets:
+  oxford-iiit-pet:
+    _target_: datasets.load_dataset
+    path: timm/oxford-iiit-pet
+    split: test
+```
+
diff --git a/resnet18-oxford-iiit-pet-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/config.json b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..fd54d9408eb0bfa96cb8fb062f40297ff8e043a3
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,117 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "abyssinian",
+    "1": "american_bulldog",
+    "2": "american_pit_bull_terrier",
+    "3": "basset_hound",
+    "4": "beagle",
+    "5": "bengal",
+    "6": "birman",
+    "7": "bombay",
+    "8": "boxer",
+    "9": "british_shorthair",
+    "10": "chihuahua",
+    "11": "egyptian_mau",
+    "12": "english_cocker_spaniel",
+    "13": "english_setter",
+    "14": "german_shorthaired",
+    "15": "great_pyrenees",
+    "16": "havanese",
+    "17": "japanese_chin",
+    "18": "keeshond",
+    "19": "leonberger",
+    "20": "maine_coon",
+    "21": "miniature_pinscher",
+    "22": "newfoundland",
+    "23": "persian",
+    "24": "pomeranian",
+    "25": "pug",
+    "26": "ragdoll",
+    "27": "russian_blue",
+    "28": "saint_bernard",
+    "29": "samoyed",
+    "30": "scottish_terrier",
+    "31": "shiba_inu",
+    "32": "siamese",
+    "33": "sphynx",
+    "34": "staffordshire_bull_terrier",
+    "35": "wheaten_terrier",
+    "36": "yorkshire_terrier"
+  },
+  "label2id": {
+    "abyssinian": 0,
+    "american_bulldog": 1,
+    "american_pit_bull_terrier": 2,
+    "basset_hound": 3,
+    "beagle": 4,
+    "bengal": 5,
+    "birman": 6,
+    "bombay": 7,
+    "boxer": 8,
+    "british_shorthair": 9,
+    "chihuahua": 10,
+    "egyptian_mau": 11,
+    "english_cocker_spaniel": 12,
+    "english_setter": 13,
+    "german_shorthaired": 14,
+    "great_pyrenees": 15,
+    "havanese": 16,
+    "japanese_chin": 17,
+    "keeshond": 18,
+    "leonberger": 19,
+    "maine_coon": 20,
+    "miniature_pinscher": 21,
+    "newfoundland": 22,
+    "persian": 23,
+    "pomeranian": 24,
+    "pug": 25,
+    "ragdoll": 26,
+    "russian_blue": 27,
+    "saint_bernard": 28,
+    "samoyed": 29,
+    "scottish_terrier": 30,
+    "shiba_inu": 31,
+    "siamese": 32,
+    "sphynx": 33,
+    "staffordshire_bull_terrier": 34,
+    "wheaten_terrier": 35,
+    "yorkshire_terrier": 36
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-oxford-iiit-pet-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-oxford-iiit-pet-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/README.md b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..724e6e8934b0eb25af36d61dd75a9bf939ad4451
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford-iiit-pet.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: oxford-iiit-pet
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford-iiit-pet:
+    _target_: datasets.load_dataset
+    path: timm/oxford-iiit-pet
+    split: train
+type: transformers
+val_datasets:
+  oxford-iiit-pet:
+    _target_: datasets.load_dataset
+    path: timm/oxford-iiit-pet
+    split: test
+```
+
diff --git a/resnet18-oxford-iiit-pet-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/config.json b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..fd54d9408eb0bfa96cb8fb062f40297ff8e043a3
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,117 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "abyssinian",
+    "1": "american_bulldog",
+    "2": "american_pit_bull_terrier",
+    "3": "basset_hound",
+    "4": "beagle",
+    "5": "bengal",
+    "6": "birman",
+    "7": "bombay",
+    "8": "boxer",
+    "9": "british_shorthair",
+    "10": "chihuahua",
+    "11": "egyptian_mau",
+    "12": "english_cocker_spaniel",
+    "13": "english_setter",
+    "14": "german_shorthaired",
+    "15": "great_pyrenees",
+    "16": "havanese",
+    "17": "japanese_chin",
+    "18": "keeshond",
+    "19": "leonberger",
+    "20": "maine_coon",
+    "21": "miniature_pinscher",
+    "22": "newfoundland",
+    "23": "persian",
+    "24": "pomeranian",
+    "25": "pug",
+    "26": "ragdoll",
+    "27": "russian_blue",
+    "28": "saint_bernard",
+    "29": "samoyed",
+    "30": "scottish_terrier",
+    "31": "shiba_inu",
+    "32": "siamese",
+    "33": "sphynx",
+    "34": "staffordshire_bull_terrier",
+    "35": "wheaten_terrier",
+    "36": "yorkshire_terrier"
+  },
+  "label2id": {
+    "abyssinian": 0,
+    "american_bulldog": 1,
+    "american_pit_bull_terrier": 2,
+    "basset_hound": 3,
+    "beagle": 4,
+    "bengal": 5,
+    "birman": 6,
+    "bombay": 7,
+    "boxer": 8,
+    "british_shorthair": 9,
+    "chihuahua": 10,
+    "egyptian_mau": 11,
+    "english_cocker_spaniel": 12,
+    "english_setter": 13,
+    "german_shorthaired": 14,
+    "great_pyrenees": 15,
+    "havanese": 16,
+    "japanese_chin": 17,
+    "keeshond": 18,
+    "leonberger": 19,
+    "maine_coon": 20,
+    "miniature_pinscher": 21,
+    "newfoundland": 22,
+    "persian": 23,
+    "pomeranian": 24,
+    "pug": 25,
+    "ragdoll": 26,
+    "russian_blue": 27,
+    "saint_bernard": 28,
+    "samoyed": 29,
+    "scottish_terrier": 30,
+    "shiba_inu": 31,
+    "siamese": 32,
+    "sphynx": 33,
+    "staffordshire_bull_terrier": 34,
+    "wheaten_terrier": 35,
+    "yorkshire_terrier": 36
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-oxford-iiit-pet-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-oxford-iiit-pet-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/README.md b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..724e6e8934b0eb25af36d61dd75a9bf939ad4451
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford-iiit-pet.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: oxford-iiit-pet
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford-iiit-pet:
+    _target_: datasets.load_dataset
+    path: timm/oxford-iiit-pet
+    split: train
+type: transformers
+val_datasets:
+  oxford-iiit-pet:
+    _target_: datasets.load_dataset
+    path: timm/oxford-iiit-pet
+    split: test
+```
+
diff --git a/resnet18-oxford-iiit-pet-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/config.json b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..fd54d9408eb0bfa96cb8fb062f40297ff8e043a3
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,117 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "abyssinian",
+    "1": "american_bulldog",
+    "2": "american_pit_bull_terrier",
+    "3": "basset_hound",
+    "4": "beagle",
+    "5": "bengal",
+    "6": "birman",
+    "7": "bombay",
+    "8": "boxer",
+    "9": "british_shorthair",
+    "10": "chihuahua",
+    "11": "egyptian_mau",
+    "12": "english_cocker_spaniel",
+    "13": "english_setter",
+    "14": "german_shorthaired",
+    "15": "great_pyrenees",
+    "16": "havanese",
+    "17": "japanese_chin",
+    "18": "keeshond",
+    "19": "leonberger",
+    "20": "maine_coon",
+    "21": "miniature_pinscher",
+    "22": "newfoundland",
+    "23": "persian",
+    "24": "pomeranian",
+    "25": "pug",
+    "26": "ragdoll",
+    "27": "russian_blue",
+    "28": "saint_bernard",
+    "29": "samoyed",
+    "30": "scottish_terrier",
+    "31": "shiba_inu",
+    "32": "siamese",
+    "33": "sphynx",
+    "34": "staffordshire_bull_terrier",
+    "35": "wheaten_terrier",
+    "36": "yorkshire_terrier"
+  },
+  "label2id": {
+    "abyssinian": 0,
+    "american_bulldog": 1,
+    "american_pit_bull_terrier": 2,
+    "basset_hound": 3,
+    "beagle": 4,
+    "bengal": 5,
+    "birman": 6,
+    "bombay": 7,
+    "boxer": 8,
+    "british_shorthair": 9,
+    "chihuahua": 10,
+    "egyptian_mau": 11,
+    "english_cocker_spaniel": 12,
+    "english_setter": 13,
+    "german_shorthaired": 14,
+    "great_pyrenees": 15,
+    "havanese": 16,
+    "japanese_chin": 17,
+    "keeshond": 18,
+    "leonberger": 19,
+    "maine_coon": 20,
+    "miniature_pinscher": 21,
+    "newfoundland": 22,
+    "persian": 23,
+    "pomeranian": 24,
+    "pug": 25,
+    "ragdoll": 26,
+    "russian_blue": 27,
+    "saint_bernard": 28,
+    "samoyed": 29,
+    "scottish_terrier": 30,
+    "shiba_inu": 31,
+    "siamese": 32,
+    "sphynx": 33,
+    "staffordshire_bull_terrier": 34,
+    "wheaten_terrier": 35,
+    "yorkshire_terrier": 36
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/README.md b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..01efd57364856ec6658ca27adaf4c1f4fdbe1b65
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford-iiit-pet.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: oxford-iiit-pet
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford-iiit-pet:
+    _target_: datasets.load_dataset
+    path: timm/oxford-iiit-pet
+    split: train
+type: transformers
+val_datasets:
+  oxford-iiit-pet:
+    _target_: datasets.load_dataset
+    path: timm/oxford-iiit-pet
+    split: test
+```
+
diff --git a/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/config.json b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..fd54d9408eb0bfa96cb8fb062f40297ff8e043a3
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,117 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "abyssinian",
+    "1": "american_bulldog",
+    "2": "american_pit_bull_terrier",
+    "3": "basset_hound",
+    "4": "beagle",
+    "5": "bengal",
+    "6": "birman",
+    "7": "bombay",
+    "8": "boxer",
+    "9": "british_shorthair",
+    "10": "chihuahua",
+    "11": "egyptian_mau",
+    "12": "english_cocker_spaniel",
+    "13": "english_setter",
+    "14": "german_shorthaired",
+    "15": "great_pyrenees",
+    "16": "havanese",
+    "17": "japanese_chin",
+    "18": "keeshond",
+    "19": "leonberger",
+    "20": "maine_coon",
+    "21": "miniature_pinscher",
+    "22": "newfoundland",
+    "23": "persian",
+    "24": "pomeranian",
+    "25": "pug",
+    "26": "ragdoll",
+    "27": "russian_blue",
+    "28": "saint_bernard",
+    "29": "samoyed",
+    "30": "scottish_terrier",
+    "31": "shiba_inu",
+    "32": "siamese",
+    "33": "sphynx",
+    "34": "staffordshire_bull_terrier",
+    "35": "wheaten_terrier",
+    "36": "yorkshire_terrier"
+  },
+  "label2id": {
+    "abyssinian": 0,
+    "american_bulldog": 1,
+    "american_pit_bull_terrier": 2,
+    "basset_hound": 3,
+    "beagle": 4,
+    "bengal": 5,
+    "birman": 6,
+    "bombay": 7,
+    "boxer": 8,
+    "british_shorthair": 9,
+    "chihuahua": 10,
+    "egyptian_mau": 11,
+    "english_cocker_spaniel": 12,
+    "english_setter": 13,
+    "german_shorthaired": 14,
+    "great_pyrenees": 15,
+    "havanese": 16,
+    "japanese_chin": 17,
+    "keeshond": 18,
+    "leonberger": 19,
+    "maine_coon": 20,
+    "miniature_pinscher": 21,
+    "newfoundland": 22,
+    "persian": 23,
+    "pomeranian": 24,
+    "pug": 25,
+    "ragdoll": 26,
+    "russian_blue": 27,
+    "saint_bernard": 28,
+    "samoyed": 29,
+    "scottish_terrier": 30,
+    "shiba_inu": 31,
+    "siamese": 32,
+    "sphynx": 33,
+    "staffordshire_bull_terrier": 34,
+    "wheaten_terrier": 35,
+    "yorkshire_terrier": 36
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/README.md b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..01efd57364856ec6658ca27adaf4c1f4fdbe1b65
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford-iiit-pet.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: oxford-iiit-pet
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford-iiit-pet:
+    _target_: datasets.load_dataset
+    path: timm/oxford-iiit-pet
+    split: train
+type: transformers
+val_datasets:
+  oxford-iiit-pet:
+    _target_: datasets.load_dataset
+    path: timm/oxford-iiit-pet
+    split: test
+```
+
diff --git a/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/config.json b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..fd54d9408eb0bfa96cb8fb062f40297ff8e043a3
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,117 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "abyssinian",
+    "1": "american_bulldog",
+    "2": "american_pit_bull_terrier",
+    "3": "basset_hound",
+    "4": "beagle",
+    "5": "bengal",
+    "6": "birman",
+    "7": "bombay",
+    "8": "boxer",
+    "9": "british_shorthair",
+    "10": "chihuahua",
+    "11": "egyptian_mau",
+    "12": "english_cocker_spaniel",
+    "13": "english_setter",
+    "14": "german_shorthaired",
+    "15": "great_pyrenees",
+    "16": "havanese",
+    "17": "japanese_chin",
+    "18": "keeshond",
+    "19": "leonberger",
+    "20": "maine_coon",
+    "21": "miniature_pinscher",
+    "22": "newfoundland",
+    "23": "persian",
+    "24": "pomeranian",
+    "25": "pug",
+    "26": "ragdoll",
+    "27": "russian_blue",
+    "28": "saint_bernard",
+    "29": "samoyed",
+    "30": "scottish_terrier",
+    "31": "shiba_inu",
+    "32": "siamese",
+    "33": "sphynx",
+    "34": "staffordshire_bull_terrier",
+    "35": "wheaten_terrier",
+    "36": "yorkshire_terrier"
+  },
+  "label2id": {
+    "abyssinian": 0,
+    "american_bulldog": 1,
+    "american_pit_bull_terrier": 2,
+    "basset_hound": 3,
+    "beagle": 4,
+    "bengal": 5,
+    "birman": 6,
+    "bombay": 7,
+    "boxer": 8,
+    "british_shorthair": 9,
+    "chihuahua": 10,
+    "egyptian_mau": 11,
+    "english_cocker_spaniel": 12,
+    "english_setter": 13,
+    "german_shorthaired": 14,
+    "great_pyrenees": 15,
+    "havanese": 16,
+    "japanese_chin": 17,
+    "keeshond": 18,
+    "leonberger": 19,
+    "maine_coon": 20,
+    "miniature_pinscher": 21,
+    "newfoundland": 22,
+    "persian": 23,
+    "pomeranian": 24,
+    "pug": 25,
+    "ragdoll": 26,
+    "russian_blue": 27,
+    "saint_bernard": 28,
+    "samoyed": 29,
+    "scottish_terrier": 30,
+    "shiba_inu": 31,
+    "siamese": 32,
+    "sphynx": 33,
+    "staffordshire_bull_terrier": 34,
+    "wheaten_terrier": 35,
+    "yorkshire_terrier": 36
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/README.md b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..01efd57364856ec6658ca27adaf4c1f4fdbe1b65
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford-iiit-pet.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: oxford-iiit-pet
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford-iiit-pet:
+    _target_: datasets.load_dataset
+    path: timm/oxford-iiit-pet
+    split: train
+type: transformers
+val_datasets:
+  oxford-iiit-pet:
+    _target_: datasets.load_dataset
+    path: timm/oxford-iiit-pet
+    split: test
+```
+
diff --git a/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/config.json b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..fd54d9408eb0bfa96cb8fb062f40297ff8e043a3
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,117 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "abyssinian",
+    "1": "american_bulldog",
+    "2": "american_pit_bull_terrier",
+    "3": "basset_hound",
+    "4": "beagle",
+    "5": "bengal",
+    "6": "birman",
+    "7": "bombay",
+    "8": "boxer",
+    "9": "british_shorthair",
+    "10": "chihuahua",
+    "11": "egyptian_mau",
+    "12": "english_cocker_spaniel",
+    "13": "english_setter",
+    "14": "german_shorthaired",
+    "15": "great_pyrenees",
+    "16": "havanese",
+    "17": "japanese_chin",
+    "18": "keeshond",
+    "19": "leonberger",
+    "20": "maine_coon",
+    "21": "miniature_pinscher",
+    "22": "newfoundland",
+    "23": "persian",
+    "24": "pomeranian",
+    "25": "pug",
+    "26": "ragdoll",
+    "27": "russian_blue",
+    "28": "saint_bernard",
+    "29": "samoyed",
+    "30": "scottish_terrier",
+    "31": "shiba_inu",
+    "32": "siamese",
+    "33": "sphynx",
+    "34": "staffordshire_bull_terrier",
+    "35": "wheaten_terrier",
+    "36": "yorkshire_terrier"
+  },
+  "label2id": {
+    "abyssinian": 0,
+    "american_bulldog": 1,
+    "american_pit_bull_terrier": 2,
+    "basset_hound": 3,
+    "beagle": 4,
+    "bengal": 5,
+    "birman": 6,
+    "bombay": 7,
+    "boxer": 8,
+    "british_shorthair": 9,
+    "chihuahua": 10,
+    "egyptian_mau": 11,
+    "english_cocker_spaniel": 12,
+    "english_setter": 13,
+    "german_shorthaired": 14,
+    "great_pyrenees": 15,
+    "havanese": 16,
+    "japanese_chin": 17,
+    "keeshond": 18,
+    "leonberger": 19,
+    "maine_coon": 20,
+    "miniature_pinscher": 21,
+    "newfoundland": 22,
+    "persian": 23,
+    "pomeranian": 24,
+    "pug": 25,
+    "ragdoll": 26,
+    "russian_blue": 27,
+    "saint_bernard": 28,
+    "samoyed": 29,
+    "scottish_terrier": 30,
+    "shiba_inu": 31,
+    "siamese": 32,
+    "sphynx": 33,
+    "staffordshire_bull_terrier": 34,
+    "wheaten_terrier": 35,
+    "yorkshire_terrier": 36
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-oxford-iiit-pet-batch_size_256_lr_0.01_training_data_ratio_0.8-4000/README.md b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.01_training_data_ratio_0.8-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..100afb94797a0a0c05ebec13e027faaa707d5ca4
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.01_training_data_ratio_0.8-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford-iiit-pet.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: oxford-iiit-pet
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford-iiit-pet:
+    _target_: datasets.load_dataset
+    path: timm/oxford-iiit-pet
+    split: train
+type: transformers
+val_datasets:
+  oxford-iiit-pet:
+    _target_: datasets.load_dataset
+    path: timm/oxford-iiit-pet
+    split: test
+```
+
diff --git a/resnet18-oxford-iiit-pet-batch_size_256_lr_0.01_training_data_ratio_0.8-4000/config.json b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.01_training_data_ratio_0.8-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..fd54d9408eb0bfa96cb8fb062f40297ff8e043a3
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.01_training_data_ratio_0.8-4000/config.json
@@ -0,0 +1,117 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "abyssinian",
+    "1": "american_bulldog",
+    "2": "american_pit_bull_terrier",
+    "3": "basset_hound",
+    "4": "beagle",
+    "5": "bengal",
+    "6": "birman",
+    "7": "bombay",
+    "8": "boxer",
+    "9": "british_shorthair",
+    "10": "chihuahua",
+    "11": "egyptian_mau",
+    "12": "english_cocker_spaniel",
+    "13": "english_setter",
+    "14": "german_shorthaired",
+    "15": "great_pyrenees",
+    "16": "havanese",
+    "17": "japanese_chin",
+    "18": "keeshond",
+    "19": "leonberger",
+    "20": "maine_coon",
+    "21": "miniature_pinscher",
+    "22": "newfoundland",
+    "23": "persian",
+    "24": "pomeranian",
+    "25": "pug",
+    "26": "ragdoll",
+    "27": "russian_blue",
+    "28": "saint_bernard",
+    "29": "samoyed",
+    "30": "scottish_terrier",
+    "31": "shiba_inu",
+    "32": "siamese",
+    "33": "sphynx",
+    "34": "staffordshire_bull_terrier",
+    "35": "wheaten_terrier",
+    "36": "yorkshire_terrier"
+  },
+  "label2id": {
+    "abyssinian": 0,
+    "american_bulldog": 1,
+    "american_pit_bull_terrier": 2,
+    "basset_hound": 3,
+    "beagle": 4,
+    "bengal": 5,
+    "birman": 6,
+    "bombay": 7,
+    "boxer": 8,
+    "british_shorthair": 9,
+    "chihuahua": 10,
+    "egyptian_mau": 11,
+    "english_cocker_spaniel": 12,
+    "english_setter": 13,
+    "german_shorthaired": 14,
+    "great_pyrenees": 15,
+    "havanese": 16,
+    "japanese_chin": 17,
+    "keeshond": 18,
+    "leonberger": 19,
+    "maine_coon": 20,
+    "miniature_pinscher": 21,
+    "newfoundland": 22,
+    "persian": 23,
+    "pomeranian": 24,
+    "pug": 25,
+    "ragdoll": 26,
+    "russian_blue": 27,
+    "saint_bernard": 28,
+    "samoyed": 29,
+    "scottish_terrier": 30,
+    "shiba_inu": 31,
+    "siamese": 32,
+    "sphynx": 33,
+    "staffordshire_bull_terrier": 34,
+    "wheaten_terrier": 35,
+    "yorkshire_terrier": 36
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-oxford-iiit-pet-batch_size_256_lr_0.01_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.01_training_data_ratio_0.8-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.01_training_data_ratio_0.8-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/README.md b/resnet18-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..d7e41f192fb01053fabe579de8499db7cab7e350
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford-iiit-pet.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: oxford-iiit-pet
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford-iiit-pet:
+    _target_: datasets.load_dataset
+    path: timm/oxford-iiit-pet
+    split: train
+type: transformers
+val_datasets:
+  oxford-iiit-pet:
+    _target_: datasets.load_dataset
+    path: timm/oxford-iiit-pet
+    split: test
+```
+
diff --git a/resnet18-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/config.json b/resnet18-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..fd54d9408eb0bfa96cb8fb062f40297ff8e043a3
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,117 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "abyssinian",
+    "1": "american_bulldog",
+    "2": "american_pit_bull_terrier",
+    "3": "basset_hound",
+    "4": "beagle",
+    "5": "bengal",
+    "6": "birman",
+    "7": "bombay",
+    "8": "boxer",
+    "9": "british_shorthair",
+    "10": "chihuahua",
+    "11": "egyptian_mau",
+    "12": "english_cocker_spaniel",
+    "13": "english_setter",
+    "14": "german_shorthaired",
+    "15": "great_pyrenees",
+    "16": "havanese",
+    "17": "japanese_chin",
+    "18": "keeshond",
+    "19": "leonberger",
+    "20": "maine_coon",
+    "21": "miniature_pinscher",
+    "22": "newfoundland",
+    "23": "persian",
+    "24": "pomeranian",
+    "25": "pug",
+    "26": "ragdoll",
+    "27": "russian_blue",
+    "28": "saint_bernard",
+    "29": "samoyed",
+    "30": "scottish_terrier",
+    "31": "shiba_inu",
+    "32": "siamese",
+    "33": "sphynx",
+    "34": "staffordshire_bull_terrier",
+    "35": "wheaten_terrier",
+    "36": "yorkshire_terrier"
+  },
+  "label2id": {
+    "abyssinian": 0,
+    "american_bulldog": 1,
+    "american_pit_bull_terrier": 2,
+    "basset_hound": 3,
+    "beagle": 4,
+    "bengal": 5,
+    "birman": 6,
+    "bombay": 7,
+    "boxer": 8,
+    "british_shorthair": 9,
+    "chihuahua": 10,
+    "egyptian_mau": 11,
+    "english_cocker_spaniel": 12,
+    "english_setter": 13,
+    "german_shorthaired": 14,
+    "great_pyrenees": 15,
+    "havanese": 16,
+    "japanese_chin": 17,
+    "keeshond": 18,
+    "leonberger": 19,
+    "maine_coon": 20,
+    "miniature_pinscher": 21,
+    "newfoundland": 22,
+    "persian": 23,
+    "pomeranian": 24,
+    "pug": 25,
+    "ragdoll": 26,
+    "russian_blue": 27,
+    "saint_bernard": 28,
+    "samoyed": 29,
+    "scottish_terrier": 30,
+    "shiba_inu": 31,
+    "siamese": 32,
+    "sphynx": 33,
+    "staffordshire_bull_terrier": 34,
+    "wheaten_terrier": 35,
+    "yorkshire_terrier": 36
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet18-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/README.md b/resnet18-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..d7e41f192fb01053fabe579de8499db7cab7e350
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford-iiit-pet.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: oxford-iiit-pet
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford-iiit-pet:
+    _target_: datasets.load_dataset
+    path: timm/oxford-iiit-pet
+    split: train
+type: transformers
+val_datasets:
+  oxford-iiit-pet:
+    _target_: datasets.load_dataset
+    path: timm/oxford-iiit-pet
+    split: test
+```
+
diff --git a/resnet18-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/config.json b/resnet18-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..fd54d9408eb0bfa96cb8fb062f40297ff8e043a3
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,117 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "abyssinian",
+    "1": "american_bulldog",
+    "2": "american_pit_bull_terrier",
+    "3": "basset_hound",
+    "4": "beagle",
+    "5": "bengal",
+    "6": "birman",
+    "7": "bombay",
+    "8": "boxer",
+    "9": "british_shorthair",
+    "10": "chihuahua",
+    "11": "egyptian_mau",
+    "12": "english_cocker_spaniel",
+    "13": "english_setter",
+    "14": "german_shorthaired",
+    "15": "great_pyrenees",
+    "16": "havanese",
+    "17": "japanese_chin",
+    "18": "keeshond",
+    "19": "leonberger",
+    "20": "maine_coon",
+    "21": "miniature_pinscher",
+    "22": "newfoundland",
+    "23": "persian",
+    "24": "pomeranian",
+    "25": "pug",
+    "26": "ragdoll",
+    "27": "russian_blue",
+    "28": "saint_bernard",
+    "29": "samoyed",
+    "30": "scottish_terrier",
+    "31": "shiba_inu",
+    "32": "siamese",
+    "33": "sphynx",
+    "34": "staffordshire_bull_terrier",
+    "35": "wheaten_terrier",
+    "36": "yorkshire_terrier"
+  },
+  "label2id": {
+    "abyssinian": 0,
+    "american_bulldog": 1,
+    "american_pit_bull_terrier": 2,
+    "basset_hound": 3,
+    "beagle": 4,
+    "bengal": 5,
+    "birman": 6,
+    "bombay": 7,
+    "boxer": 8,
+    "british_shorthair": 9,
+    "chihuahua": 10,
+    "egyptian_mau": 11,
+    "english_cocker_spaniel": 12,
+    "english_setter": 13,
+    "german_shorthaired": 14,
+    "great_pyrenees": 15,
+    "havanese": 16,
+    "japanese_chin": 17,
+    "keeshond": 18,
+    "leonberger": 19,
+    "maine_coon": 20,
+    "miniature_pinscher": 21,
+    "newfoundland": 22,
+    "persian": 23,
+    "pomeranian": 24,
+    "pug": 25,
+    "ragdoll": 26,
+    "russian_blue": 27,
+    "saint_bernard": 28,
+    "samoyed": 29,
+    "scottish_terrier": 30,
+    "shiba_inu": 31,
+    "siamese": 32,
+    "sphynx": 33,
+    "staffordshire_bull_terrier": 34,
+    "wheaten_terrier": 35,
+    "yorkshire_terrier": 36
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet18-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-oxford-iiit-pet-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/README.md b/resnet18-oxford-iiit-pet-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..c6d3b778f0de804cf4d927040df8c97011a203b1
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford-iiit-pet.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: oxford-iiit-pet
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford-iiit-pet:
+    _target_: datasets.load_dataset
+    path: timm/oxford-iiit-pet
+    split: train
+type: transformers
+val_datasets:
+  oxford-iiit-pet:
+    _target_: datasets.load_dataset
+    path: timm/oxford-iiit-pet
+    split: test
+```
+
diff --git a/resnet18-oxford-iiit-pet-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/config.json b/resnet18-oxford-iiit-pet-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..fd54d9408eb0bfa96cb8fb062f40297ff8e043a3
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,117 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "abyssinian",
+    "1": "american_bulldog",
+    "2": "american_pit_bull_terrier",
+    "3": "basset_hound",
+    "4": "beagle",
+    "5": "bengal",
+    "6": "birman",
+    "7": "bombay",
+    "8": "boxer",
+    "9": "british_shorthair",
+    "10": "chihuahua",
+    "11": "egyptian_mau",
+    "12": "english_cocker_spaniel",
+    "13": "english_setter",
+    "14": "german_shorthaired",
+    "15": "great_pyrenees",
+    "16": "havanese",
+    "17": "japanese_chin",
+    "18": "keeshond",
+    "19": "leonberger",
+    "20": "maine_coon",
+    "21": "miniature_pinscher",
+    "22": "newfoundland",
+    "23": "persian",
+    "24": "pomeranian",
+    "25": "pug",
+    "26": "ragdoll",
+    "27": "russian_blue",
+    "28": "saint_bernard",
+    "29": "samoyed",
+    "30": "scottish_terrier",
+    "31": "shiba_inu",
+    "32": "siamese",
+    "33": "sphynx",
+    "34": "staffordshire_bull_terrier",
+    "35": "wheaten_terrier",
+    "36": "yorkshire_terrier"
+  },
+  "label2id": {
+    "abyssinian": 0,
+    "american_bulldog": 1,
+    "american_pit_bull_terrier": 2,
+    "basset_hound": 3,
+    "beagle": 4,
+    "bengal": 5,
+    "birman": 6,
+    "bombay": 7,
+    "boxer": 8,
+    "british_shorthair": 9,
+    "chihuahua": 10,
+    "egyptian_mau": 11,
+    "english_cocker_spaniel": 12,
+    "english_setter": 13,
+    "german_shorthaired": 14,
+    "great_pyrenees": 15,
+    "havanese": 16,
+    "japanese_chin": 17,
+    "keeshond": 18,
+    "leonberger": 19,
+    "maine_coon": 20,
+    "miniature_pinscher": 21,
+    "newfoundland": 22,
+    "persian": 23,
+    "pomeranian": 24,
+    "pug": 25,
+    "ragdoll": 26,
+    "russian_blue": 27,
+    "saint_bernard": 28,
+    "samoyed": 29,
+    "scottish_terrier": 30,
+    "shiba_inu": 31,
+    "siamese": 32,
+    "sphynx": 33,
+    "staffordshire_bull_terrier": 34,
+    "wheaten_terrier": 35,
+    "yorkshire_terrier": 36
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-oxford-iiit-pet-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet18-oxford-iiit-pet-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-oxford-iiit-pet-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-oxford_flowers102-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/README.md b/resnet18-oxford_flowers102-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..6b491bd4e02afdfafbad3b576d6b94a93ba9f76f
--- /dev/null
+++ b/resnet18-oxford_flowers102-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford_flowers102.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: oxford_flowers102
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: train
+type: transformers
+val_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: test
+```
+
diff --git a/resnet18-oxford_flowers102-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/config.json b/resnet18-oxford_flowers102-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..f938618d830ad3512a63af4ea0f8ca5e6b26a242
--- /dev/null
+++ b/resnet18-oxford_flowers102-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,247 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "pink primrose",
+    "1": "hard-leaved pocket orchid",
+    "2": "canterbury bells",
+    "3": "sweet pea",
+    "4": "english marigold",
+    "5": "tiger lily",
+    "6": "moon orchid",
+    "7": "bird of paradise",
+    "8": "monkshood",
+    "9": "globe thistle",
+    "10": "snapdragon",
+    "11": "colt's foot",
+    "12": "king protea",
+    "13": "spear thistle",
+    "14": "yellow iris",
+    "15": "globe-flower",
+    "16": "purple coneflower",
+    "17": "peruvian lily",
+    "18": "balloon flower",
+    "19": "giant white arum lily",
+    "20": "fire lily",
+    "21": "pincushion flower",
+    "22": "fritillary",
+    "23": "red ginger",
+    "24": "grape hyacinth",
+    "25": "corn poppy",
+    "26": "prince of wales feathers",
+    "27": "stemless gentian",
+    "28": "artichoke",
+    "29": "sweet william",
+    "30": "carnation",
+    "31": "garden phlox",
+    "32": "love in the mist",
+    "33": "mexican aster",
+    "34": "alpine sea holly",
+    "35": "ruby-lipped cattleya",
+    "36": "cape flower",
+    "37": "great masterwort",
+    "38": "siam tulip",
+    "39": "lenten rose",
+    "40": "barbeton daisy",
+    "41": "daffodil",
+    "42": "sword lily",
+    "43": "poinsettia",
+    "44": "bolero deep blue",
+    "45": "wallflower",
+    "46": "marigold",
+    "47": "buttercup",
+    "48": "oxeye daisy",
+    "49": "common dandelion",
+    "50": "petunia",
+    "51": "wild pansy",
+    "52": "primula",
+    "53": "sunflower",
+    "54": "pelargonium",
+    "55": "bishop of llandaff",
+    "56": "gaura",
+    "57": "geranium",
+    "58": "orange dahlia",
+    "59": "pink-yellow dahlia?",
+    "60": "cautleya spicata",
+    "61": "japanese anemone",
+    "62": "black-eyed susan",
+    "63": "silverbush",
+    "64": "californian poppy",
+    "65": "osteospermum",
+    "66": "spring crocus",
+    "67": "bearded iris",
+    "68": "windflower",
+    "69": "tree poppy",
+    "70": "gazania",
+    "71": "azalea",
+    "72": "water lily",
+    "73": "rose",
+    "74": "thorn apple",
+    "75": "morning glory",
+    "76": "passion flower",
+    "77": "lotus",
+    "78": "toad lily",
+    "79": "anthurium",
+    "80": "frangipani",
+    "81": "clematis",
+    "82": "hibiscus",
+    "83": "columbine",
+    "84": "desert-rose",
+    "85": "tree mallow",
+    "86": "magnolia",
+    "87": "cyclamen",
+    "88": "watercress",
+    "89": "canna lily",
+    "90": "hippeastrum",
+    "91": "bee balm",
+    "92": "ball moss",
+    "93": "foxglove",
+    "94": "bougainvillea",
+    "95": "camellia",
+    "96": "mallow",
+    "97": "mexican petunia",
+    "98": "bromelia",
+    "99": "blanket flower",
+    "100": "trumpet creeper",
+    "101": "blackberry lily"
+  },
+  "label2id": {
+    "alpine sea holly": 34,
+    "anthurium": 79,
+    "artichoke": 28,
+    "azalea": 71,
+    "ball moss": 92,
+    "balloon flower": 18,
+    "barbeton daisy": 40,
+    "bearded iris": 67,
+    "bee balm": 91,
+    "bird of paradise": 7,
+    "bishop of llandaff": 55,
+    "black-eyed susan": 62,
+    "blackberry lily": 101,
+    "blanket flower": 99,
+    "bolero deep blue": 44,
+    "bougainvillea": 94,
+    "bromelia": 98,
+    "buttercup": 47,
+    "californian poppy": 64,
+    "camellia": 95,
+    "canna lily": 89,
+    "canterbury bells": 2,
+    "cape flower": 36,
+    "carnation": 30,
+    "cautleya spicata": 60,
+    "clematis": 81,
+    "colt's foot": 11,
+    "columbine": 83,
+    "common dandelion": 49,
+    "corn poppy": 25,
+    "cyclamen": 87,
+    "daffodil": 41,
+    "desert-rose": 84,
+    "english marigold": 4,
+    "fire lily": 20,
+    "foxglove": 93,
+    "frangipani": 80,
+    "fritillary": 22,
+    "garden phlox": 31,
+    "gaura": 56,
+    "gazania": 70,
+    "geranium": 57,
+    "giant white arum lily": 19,
+    "globe thistle": 9,
+    "globe-flower": 15,
+    "grape hyacinth": 24,
+    "great masterwort": 37,
+    "hard-leaved pocket orchid": 1,
+    "hibiscus": 82,
+    "hippeastrum": 90,
+    "japanese anemone": 61,
+    "king protea": 12,
+    "lenten rose": 39,
+    "lotus": 77,
+    "love in the mist": 32,
+    "magnolia": 86,
+    "mallow": 96,
+    "marigold": 46,
+    "mexican aster": 33,
+    "mexican petunia": 97,
+    "monkshood": 8,
+    "moon orchid": 6,
+    "morning glory": 75,
+    "orange dahlia": 58,
+    "osteospermum": 65,
+    "oxeye daisy": 48,
+    "passion flower": 76,
+    "pelargonium": 54,
+    "peruvian lily": 17,
+    "petunia": 50,
+    "pincushion flower": 21,
+    "pink primrose": 0,
+    "pink-yellow dahlia?": 59,
+    "poinsettia": 43,
+    "primula": 52,
+    "prince of wales feathers": 26,
+    "purple coneflower": 16,
+    "red ginger": 23,
+    "rose": 73,
+    "ruby-lipped cattleya": 35,
+    "siam tulip": 38,
+    "silverbush": 63,
+    "snapdragon": 10,
+    "spear thistle": 13,
+    "spring crocus": 66,
+    "stemless gentian": 27,
+    "sunflower": 53,
+    "sweet pea": 3,
+    "sweet william": 29,
+    "sword lily": 42,
+    "thorn apple": 74,
+    "tiger lily": 5,
+    "toad lily": 78,
+    "tree mallow": 85,
+    "tree poppy": 69,
+    "trumpet creeper": 100,
+    "wallflower": 45,
+    "water lily": 72,
+    "watercress": 88,
+    "wild pansy": 51,
+    "windflower": 68,
+    "yellow iris": 14
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-oxford_flowers102-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet18-oxford_flowers102-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-oxford_flowers102-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/README.md b/resnet18-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..08d9656a911c12592b8b77dfe6fe0d0c57bf6c9b
--- /dev/null
+++ b/resnet18-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford_flowers102.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: oxford_flowers102
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: train
+type: transformers
+val_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: test
+```
+
diff --git a/resnet18-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/config.json b/resnet18-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..f938618d830ad3512a63af4ea0f8ca5e6b26a242
--- /dev/null
+++ b/resnet18-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,247 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "pink primrose",
+    "1": "hard-leaved pocket orchid",
+    "2": "canterbury bells",
+    "3": "sweet pea",
+    "4": "english marigold",
+    "5": "tiger lily",
+    "6": "moon orchid",
+    "7": "bird of paradise",
+    "8": "monkshood",
+    "9": "globe thistle",
+    "10": "snapdragon",
+    "11": "colt's foot",
+    "12": "king protea",
+    "13": "spear thistle",
+    "14": "yellow iris",
+    "15": "globe-flower",
+    "16": "purple coneflower",
+    "17": "peruvian lily",
+    "18": "balloon flower",
+    "19": "giant white arum lily",
+    "20": "fire lily",
+    "21": "pincushion flower",
+    "22": "fritillary",
+    "23": "red ginger",
+    "24": "grape hyacinth",
+    "25": "corn poppy",
+    "26": "prince of wales feathers",
+    "27": "stemless gentian",
+    "28": "artichoke",
+    "29": "sweet william",
+    "30": "carnation",
+    "31": "garden phlox",
+    "32": "love in the mist",
+    "33": "mexican aster",
+    "34": "alpine sea holly",
+    "35": "ruby-lipped cattleya",
+    "36": "cape flower",
+    "37": "great masterwort",
+    "38": "siam tulip",
+    "39": "lenten rose",
+    "40": "barbeton daisy",
+    "41": "daffodil",
+    "42": "sword lily",
+    "43": "poinsettia",
+    "44": "bolero deep blue",
+    "45": "wallflower",
+    "46": "marigold",
+    "47": "buttercup",
+    "48": "oxeye daisy",
+    "49": "common dandelion",
+    "50": "petunia",
+    "51": "wild pansy",
+    "52": "primula",
+    "53": "sunflower",
+    "54": "pelargonium",
+    "55": "bishop of llandaff",
+    "56": "gaura",
+    "57": "geranium",
+    "58": "orange dahlia",
+    "59": "pink-yellow dahlia?",
+    "60": "cautleya spicata",
+    "61": "japanese anemone",
+    "62": "black-eyed susan",
+    "63": "silverbush",
+    "64": "californian poppy",
+    "65": "osteospermum",
+    "66": "spring crocus",
+    "67": "bearded iris",
+    "68": "windflower",
+    "69": "tree poppy",
+    "70": "gazania",
+    "71": "azalea",
+    "72": "water lily",
+    "73": "rose",
+    "74": "thorn apple",
+    "75": "morning glory",
+    "76": "passion flower",
+    "77": "lotus",
+    "78": "toad lily",
+    "79": "anthurium",
+    "80": "frangipani",
+    "81": "clematis",
+    "82": "hibiscus",
+    "83": "columbine",
+    "84": "desert-rose",
+    "85": "tree mallow",
+    "86": "magnolia",
+    "87": "cyclamen",
+    "88": "watercress",
+    "89": "canna lily",
+    "90": "hippeastrum",
+    "91": "bee balm",
+    "92": "ball moss",
+    "93": "foxglove",
+    "94": "bougainvillea",
+    "95": "camellia",
+    "96": "mallow",
+    "97": "mexican petunia",
+    "98": "bromelia",
+    "99": "blanket flower",
+    "100": "trumpet creeper",
+    "101": "blackberry lily"
+  },
+  "label2id": {
+    "alpine sea holly": 34,
+    "anthurium": 79,
+    "artichoke": 28,
+    "azalea": 71,
+    "ball moss": 92,
+    "balloon flower": 18,
+    "barbeton daisy": 40,
+    "bearded iris": 67,
+    "bee balm": 91,
+    "bird of paradise": 7,
+    "bishop of llandaff": 55,
+    "black-eyed susan": 62,
+    "blackberry lily": 101,
+    "blanket flower": 99,
+    "bolero deep blue": 44,
+    "bougainvillea": 94,
+    "bromelia": 98,
+    "buttercup": 47,
+    "californian poppy": 64,
+    "camellia": 95,
+    "canna lily": 89,
+    "canterbury bells": 2,
+    "cape flower": 36,
+    "carnation": 30,
+    "cautleya spicata": 60,
+    "clematis": 81,
+    "colt's foot": 11,
+    "columbine": 83,
+    "common dandelion": 49,
+    "corn poppy": 25,
+    "cyclamen": 87,
+    "daffodil": 41,
+    "desert-rose": 84,
+    "english marigold": 4,
+    "fire lily": 20,
+    "foxglove": 93,
+    "frangipani": 80,
+    "fritillary": 22,
+    "garden phlox": 31,
+    "gaura": 56,
+    "gazania": 70,
+    "geranium": 57,
+    "giant white arum lily": 19,
+    "globe thistle": 9,
+    "globe-flower": 15,
+    "grape hyacinth": 24,
+    "great masterwort": 37,
+    "hard-leaved pocket orchid": 1,
+    "hibiscus": 82,
+    "hippeastrum": 90,
+    "japanese anemone": 61,
+    "king protea": 12,
+    "lenten rose": 39,
+    "lotus": 77,
+    "love in the mist": 32,
+    "magnolia": 86,
+    "mallow": 96,
+    "marigold": 46,
+    "mexican aster": 33,
+    "mexican petunia": 97,
+    "monkshood": 8,
+    "moon orchid": 6,
+    "morning glory": 75,
+    "orange dahlia": 58,
+    "osteospermum": 65,
+    "oxeye daisy": 48,
+    "passion flower": 76,
+    "pelargonium": 54,
+    "peruvian lily": 17,
+    "petunia": 50,
+    "pincushion flower": 21,
+    "pink primrose": 0,
+    "pink-yellow dahlia?": 59,
+    "poinsettia": 43,
+    "primula": 52,
+    "prince of wales feathers": 26,
+    "purple coneflower": 16,
+    "red ginger": 23,
+    "rose": 73,
+    "ruby-lipped cattleya": 35,
+    "siam tulip": 38,
+    "silverbush": 63,
+    "snapdragon": 10,
+    "spear thistle": 13,
+    "spring crocus": 66,
+    "stemless gentian": 27,
+    "sunflower": 53,
+    "sweet pea": 3,
+    "sweet william": 29,
+    "sword lily": 42,
+    "thorn apple": 74,
+    "tiger lily": 5,
+    "toad lily": 78,
+    "tree mallow": 85,
+    "tree poppy": 69,
+    "trumpet creeper": 100,
+    "wallflower": 45,
+    "water lily": 72,
+    "watercress": 88,
+    "wild pansy": 51,
+    "windflower": 68,
+    "yellow iris": 14
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet18-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/README.md b/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..066540d46f0325edef51321671df853a4d31a2c0
--- /dev/null
+++ b/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford_flowers102.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: oxford_flowers102
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: train
+type: transformers
+val_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: test
+```
+
diff --git a/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/config.json b/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..f938618d830ad3512a63af4ea0f8ca5e6b26a242
--- /dev/null
+++ b/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,247 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "pink primrose",
+    "1": "hard-leaved pocket orchid",
+    "2": "canterbury bells",
+    "3": "sweet pea",
+    "4": "english marigold",
+    "5": "tiger lily",
+    "6": "moon orchid",
+    "7": "bird of paradise",
+    "8": "monkshood",
+    "9": "globe thistle",
+    "10": "snapdragon",
+    "11": "colt's foot",
+    "12": "king protea",
+    "13": "spear thistle",
+    "14": "yellow iris",
+    "15": "globe-flower",
+    "16": "purple coneflower",
+    "17": "peruvian lily",
+    "18": "balloon flower",
+    "19": "giant white arum lily",
+    "20": "fire lily",
+    "21": "pincushion flower",
+    "22": "fritillary",
+    "23": "red ginger",
+    "24": "grape hyacinth",
+    "25": "corn poppy",
+    "26": "prince of wales feathers",
+    "27": "stemless gentian",
+    "28": "artichoke",
+    "29": "sweet william",
+    "30": "carnation",
+    "31": "garden phlox",
+    "32": "love in the mist",
+    "33": "mexican aster",
+    "34": "alpine sea holly",
+    "35": "ruby-lipped cattleya",
+    "36": "cape flower",
+    "37": "great masterwort",
+    "38": "siam tulip",
+    "39": "lenten rose",
+    "40": "barbeton daisy",
+    "41": "daffodil",
+    "42": "sword lily",
+    "43": "poinsettia",
+    "44": "bolero deep blue",
+    "45": "wallflower",
+    "46": "marigold",
+    "47": "buttercup",
+    "48": "oxeye daisy",
+    "49": "common dandelion",
+    "50": "petunia",
+    "51": "wild pansy",
+    "52": "primula",
+    "53": "sunflower",
+    "54": "pelargonium",
+    "55": "bishop of llandaff",
+    "56": "gaura",
+    "57": "geranium",
+    "58": "orange dahlia",
+    "59": "pink-yellow dahlia?",
+    "60": "cautleya spicata",
+    "61": "japanese anemone",
+    "62": "black-eyed susan",
+    "63": "silverbush",
+    "64": "californian poppy",
+    "65": "osteospermum",
+    "66": "spring crocus",
+    "67": "bearded iris",
+    "68": "windflower",
+    "69": "tree poppy",
+    "70": "gazania",
+    "71": "azalea",
+    "72": "water lily",
+    "73": "rose",
+    "74": "thorn apple",
+    "75": "morning glory",
+    "76": "passion flower",
+    "77": "lotus",
+    "78": "toad lily",
+    "79": "anthurium",
+    "80": "frangipani",
+    "81": "clematis",
+    "82": "hibiscus",
+    "83": "columbine",
+    "84": "desert-rose",
+    "85": "tree mallow",
+    "86": "magnolia",
+    "87": "cyclamen",
+    "88": "watercress",
+    "89": "canna lily",
+    "90": "hippeastrum",
+    "91": "bee balm",
+    "92": "ball moss",
+    "93": "foxglove",
+    "94": "bougainvillea",
+    "95": "camellia",
+    "96": "mallow",
+    "97": "mexican petunia",
+    "98": "bromelia",
+    "99": "blanket flower",
+    "100": "trumpet creeper",
+    "101": "blackberry lily"
+  },
+  "label2id": {
+    "alpine sea holly": 34,
+    "anthurium": 79,
+    "artichoke": 28,
+    "azalea": 71,
+    "ball moss": 92,
+    "balloon flower": 18,
+    "barbeton daisy": 40,
+    "bearded iris": 67,
+    "bee balm": 91,
+    "bird of paradise": 7,
+    "bishop of llandaff": 55,
+    "black-eyed susan": 62,
+    "blackberry lily": 101,
+    "blanket flower": 99,
+    "bolero deep blue": 44,
+    "bougainvillea": 94,
+    "bromelia": 98,
+    "buttercup": 47,
+    "californian poppy": 64,
+    "camellia": 95,
+    "canna lily": 89,
+    "canterbury bells": 2,
+    "cape flower": 36,
+    "carnation": 30,
+    "cautleya spicata": 60,
+    "clematis": 81,
+    "colt's foot": 11,
+    "columbine": 83,
+    "common dandelion": 49,
+    "corn poppy": 25,
+    "cyclamen": 87,
+    "daffodil": 41,
+    "desert-rose": 84,
+    "english marigold": 4,
+    "fire lily": 20,
+    "foxglove": 93,
+    "frangipani": 80,
+    "fritillary": 22,
+    "garden phlox": 31,
+    "gaura": 56,
+    "gazania": 70,
+    "geranium": 57,
+    "giant white arum lily": 19,
+    "globe thistle": 9,
+    "globe-flower": 15,
+    "grape hyacinth": 24,
+    "great masterwort": 37,
+    "hard-leaved pocket orchid": 1,
+    "hibiscus": 82,
+    "hippeastrum": 90,
+    "japanese anemone": 61,
+    "king protea": 12,
+    "lenten rose": 39,
+    "lotus": 77,
+    "love in the mist": 32,
+    "magnolia": 86,
+    "mallow": 96,
+    "marigold": 46,
+    "mexican aster": 33,
+    "mexican petunia": 97,
+    "monkshood": 8,
+    "moon orchid": 6,
+    "morning glory": 75,
+    "orange dahlia": 58,
+    "osteospermum": 65,
+    "oxeye daisy": 48,
+    "passion flower": 76,
+    "pelargonium": 54,
+    "peruvian lily": 17,
+    "petunia": 50,
+    "pincushion flower": 21,
+    "pink primrose": 0,
+    "pink-yellow dahlia?": 59,
+    "poinsettia": 43,
+    "primula": 52,
+    "prince of wales feathers": 26,
+    "purple coneflower": 16,
+    "red ginger": 23,
+    "rose": 73,
+    "ruby-lipped cattleya": 35,
+    "siam tulip": 38,
+    "silverbush": 63,
+    "snapdragon": 10,
+    "spear thistle": 13,
+    "spring crocus": 66,
+    "stemless gentian": 27,
+    "sunflower": 53,
+    "sweet pea": 3,
+    "sweet william": 29,
+    "sword lily": 42,
+    "thorn apple": 74,
+    "tiger lily": 5,
+    "toad lily": 78,
+    "tree mallow": 85,
+    "tree poppy": 69,
+    "trumpet creeper": 100,
+    "wallflower": 45,
+    "water lily": 72,
+    "watercress": 88,
+    "wild pansy": 51,
+    "windflower": 68,
+    "yellow iris": 14
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/README.md b/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..066540d46f0325edef51321671df853a4d31a2c0
--- /dev/null
+++ b/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford_flowers102.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: oxford_flowers102
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: train
+type: transformers
+val_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: test
+```
+
diff --git a/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/config.json b/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..f938618d830ad3512a63af4ea0f8ca5e6b26a242
--- /dev/null
+++ b/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/config.json
@@ -0,0 +1,247 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "pink primrose",
+    "1": "hard-leaved pocket orchid",
+    "2": "canterbury bells",
+    "3": "sweet pea",
+    "4": "english marigold",
+    "5": "tiger lily",
+    "6": "moon orchid",
+    "7": "bird of paradise",
+    "8": "monkshood",
+    "9": "globe thistle",
+    "10": "snapdragon",
+    "11": "colt's foot",
+    "12": "king protea",
+    "13": "spear thistle",
+    "14": "yellow iris",
+    "15": "globe-flower",
+    "16": "purple coneflower",
+    "17": "peruvian lily",
+    "18": "balloon flower",
+    "19": "giant white arum lily",
+    "20": "fire lily",
+    "21": "pincushion flower",
+    "22": "fritillary",
+    "23": "red ginger",
+    "24": "grape hyacinth",
+    "25": "corn poppy",
+    "26": "prince of wales feathers",
+    "27": "stemless gentian",
+    "28": "artichoke",
+    "29": "sweet william",
+    "30": "carnation",
+    "31": "garden phlox",
+    "32": "love in the mist",
+    "33": "mexican aster",
+    "34": "alpine sea holly",
+    "35": "ruby-lipped cattleya",
+    "36": "cape flower",
+    "37": "great masterwort",
+    "38": "siam tulip",
+    "39": "lenten rose",
+    "40": "barbeton daisy",
+    "41": "daffodil",
+    "42": "sword lily",
+    "43": "poinsettia",
+    "44": "bolero deep blue",
+    "45": "wallflower",
+    "46": "marigold",
+    "47": "buttercup",
+    "48": "oxeye daisy",
+    "49": "common dandelion",
+    "50": "petunia",
+    "51": "wild pansy",
+    "52": "primula",
+    "53": "sunflower",
+    "54": "pelargonium",
+    "55": "bishop of llandaff",
+    "56": "gaura",
+    "57": "geranium",
+    "58": "orange dahlia",
+    "59": "pink-yellow dahlia?",
+    "60": "cautleya spicata",
+    "61": "japanese anemone",
+    "62": "black-eyed susan",
+    "63": "silverbush",
+    "64": "californian poppy",
+    "65": "osteospermum",
+    "66": "spring crocus",
+    "67": "bearded iris",
+    "68": "windflower",
+    "69": "tree poppy",
+    "70": "gazania",
+    "71": "azalea",
+    "72": "water lily",
+    "73": "rose",
+    "74": "thorn apple",
+    "75": "morning glory",
+    "76": "passion flower",
+    "77": "lotus",
+    "78": "toad lily",
+    "79": "anthurium",
+    "80": "frangipani",
+    "81": "clematis",
+    "82": "hibiscus",
+    "83": "columbine",
+    "84": "desert-rose",
+    "85": "tree mallow",
+    "86": "magnolia",
+    "87": "cyclamen",
+    "88": "watercress",
+    "89": "canna lily",
+    "90": "hippeastrum",
+    "91": "bee balm",
+    "92": "ball moss",
+    "93": "foxglove",
+    "94": "bougainvillea",
+    "95": "camellia",
+    "96": "mallow",
+    "97": "mexican petunia",
+    "98": "bromelia",
+    "99": "blanket flower",
+    "100": "trumpet creeper",
+    "101": "blackberry lily"
+  },
+  "label2id": {
+    "alpine sea holly": 34,
+    "anthurium": 79,
+    "artichoke": 28,
+    "azalea": 71,
+    "ball moss": 92,
+    "balloon flower": 18,
+    "barbeton daisy": 40,
+    "bearded iris": 67,
+    "bee balm": 91,
+    "bird of paradise": 7,
+    "bishop of llandaff": 55,
+    "black-eyed susan": 62,
+    "blackberry lily": 101,
+    "blanket flower": 99,
+    "bolero deep blue": 44,
+    "bougainvillea": 94,
+    "bromelia": 98,
+    "buttercup": 47,
+    "californian poppy": 64,
+    "camellia": 95,
+    "canna lily": 89,
+    "canterbury bells": 2,
+    "cape flower": 36,
+    "carnation": 30,
+    "cautleya spicata": 60,
+    "clematis": 81,
+    "colt's foot": 11,
+    "columbine": 83,
+    "common dandelion": 49,
+    "corn poppy": 25,
+    "cyclamen": 87,
+    "daffodil": 41,
+    "desert-rose": 84,
+    "english marigold": 4,
+    "fire lily": 20,
+    "foxglove": 93,
+    "frangipani": 80,
+    "fritillary": 22,
+    "garden phlox": 31,
+    "gaura": 56,
+    "gazania": 70,
+    "geranium": 57,
+    "giant white arum lily": 19,
+    "globe thistle": 9,
+    "globe-flower": 15,
+    "grape hyacinth": 24,
+    "great masterwort": 37,
+    "hard-leaved pocket orchid": 1,
+    "hibiscus": 82,
+    "hippeastrum": 90,
+    "japanese anemone": 61,
+    "king protea": 12,
+    "lenten rose": 39,
+    "lotus": 77,
+    "love in the mist": 32,
+    "magnolia": 86,
+    "mallow": 96,
+    "marigold": 46,
+    "mexican aster": 33,
+    "mexican petunia": 97,
+    "monkshood": 8,
+    "moon orchid": 6,
+    "morning glory": 75,
+    "orange dahlia": 58,
+    "osteospermum": 65,
+    "oxeye daisy": 48,
+    "passion flower": 76,
+    "pelargonium": 54,
+    "peruvian lily": 17,
+    "petunia": 50,
+    "pincushion flower": 21,
+    "pink primrose": 0,
+    "pink-yellow dahlia?": 59,
+    "poinsettia": 43,
+    "primula": 52,
+    "prince of wales feathers": 26,
+    "purple coneflower": 16,
+    "red ginger": 23,
+    "rose": 73,
+    "ruby-lipped cattleya": 35,
+    "siam tulip": 38,
+    "silverbush": 63,
+    "snapdragon": 10,
+    "spear thistle": 13,
+    "spring crocus": 66,
+    "stemless gentian": 27,
+    "sunflower": 53,
+    "sweet pea": 3,
+    "sweet william": 29,
+    "sword lily": 42,
+    "thorn apple": 74,
+    "tiger lily": 5,
+    "toad lily": 78,
+    "tree mallow": 85,
+    "tree poppy": 69,
+    "trumpet creeper": 100,
+    "wallflower": 45,
+    "water lily": 72,
+    "watercress": 88,
+    "wild pansy": 51,
+    "windflower": 68,
+    "yellow iris": 14
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/README.md b/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..37bb6bccf64fd43837280236bca7305d8d499741
--- /dev/null
+++ b/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford_flowers102.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: oxford_flowers102
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: train
+type: transformers
+val_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: test
+```
+
diff --git a/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/config.json b/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..f938618d830ad3512a63af4ea0f8ca5e6b26a242
--- /dev/null
+++ b/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,247 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "pink primrose",
+    "1": "hard-leaved pocket orchid",
+    "2": "canterbury bells",
+    "3": "sweet pea",
+    "4": "english marigold",
+    "5": "tiger lily",
+    "6": "moon orchid",
+    "7": "bird of paradise",
+    "8": "monkshood",
+    "9": "globe thistle",
+    "10": "snapdragon",
+    "11": "colt's foot",
+    "12": "king protea",
+    "13": "spear thistle",
+    "14": "yellow iris",
+    "15": "globe-flower",
+    "16": "purple coneflower",
+    "17": "peruvian lily",
+    "18": "balloon flower",
+    "19": "giant white arum lily",
+    "20": "fire lily",
+    "21": "pincushion flower",
+    "22": "fritillary",
+    "23": "red ginger",
+    "24": "grape hyacinth",
+    "25": "corn poppy",
+    "26": "prince of wales feathers",
+    "27": "stemless gentian",
+    "28": "artichoke",
+    "29": "sweet william",
+    "30": "carnation",
+    "31": "garden phlox",
+    "32": "love in the mist",
+    "33": "mexican aster",
+    "34": "alpine sea holly",
+    "35": "ruby-lipped cattleya",
+    "36": "cape flower",
+    "37": "great masterwort",
+    "38": "siam tulip",
+    "39": "lenten rose",
+    "40": "barbeton daisy",
+    "41": "daffodil",
+    "42": "sword lily",
+    "43": "poinsettia",
+    "44": "bolero deep blue",
+    "45": "wallflower",
+    "46": "marigold",
+    "47": "buttercup",
+    "48": "oxeye daisy",
+    "49": "common dandelion",
+    "50": "petunia",
+    "51": "wild pansy",
+    "52": "primula",
+    "53": "sunflower",
+    "54": "pelargonium",
+    "55": "bishop of llandaff",
+    "56": "gaura",
+    "57": "geranium",
+    "58": "orange dahlia",
+    "59": "pink-yellow dahlia?",
+    "60": "cautleya spicata",
+    "61": "japanese anemone",
+    "62": "black-eyed susan",
+    "63": "silverbush",
+    "64": "californian poppy",
+    "65": "osteospermum",
+    "66": "spring crocus",
+    "67": "bearded iris",
+    "68": "windflower",
+    "69": "tree poppy",
+    "70": "gazania",
+    "71": "azalea",
+    "72": "water lily",
+    "73": "rose",
+    "74": "thorn apple",
+    "75": "morning glory",
+    "76": "passion flower",
+    "77": "lotus",
+    "78": "toad lily",
+    "79": "anthurium",
+    "80": "frangipani",
+    "81": "clematis",
+    "82": "hibiscus",
+    "83": "columbine",
+    "84": "desert-rose",
+    "85": "tree mallow",
+    "86": "magnolia",
+    "87": "cyclamen",
+    "88": "watercress",
+    "89": "canna lily",
+    "90": "hippeastrum",
+    "91": "bee balm",
+    "92": "ball moss",
+    "93": "foxglove",
+    "94": "bougainvillea",
+    "95": "camellia",
+    "96": "mallow",
+    "97": "mexican petunia",
+    "98": "bromelia",
+    "99": "blanket flower",
+    "100": "trumpet creeper",
+    "101": "blackberry lily"
+  },
+  "label2id": {
+    "alpine sea holly": 34,
+    "anthurium": 79,
+    "artichoke": 28,
+    "azalea": 71,
+    "ball moss": 92,
+    "balloon flower": 18,
+    "barbeton daisy": 40,
+    "bearded iris": 67,
+    "bee balm": 91,
+    "bird of paradise": 7,
+    "bishop of llandaff": 55,
+    "black-eyed susan": 62,
+    "blackberry lily": 101,
+    "blanket flower": 99,
+    "bolero deep blue": 44,
+    "bougainvillea": 94,
+    "bromelia": 98,
+    "buttercup": 47,
+    "californian poppy": 64,
+    "camellia": 95,
+    "canna lily": 89,
+    "canterbury bells": 2,
+    "cape flower": 36,
+    "carnation": 30,
+    "cautleya spicata": 60,
+    "clematis": 81,
+    "colt's foot": 11,
+    "columbine": 83,
+    "common dandelion": 49,
+    "corn poppy": 25,
+    "cyclamen": 87,
+    "daffodil": 41,
+    "desert-rose": 84,
+    "english marigold": 4,
+    "fire lily": 20,
+    "foxglove": 93,
+    "frangipani": 80,
+    "fritillary": 22,
+    "garden phlox": 31,
+    "gaura": 56,
+    "gazania": 70,
+    "geranium": 57,
+    "giant white arum lily": 19,
+    "globe thistle": 9,
+    "globe-flower": 15,
+    "grape hyacinth": 24,
+    "great masterwort": 37,
+    "hard-leaved pocket orchid": 1,
+    "hibiscus": 82,
+    "hippeastrum": 90,
+    "japanese anemone": 61,
+    "king protea": 12,
+    "lenten rose": 39,
+    "lotus": 77,
+    "love in the mist": 32,
+    "magnolia": 86,
+    "mallow": 96,
+    "marigold": 46,
+    "mexican aster": 33,
+    "mexican petunia": 97,
+    "monkshood": 8,
+    "moon orchid": 6,
+    "morning glory": 75,
+    "orange dahlia": 58,
+    "osteospermum": 65,
+    "oxeye daisy": 48,
+    "passion flower": 76,
+    "pelargonium": 54,
+    "peruvian lily": 17,
+    "petunia": 50,
+    "pincushion flower": 21,
+    "pink primrose": 0,
+    "pink-yellow dahlia?": 59,
+    "poinsettia": 43,
+    "primula": 52,
+    "prince of wales feathers": 26,
+    "purple coneflower": 16,
+    "red ginger": 23,
+    "rose": 73,
+    "ruby-lipped cattleya": 35,
+    "siam tulip": 38,
+    "silverbush": 63,
+    "snapdragon": 10,
+    "spear thistle": 13,
+    "spring crocus": 66,
+    "stemless gentian": 27,
+    "sunflower": 53,
+    "sweet pea": 3,
+    "sweet william": 29,
+    "sword lily": 42,
+    "thorn apple": 74,
+    "tiger lily": 5,
+    "toad lily": 78,
+    "tree mallow": 85,
+    "tree poppy": 69,
+    "trumpet creeper": 100,
+    "wallflower": 45,
+    "water lily": 72,
+    "watercress": 88,
+    "wild pansy": 51,
+    "windflower": 68,
+    "yellow iris": 14
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-oxford_flowers102-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-oxford_flowers102-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/README.md b/resnet18-oxford_flowers102-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..7c0396af621941375188a6cede1cb6f42f734294
--- /dev/null
+++ b/resnet18-oxford_flowers102-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford_flowers102.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: oxford_flowers102
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: train
+type: transformers
+val_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: test
+```
+
diff --git a/resnet18-oxford_flowers102-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/config.json b/resnet18-oxford_flowers102-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..f938618d830ad3512a63af4ea0f8ca5e6b26a242
--- /dev/null
+++ b/resnet18-oxford_flowers102-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,247 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "pink primrose",
+    "1": "hard-leaved pocket orchid",
+    "2": "canterbury bells",
+    "3": "sweet pea",
+    "4": "english marigold",
+    "5": "tiger lily",
+    "6": "moon orchid",
+    "7": "bird of paradise",
+    "8": "monkshood",
+    "9": "globe thistle",
+    "10": "snapdragon",
+    "11": "colt's foot",
+    "12": "king protea",
+    "13": "spear thistle",
+    "14": "yellow iris",
+    "15": "globe-flower",
+    "16": "purple coneflower",
+    "17": "peruvian lily",
+    "18": "balloon flower",
+    "19": "giant white arum lily",
+    "20": "fire lily",
+    "21": "pincushion flower",
+    "22": "fritillary",
+    "23": "red ginger",
+    "24": "grape hyacinth",
+    "25": "corn poppy",
+    "26": "prince of wales feathers",
+    "27": "stemless gentian",
+    "28": "artichoke",
+    "29": "sweet william",
+    "30": "carnation",
+    "31": "garden phlox",
+    "32": "love in the mist",
+    "33": "mexican aster",
+    "34": "alpine sea holly",
+    "35": "ruby-lipped cattleya",
+    "36": "cape flower",
+    "37": "great masterwort",
+    "38": "siam tulip",
+    "39": "lenten rose",
+    "40": "barbeton daisy",
+    "41": "daffodil",
+    "42": "sword lily",
+    "43": "poinsettia",
+    "44": "bolero deep blue",
+    "45": "wallflower",
+    "46": "marigold",
+    "47": "buttercup",
+    "48": "oxeye daisy",
+    "49": "common dandelion",
+    "50": "petunia",
+    "51": "wild pansy",
+    "52": "primula",
+    "53": "sunflower",
+    "54": "pelargonium",
+    "55": "bishop of llandaff",
+    "56": "gaura",
+    "57": "geranium",
+    "58": "orange dahlia",
+    "59": "pink-yellow dahlia?",
+    "60": "cautleya spicata",
+    "61": "japanese anemone",
+    "62": "black-eyed susan",
+    "63": "silverbush",
+    "64": "californian poppy",
+    "65": "osteospermum",
+    "66": "spring crocus",
+    "67": "bearded iris",
+    "68": "windflower",
+    "69": "tree poppy",
+    "70": "gazania",
+    "71": "azalea",
+    "72": "water lily",
+    "73": "rose",
+    "74": "thorn apple",
+    "75": "morning glory",
+    "76": "passion flower",
+    "77": "lotus",
+    "78": "toad lily",
+    "79": "anthurium",
+    "80": "frangipani",
+    "81": "clematis",
+    "82": "hibiscus",
+    "83": "columbine",
+    "84": "desert-rose",
+    "85": "tree mallow",
+    "86": "magnolia",
+    "87": "cyclamen",
+    "88": "watercress",
+    "89": "canna lily",
+    "90": "hippeastrum",
+    "91": "bee balm",
+    "92": "ball moss",
+    "93": "foxglove",
+    "94": "bougainvillea",
+    "95": "camellia",
+    "96": "mallow",
+    "97": "mexican petunia",
+    "98": "bromelia",
+    "99": "blanket flower",
+    "100": "trumpet creeper",
+    "101": "blackberry lily"
+  },
+  "label2id": {
+    "alpine sea holly": 34,
+    "anthurium": 79,
+    "artichoke": 28,
+    "azalea": 71,
+    "ball moss": 92,
+    "balloon flower": 18,
+    "barbeton daisy": 40,
+    "bearded iris": 67,
+    "bee balm": 91,
+    "bird of paradise": 7,
+    "bishop of llandaff": 55,
+    "black-eyed susan": 62,
+    "blackberry lily": 101,
+    "blanket flower": 99,
+    "bolero deep blue": 44,
+    "bougainvillea": 94,
+    "bromelia": 98,
+    "buttercup": 47,
+    "californian poppy": 64,
+    "camellia": 95,
+    "canna lily": 89,
+    "canterbury bells": 2,
+    "cape flower": 36,
+    "carnation": 30,
+    "cautleya spicata": 60,
+    "clematis": 81,
+    "colt's foot": 11,
+    "columbine": 83,
+    "common dandelion": 49,
+    "corn poppy": 25,
+    "cyclamen": 87,
+    "daffodil": 41,
+    "desert-rose": 84,
+    "english marigold": 4,
+    "fire lily": 20,
+    "foxglove": 93,
+    "frangipani": 80,
+    "fritillary": 22,
+    "garden phlox": 31,
+    "gaura": 56,
+    "gazania": 70,
+    "geranium": 57,
+    "giant white arum lily": 19,
+    "globe thistle": 9,
+    "globe-flower": 15,
+    "grape hyacinth": 24,
+    "great masterwort": 37,
+    "hard-leaved pocket orchid": 1,
+    "hibiscus": 82,
+    "hippeastrum": 90,
+    "japanese anemone": 61,
+    "king protea": 12,
+    "lenten rose": 39,
+    "lotus": 77,
+    "love in the mist": 32,
+    "magnolia": 86,
+    "mallow": 96,
+    "marigold": 46,
+    "mexican aster": 33,
+    "mexican petunia": 97,
+    "monkshood": 8,
+    "moon orchid": 6,
+    "morning glory": 75,
+    "orange dahlia": 58,
+    "osteospermum": 65,
+    "oxeye daisy": 48,
+    "passion flower": 76,
+    "pelargonium": 54,
+    "peruvian lily": 17,
+    "petunia": 50,
+    "pincushion flower": 21,
+    "pink primrose": 0,
+    "pink-yellow dahlia?": 59,
+    "poinsettia": 43,
+    "primula": 52,
+    "prince of wales feathers": 26,
+    "purple coneflower": 16,
+    "red ginger": 23,
+    "rose": 73,
+    "ruby-lipped cattleya": 35,
+    "siam tulip": 38,
+    "silverbush": 63,
+    "snapdragon": 10,
+    "spear thistle": 13,
+    "spring crocus": 66,
+    "stemless gentian": 27,
+    "sunflower": 53,
+    "sweet pea": 3,
+    "sweet william": 29,
+    "sword lily": 42,
+    "thorn apple": 74,
+    "tiger lily": 5,
+    "toad lily": 78,
+    "tree mallow": 85,
+    "tree poppy": 69,
+    "trumpet creeper": 100,
+    "wallflower": 45,
+    "water lily": 72,
+    "watercress": 88,
+    "wild pansy": 51,
+    "windflower": 68,
+    "yellow iris": 14
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-oxford_flowers102-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet18-oxford_flowers102-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-oxford_flowers102-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-oxford_flowers102-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/README.md b/resnet18-oxford_flowers102-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..54b5a688fc3aec6c2ef318c9b84f1f7c7ffbd931
--- /dev/null
+++ b/resnet18-oxford_flowers102-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford_flowers102.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: oxford_flowers102
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: train
+type: transformers
+val_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: test
+```
+
diff --git a/resnet18-oxford_flowers102-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/config.json b/resnet18-oxford_flowers102-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..f938618d830ad3512a63af4ea0f8ca5e6b26a242
--- /dev/null
+++ b/resnet18-oxford_flowers102-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/config.json
@@ -0,0 +1,247 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "pink primrose",
+    "1": "hard-leaved pocket orchid",
+    "2": "canterbury bells",
+    "3": "sweet pea",
+    "4": "english marigold",
+    "5": "tiger lily",
+    "6": "moon orchid",
+    "7": "bird of paradise",
+    "8": "monkshood",
+    "9": "globe thistle",
+    "10": "snapdragon",
+    "11": "colt's foot",
+    "12": "king protea",
+    "13": "spear thistle",
+    "14": "yellow iris",
+    "15": "globe-flower",
+    "16": "purple coneflower",
+    "17": "peruvian lily",
+    "18": "balloon flower",
+    "19": "giant white arum lily",
+    "20": "fire lily",
+    "21": "pincushion flower",
+    "22": "fritillary",
+    "23": "red ginger",
+    "24": "grape hyacinth",
+    "25": "corn poppy",
+    "26": "prince of wales feathers",
+    "27": "stemless gentian",
+    "28": "artichoke",
+    "29": "sweet william",
+    "30": "carnation",
+    "31": "garden phlox",
+    "32": "love in the mist",
+    "33": "mexican aster",
+    "34": "alpine sea holly",
+    "35": "ruby-lipped cattleya",
+    "36": "cape flower",
+    "37": "great masterwort",
+    "38": "siam tulip",
+    "39": "lenten rose",
+    "40": "barbeton daisy",
+    "41": "daffodil",
+    "42": "sword lily",
+    "43": "poinsettia",
+    "44": "bolero deep blue",
+    "45": "wallflower",
+    "46": "marigold",
+    "47": "buttercup",
+    "48": "oxeye daisy",
+    "49": "common dandelion",
+    "50": "petunia",
+    "51": "wild pansy",
+    "52": "primula",
+    "53": "sunflower",
+    "54": "pelargonium",
+    "55": "bishop of llandaff",
+    "56": "gaura",
+    "57": "geranium",
+    "58": "orange dahlia",
+    "59": "pink-yellow dahlia?",
+    "60": "cautleya spicata",
+    "61": "japanese anemone",
+    "62": "black-eyed susan",
+    "63": "silverbush",
+    "64": "californian poppy",
+    "65": "osteospermum",
+    "66": "spring crocus",
+    "67": "bearded iris",
+    "68": "windflower",
+    "69": "tree poppy",
+    "70": "gazania",
+    "71": "azalea",
+    "72": "water lily",
+    "73": "rose",
+    "74": "thorn apple",
+    "75": "morning glory",
+    "76": "passion flower",
+    "77": "lotus",
+    "78": "toad lily",
+    "79": "anthurium",
+    "80": "frangipani",
+    "81": "clematis",
+    "82": "hibiscus",
+    "83": "columbine",
+    "84": "desert-rose",
+    "85": "tree mallow",
+    "86": "magnolia",
+    "87": "cyclamen",
+    "88": "watercress",
+    "89": "canna lily",
+    "90": "hippeastrum",
+    "91": "bee balm",
+    "92": "ball moss",
+    "93": "foxglove",
+    "94": "bougainvillea",
+    "95": "camellia",
+    "96": "mallow",
+    "97": "mexican petunia",
+    "98": "bromelia",
+    "99": "blanket flower",
+    "100": "trumpet creeper",
+    "101": "blackberry lily"
+  },
+  "label2id": {
+    "alpine sea holly": 34,
+    "anthurium": 79,
+    "artichoke": 28,
+    "azalea": 71,
+    "ball moss": 92,
+    "balloon flower": 18,
+    "barbeton daisy": 40,
+    "bearded iris": 67,
+    "bee balm": 91,
+    "bird of paradise": 7,
+    "bishop of llandaff": 55,
+    "black-eyed susan": 62,
+    "blackberry lily": 101,
+    "blanket flower": 99,
+    "bolero deep blue": 44,
+    "bougainvillea": 94,
+    "bromelia": 98,
+    "buttercup": 47,
+    "californian poppy": 64,
+    "camellia": 95,
+    "canna lily": 89,
+    "canterbury bells": 2,
+    "cape flower": 36,
+    "carnation": 30,
+    "cautleya spicata": 60,
+    "clematis": 81,
+    "colt's foot": 11,
+    "columbine": 83,
+    "common dandelion": 49,
+    "corn poppy": 25,
+    "cyclamen": 87,
+    "daffodil": 41,
+    "desert-rose": 84,
+    "english marigold": 4,
+    "fire lily": 20,
+    "foxglove": 93,
+    "frangipani": 80,
+    "fritillary": 22,
+    "garden phlox": 31,
+    "gaura": 56,
+    "gazania": 70,
+    "geranium": 57,
+    "giant white arum lily": 19,
+    "globe thistle": 9,
+    "globe-flower": 15,
+    "grape hyacinth": 24,
+    "great masterwort": 37,
+    "hard-leaved pocket orchid": 1,
+    "hibiscus": 82,
+    "hippeastrum": 90,
+    "japanese anemone": 61,
+    "king protea": 12,
+    "lenten rose": 39,
+    "lotus": 77,
+    "love in the mist": 32,
+    "magnolia": 86,
+    "mallow": 96,
+    "marigold": 46,
+    "mexican aster": 33,
+    "mexican petunia": 97,
+    "monkshood": 8,
+    "moon orchid": 6,
+    "morning glory": 75,
+    "orange dahlia": 58,
+    "osteospermum": 65,
+    "oxeye daisy": 48,
+    "passion flower": 76,
+    "pelargonium": 54,
+    "peruvian lily": 17,
+    "petunia": 50,
+    "pincushion flower": 21,
+    "pink primrose": 0,
+    "pink-yellow dahlia?": 59,
+    "poinsettia": 43,
+    "primula": 52,
+    "prince of wales feathers": 26,
+    "purple coneflower": 16,
+    "red ginger": 23,
+    "rose": 73,
+    "ruby-lipped cattleya": 35,
+    "siam tulip": 38,
+    "silverbush": 63,
+    "snapdragon": 10,
+    "spear thistle": 13,
+    "spring crocus": 66,
+    "stemless gentian": 27,
+    "sunflower": 53,
+    "sweet pea": 3,
+    "sweet william": 29,
+    "sword lily": 42,
+    "thorn apple": 74,
+    "tiger lily": 5,
+    "toad lily": 78,
+    "tree mallow": 85,
+    "tree poppy": 69,
+    "trumpet creeper": 100,
+    "wallflower": 45,
+    "water lily": 72,
+    "watercress": 88,
+    "wild pansy": 51,
+    "windflower": 68,
+    "yellow iris": 14
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-oxford_flowers102-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet18-oxford_flowers102-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-oxford_flowers102-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-pcam-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/README.md b/resnet18-pcam-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..1fa01cc3746ef5251b098eb52e2e267b60144e53
--- /dev/null
+++ b/resnet18-pcam-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset pcam.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: pcam
+    pretrained: true
+test_datasets: null
+train_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: train
+type: transformers
+val_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: test
+```
+
diff --git a/resnet18-pcam-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/config.json b/resnet18-pcam-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..af7ef4427b07ea4c1e108606639855234dfa1a8d
--- /dev/null
+++ b/resnet18-pcam-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "lymph node",
+    "1": "lymph node containing metastatic tumor tissue"
+  },
+  "label2id": {
+    "lymph node": 0,
+    "lymph node containing metastatic tumor tissue": 1
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-pcam-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet18-pcam-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-pcam-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-pcam-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/README.md b/resnet18-pcam-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..38fef9285e74278a6ffb81c3ca3df51929d2a841
--- /dev/null
+++ b/resnet18-pcam-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset pcam.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: pcam
+    pretrained: true
+test_datasets: null
+train_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: train
+type: transformers
+val_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: test
+```
+
diff --git a/resnet18-pcam-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/config.json b/resnet18-pcam-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..af7ef4427b07ea4c1e108606639855234dfa1a8d
--- /dev/null
+++ b/resnet18-pcam-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "lymph node",
+    "1": "lymph node containing metastatic tumor tissue"
+  },
+  "label2id": {
+    "lymph node": 0,
+    "lymph node containing metastatic tumor tissue": 1
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-pcam-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet18-pcam-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-pcam-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-pcam-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/README.md b/resnet18-pcam-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..776c33a76d389f442a86260039f1e485da733cf8
--- /dev/null
+++ b/resnet18-pcam-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset pcam.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: pcam
+    pretrained: true
+test_datasets: null
+train_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: train
+type: transformers
+val_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: test
+```
+
diff --git a/resnet18-pcam-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/config.json b/resnet18-pcam-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..af7ef4427b07ea4c1e108606639855234dfa1a8d
--- /dev/null
+++ b/resnet18-pcam-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "lymph node",
+    "1": "lymph node containing metastatic tumor tissue"
+  },
+  "label2id": {
+    "lymph node": 0,
+    "lymph node containing metastatic tumor tissue": 1
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-pcam-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet18-pcam-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-pcam-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-pcam-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/README.md b/resnet18-pcam-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..72fa216d803a73ee9702ef761d2a79389b913c40
--- /dev/null
+++ b/resnet18-pcam-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset pcam.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: pcam
+    pretrained: true
+test_datasets: null
+train_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: train
+type: transformers
+val_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: test
+```
+
diff --git a/resnet18-pcam-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/config.json b/resnet18-pcam-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..af7ef4427b07ea4c1e108606639855234dfa1a8d
--- /dev/null
+++ b/resnet18-pcam-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "lymph node",
+    "1": "lymph node containing metastatic tumor tissue"
+  },
+  "label2id": {
+    "lymph node": 0,
+    "lymph node containing metastatic tumor tissue": 1
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-pcam-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet18-pcam-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-pcam-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-pcam-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/README.md b/resnet18-pcam-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..72fa216d803a73ee9702ef761d2a79389b913c40
--- /dev/null
+++ b/resnet18-pcam-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset pcam.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: pcam
+    pretrained: true
+test_datasets: null
+train_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: train
+type: transformers
+val_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: test
+```
+
diff --git a/resnet18-pcam-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/config.json b/resnet18-pcam-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..af7ef4427b07ea4c1e108606639855234dfa1a8d
--- /dev/null
+++ b/resnet18-pcam-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "lymph node",
+    "1": "lymph node containing metastatic tumor tissue"
+  },
+  "label2id": {
+    "lymph node": 0,
+    "lymph node containing metastatic tumor tissue": 1
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-pcam-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet18-pcam-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-pcam-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-pcam-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/README.md b/resnet18-pcam-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..a667c387ee822f13ec11708f42ebf3401a4cbe82
--- /dev/null
+++ b/resnet18-pcam-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset pcam.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: pcam
+    pretrained: true
+test_datasets: null
+train_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: train
+type: transformers
+val_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: test
+```
+
diff --git a/resnet18-pcam-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/config.json b/resnet18-pcam-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..af7ef4427b07ea4c1e108606639855234dfa1a8d
--- /dev/null
+++ b/resnet18-pcam-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "lymph node",
+    "1": "lymph node containing metastatic tumor tissue"
+  },
+  "label2id": {
+    "lymph node": 0,
+    "lymph node containing metastatic tumor tissue": 1
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-pcam-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet18-pcam-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-pcam-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-pcam-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/README.md b/resnet18-pcam-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..189d40cc545fb149c408ee6a90be3fa741ed86bb
--- /dev/null
+++ b/resnet18-pcam-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset pcam.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: pcam
+    pretrained: true
+test_datasets: null
+train_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: train
+type: transformers
+val_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: test
+```
+
diff --git a/resnet18-pcam-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/config.json b/resnet18-pcam-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..af7ef4427b07ea4c1e108606639855234dfa1a8d
--- /dev/null
+++ b/resnet18-pcam-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "lymph node",
+    "1": "lymph node containing metastatic tumor tissue"
+  },
+  "label2id": {
+    "lymph node": 0,
+    "lymph node containing metastatic tumor tissue": 1
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-pcam-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet18-pcam-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-pcam-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-pcam-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/README.md b/resnet18-pcam-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..189d40cc545fb149c408ee6a90be3fa741ed86bb
--- /dev/null
+++ b/resnet18-pcam-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset pcam.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: pcam
+    pretrained: true
+test_datasets: null
+train_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: train
+type: transformers
+val_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: test
+```
+
diff --git a/resnet18-pcam-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/config.json b/resnet18-pcam-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..af7ef4427b07ea4c1e108606639855234dfa1a8d
--- /dev/null
+++ b/resnet18-pcam-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "lymph node",
+    "1": "lymph node containing metastatic tumor tissue"
+  },
+  "label2id": {
+    "lymph node": 0,
+    "lymph node containing metastatic tumor tissue": 1
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-pcam-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet18-pcam-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-pcam-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md b/resnet18-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..385e87fd7d204e0c3a743ed1f59e92b7054b4bb6
--- /dev/null
+++ b/resnet18-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset rendered-sst2.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: rendered-sst2
+    pretrained: true
+test_datasets: null
+train_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: train
+type: transformers
+val_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: test
+```
+
diff --git a/resnet18-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/config.json b/resnet18-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..7de77b1b23edcbdb1f59b2b21726aa56f03fbfdb
--- /dev/null
+++ b/resnet18-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "negative",
+    "1": "positive"
+  },
+  "label2id": {
+    "negative": 0,
+    "positive": 1
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet18-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-rendered-sst2-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/README.md b/resnet18-rendered-sst2-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..2538beb0f91c8b0ed3ea2502aef33e6090141f97
--- /dev/null
+++ b/resnet18-rendered-sst2-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset rendered-sst2.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: rendered-sst2
+    pretrained: true
+test_datasets: null
+train_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: train
+type: transformers
+val_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: test
+```
+
diff --git a/resnet18-rendered-sst2-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/config.json b/resnet18-rendered-sst2-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..7de77b1b23edcbdb1f59b2b21726aa56f03fbfdb
--- /dev/null
+++ b/resnet18-rendered-sst2-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "negative",
+    "1": "positive"
+  },
+  "label2id": {
+    "negative": 0,
+    "positive": 1
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-rendered-sst2-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet18-rendered-sst2-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-rendered-sst2-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/README.md b/resnet18-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..cdd843ae99e73516ef94344cfb4ce552ff3f9f5e
--- /dev/null
+++ b/resnet18-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset rendered-sst2.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: rendered-sst2
+    pretrained: true
+test_datasets: null
+train_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: train
+type: transformers
+val_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: test
+```
+
diff --git a/resnet18-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/config.json b/resnet18-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..7de77b1b23edcbdb1f59b2b21726aa56f03fbfdb
--- /dev/null
+++ b/resnet18-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "negative",
+    "1": "positive"
+  },
+  "label2id": {
+    "negative": 0,
+    "positive": 1
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet18-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/README.md b/resnet18-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..5e1e3a1dd8aa2d838d9b22bacc291f745759f8a6
--- /dev/null
+++ b/resnet18-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset rendered-sst2.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: rendered-sst2
+    pretrained: true
+test_datasets: null
+train_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: train
+type: transformers
+val_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: test
+```
+
diff --git a/resnet18-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/config.json b/resnet18-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..7de77b1b23edcbdb1f59b2b21726aa56f03fbfdb
--- /dev/null
+++ b/resnet18-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "negative",
+    "1": "positive"
+  },
+  "label2id": {
+    "negative": 0,
+    "positive": 1
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet18-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-rendered-sst2-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/README.md b/resnet18-rendered-sst2-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..0da23f89926d81c930429c43b31edb377313d4b5
--- /dev/null
+++ b/resnet18-rendered-sst2-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset rendered-sst2.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: rendered-sst2
+    pretrained: true
+test_datasets: null
+train_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: train
+type: transformers
+val_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: test
+```
+
diff --git a/resnet18-rendered-sst2-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/config.json b/resnet18-rendered-sst2-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..7de77b1b23edcbdb1f59b2b21726aa56f03fbfdb
--- /dev/null
+++ b/resnet18-rendered-sst2-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "negative",
+    "1": "positive"
+  },
+  "label2id": {
+    "negative": 0,
+    "positive": 1
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-rendered-sst2-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet18-rendered-sst2-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-rendered-sst2-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-rendered-sst2-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/README.md b/resnet18-rendered-sst2-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..67e6a3f25aa679dfbead614215a0670757238607
--- /dev/null
+++ b/resnet18-rendered-sst2-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset rendered-sst2.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: rendered-sst2
+    pretrained: true
+test_datasets: null
+train_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: train
+type: transformers
+val_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: test
+```
+
diff --git a/resnet18-rendered-sst2-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/config.json b/resnet18-rendered-sst2-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..7de77b1b23edcbdb1f59b2b21726aa56f03fbfdb
--- /dev/null
+++ b/resnet18-rendered-sst2-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "negative",
+    "1": "positive"
+  },
+  "label2id": {
+    "negative": 0,
+    "positive": 1
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-rendered-sst2-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet18-rendered-sst2-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-rendered-sst2-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-rendered-sst2-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/README.md b/resnet18-rendered-sst2-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..45074acb41f79517faf640834bb384aec44d214a
--- /dev/null
+++ b/resnet18-rendered-sst2-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset rendered-sst2.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: rendered-sst2
+    pretrained: true
+test_datasets: null
+train_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: train
+type: transformers
+val_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: test
+```
+
diff --git a/resnet18-rendered-sst2-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/config.json b/resnet18-rendered-sst2-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..7de77b1b23edcbdb1f59b2b21726aa56f03fbfdb
--- /dev/null
+++ b/resnet18-rendered-sst2-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "negative",
+    "1": "positive"
+  },
+  "label2id": {
+    "negative": 0,
+    "positive": 1
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-rendered-sst2-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet18-rendered-sst2-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-rendered-sst2-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-rendered-sst2-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/README.md b/resnet18-rendered-sst2-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..6800836082891b2c6c3a714d07616108e8fa30f4
--- /dev/null
+++ b/resnet18-rendered-sst2-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset rendered-sst2.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: rendered-sst2
+    pretrained: true
+test_datasets: null
+train_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: train
+type: transformers
+val_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: test
+```
+
diff --git a/resnet18-rendered-sst2-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/config.json b/resnet18-rendered-sst2-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..7de77b1b23edcbdb1f59b2b21726aa56f03fbfdb
--- /dev/null
+++ b/resnet18-rendered-sst2-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "negative",
+    "1": "positive"
+  },
+  "label2id": {
+    "negative": 0,
+    "positive": 1
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-rendered-sst2-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet18-rendered-sst2-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-rendered-sst2-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/README.md b/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..fb867e4f5388196fb06c2ca9f942822d18531d86
--- /dev/null
+++ b/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset resisc45.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: resisc45
+    pretrained: true
+test_datasets: null
+train_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: train
+type: transformers
+val_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: test
+```
+
diff --git a/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/config.json b/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..92840a13704fe0d58f3cc8774361fed5e980dc70
--- /dev/null
+++ b/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/config.json
@@ -0,0 +1,133 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "airport",
+    "2": "baseball diamond",
+    "3": "basketball court",
+    "4": "beach",
+    "5": "bridge",
+    "6": "chaparral",
+    "7": "church",
+    "8": "circular farmland",
+    "9": "cloud",
+    "10": "commercial area",
+    "11": "dense residential",
+    "12": "desert",
+    "13": "forest",
+    "14": "freeway",
+    "15": "golf course",
+    "16": "ground track field",
+    "17": "harbor",
+    "18": "industrial area",
+    "19": "intersection",
+    "20": "island",
+    "21": "lake",
+    "22": "meadow",
+    "23": "medium residential",
+    "24": "mobile home park",
+    "25": "mountain",
+    "26": "overpass",
+    "27": "palace",
+    "28": "parking lot",
+    "29": "railway",
+    "30": "railway station",
+    "31": "rectangular farmland",
+    "32": "river",
+    "33": "roundabout",
+    "34": "runway",
+    "35": "sea ice",
+    "36": "ship",
+    "37": "snowberg",
+    "38": "sparse residential",
+    "39": "stadium",
+    "40": "storage tank",
+    "41": "tennis court",
+    "42": "terrace",
+    "43": "thermal power station",
+    "44": "wetland"
+  },
+  "label2id": {
+    "airplane": 0,
+    "airport": 1,
+    "baseball diamond": 2,
+    "basketball court": 3,
+    "beach": 4,
+    "bridge": 5,
+    "chaparral": 6,
+    "church": 7,
+    "circular farmland": 8,
+    "cloud": 9,
+    "commercial area": 10,
+    "dense residential": 11,
+    "desert": 12,
+    "forest": 13,
+    "freeway": 14,
+    "golf course": 15,
+    "ground track field": 16,
+    "harbor": 17,
+    "industrial area": 18,
+    "intersection": 19,
+    "island": 20,
+    "lake": 21,
+    "meadow": 22,
+    "medium residential": 23,
+    "mobile home park": 24,
+    "mountain": 25,
+    "overpass": 26,
+    "palace": 27,
+    "parking lot": 28,
+    "railway": 29,
+    "railway station": 30,
+    "rectangular farmland": 31,
+    "river": 32,
+    "roundabout": 33,
+    "runway": 34,
+    "sea ice": 35,
+    "ship": 36,
+    "snowberg": 37,
+    "sparse residential": 38,
+    "stadium": 39,
+    "storage tank": 40,
+    "tennis court": 41,
+    "terrace": 42,
+    "thermal power station": 43,
+    "wetland": 44
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/README.md b/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..b2a98a440f17971251b1780e6a37ee6041e86a00
--- /dev/null
+++ b/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset resisc45.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: resisc45
+    pretrained: true
+test_datasets: null
+train_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: train
+type: transformers
+val_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: test
+```
+
diff --git a/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/config.json b/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..92840a13704fe0d58f3cc8774361fed5e980dc70
--- /dev/null
+++ b/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,133 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "airport",
+    "2": "baseball diamond",
+    "3": "basketball court",
+    "4": "beach",
+    "5": "bridge",
+    "6": "chaparral",
+    "7": "church",
+    "8": "circular farmland",
+    "9": "cloud",
+    "10": "commercial area",
+    "11": "dense residential",
+    "12": "desert",
+    "13": "forest",
+    "14": "freeway",
+    "15": "golf course",
+    "16": "ground track field",
+    "17": "harbor",
+    "18": "industrial area",
+    "19": "intersection",
+    "20": "island",
+    "21": "lake",
+    "22": "meadow",
+    "23": "medium residential",
+    "24": "mobile home park",
+    "25": "mountain",
+    "26": "overpass",
+    "27": "palace",
+    "28": "parking lot",
+    "29": "railway",
+    "30": "railway station",
+    "31": "rectangular farmland",
+    "32": "river",
+    "33": "roundabout",
+    "34": "runway",
+    "35": "sea ice",
+    "36": "ship",
+    "37": "snowberg",
+    "38": "sparse residential",
+    "39": "stadium",
+    "40": "storage tank",
+    "41": "tennis court",
+    "42": "terrace",
+    "43": "thermal power station",
+    "44": "wetland"
+  },
+  "label2id": {
+    "airplane": 0,
+    "airport": 1,
+    "baseball diamond": 2,
+    "basketball court": 3,
+    "beach": 4,
+    "bridge": 5,
+    "chaparral": 6,
+    "church": 7,
+    "circular farmland": 8,
+    "cloud": 9,
+    "commercial area": 10,
+    "dense residential": 11,
+    "desert": 12,
+    "forest": 13,
+    "freeway": 14,
+    "golf course": 15,
+    "ground track field": 16,
+    "harbor": 17,
+    "industrial area": 18,
+    "intersection": 19,
+    "island": 20,
+    "lake": 21,
+    "meadow": 22,
+    "medium residential": 23,
+    "mobile home park": 24,
+    "mountain": 25,
+    "overpass": 26,
+    "palace": 27,
+    "parking lot": 28,
+    "railway": 29,
+    "railway station": 30,
+    "rectangular farmland": 31,
+    "river": 32,
+    "roundabout": 33,
+    "runway": 34,
+    "sea ice": 35,
+    "ship": 36,
+    "snowberg": 37,
+    "sparse residential": 38,
+    "stadium": 39,
+    "storage tank": 40,
+    "tennis court": 41,
+    "terrace": 42,
+    "thermal power station": 43,
+    "wetland": 44
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/README.md b/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..b2a98a440f17971251b1780e6a37ee6041e86a00
--- /dev/null
+++ b/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset resisc45.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: resisc45
+    pretrained: true
+test_datasets: null
+train_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: train
+type: transformers
+val_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: test
+```
+
diff --git a/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/config.json b/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..92840a13704fe0d58f3cc8774361fed5e980dc70
--- /dev/null
+++ b/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,133 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "airport",
+    "2": "baseball diamond",
+    "3": "basketball court",
+    "4": "beach",
+    "5": "bridge",
+    "6": "chaparral",
+    "7": "church",
+    "8": "circular farmland",
+    "9": "cloud",
+    "10": "commercial area",
+    "11": "dense residential",
+    "12": "desert",
+    "13": "forest",
+    "14": "freeway",
+    "15": "golf course",
+    "16": "ground track field",
+    "17": "harbor",
+    "18": "industrial area",
+    "19": "intersection",
+    "20": "island",
+    "21": "lake",
+    "22": "meadow",
+    "23": "medium residential",
+    "24": "mobile home park",
+    "25": "mountain",
+    "26": "overpass",
+    "27": "palace",
+    "28": "parking lot",
+    "29": "railway",
+    "30": "railway station",
+    "31": "rectangular farmland",
+    "32": "river",
+    "33": "roundabout",
+    "34": "runway",
+    "35": "sea ice",
+    "36": "ship",
+    "37": "snowberg",
+    "38": "sparse residential",
+    "39": "stadium",
+    "40": "storage tank",
+    "41": "tennis court",
+    "42": "terrace",
+    "43": "thermal power station",
+    "44": "wetland"
+  },
+  "label2id": {
+    "airplane": 0,
+    "airport": 1,
+    "baseball diamond": 2,
+    "basketball court": 3,
+    "beach": 4,
+    "bridge": 5,
+    "chaparral": 6,
+    "church": 7,
+    "circular farmland": 8,
+    "cloud": 9,
+    "commercial area": 10,
+    "dense residential": 11,
+    "desert": 12,
+    "forest": 13,
+    "freeway": 14,
+    "golf course": 15,
+    "ground track field": 16,
+    "harbor": 17,
+    "industrial area": 18,
+    "intersection": 19,
+    "island": 20,
+    "lake": 21,
+    "meadow": 22,
+    "medium residential": 23,
+    "mobile home park": 24,
+    "mountain": 25,
+    "overpass": 26,
+    "palace": 27,
+    "parking lot": 28,
+    "railway": 29,
+    "railway station": 30,
+    "rectangular farmland": 31,
+    "river": 32,
+    "roundabout": 33,
+    "runway": 34,
+    "sea ice": 35,
+    "ship": 36,
+    "snowberg": 37,
+    "sparse residential": 38,
+    "stadium": 39,
+    "storage tank": 40,
+    "tennis court": 41,
+    "terrace": 42,
+    "thermal power station": 43,
+    "wetland": 44
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-resisc45-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/README.md b/resnet18-resisc45-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..1e8f8926efb8536aae6c4b4807f3a03401fb404d
--- /dev/null
+++ b/resnet18-resisc45-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset resisc45.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: resisc45
+    pretrained: true
+test_datasets: null
+train_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: train
+type: transformers
+val_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: test
+```
+
diff --git a/resnet18-resisc45-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/config.json b/resnet18-resisc45-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..92840a13704fe0d58f3cc8774361fed5e980dc70
--- /dev/null
+++ b/resnet18-resisc45-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,133 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "airport",
+    "2": "baseball diamond",
+    "3": "basketball court",
+    "4": "beach",
+    "5": "bridge",
+    "6": "chaparral",
+    "7": "church",
+    "8": "circular farmland",
+    "9": "cloud",
+    "10": "commercial area",
+    "11": "dense residential",
+    "12": "desert",
+    "13": "forest",
+    "14": "freeway",
+    "15": "golf course",
+    "16": "ground track field",
+    "17": "harbor",
+    "18": "industrial area",
+    "19": "intersection",
+    "20": "island",
+    "21": "lake",
+    "22": "meadow",
+    "23": "medium residential",
+    "24": "mobile home park",
+    "25": "mountain",
+    "26": "overpass",
+    "27": "palace",
+    "28": "parking lot",
+    "29": "railway",
+    "30": "railway station",
+    "31": "rectangular farmland",
+    "32": "river",
+    "33": "roundabout",
+    "34": "runway",
+    "35": "sea ice",
+    "36": "ship",
+    "37": "snowberg",
+    "38": "sparse residential",
+    "39": "stadium",
+    "40": "storage tank",
+    "41": "tennis court",
+    "42": "terrace",
+    "43": "thermal power station",
+    "44": "wetland"
+  },
+  "label2id": {
+    "airplane": 0,
+    "airport": 1,
+    "baseball diamond": 2,
+    "basketball court": 3,
+    "beach": 4,
+    "bridge": 5,
+    "chaparral": 6,
+    "church": 7,
+    "circular farmland": 8,
+    "cloud": 9,
+    "commercial area": 10,
+    "dense residential": 11,
+    "desert": 12,
+    "forest": 13,
+    "freeway": 14,
+    "golf course": 15,
+    "ground track field": 16,
+    "harbor": 17,
+    "industrial area": 18,
+    "intersection": 19,
+    "island": 20,
+    "lake": 21,
+    "meadow": 22,
+    "medium residential": 23,
+    "mobile home park": 24,
+    "mountain": 25,
+    "overpass": 26,
+    "palace": 27,
+    "parking lot": 28,
+    "railway": 29,
+    "railway station": 30,
+    "rectangular farmland": 31,
+    "river": 32,
+    "roundabout": 33,
+    "runway": 34,
+    "sea ice": 35,
+    "ship": 36,
+    "snowberg": 37,
+    "sparse residential": 38,
+    "stadium": 39,
+    "storage tank": 40,
+    "tennis court": 41,
+    "terrace": 42,
+    "thermal power station": 43,
+    "wetland": 44
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-resisc45-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet18-resisc45-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-resisc45-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-resisc45-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/README.md b/resnet18-resisc45-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..2e329928e5305e84b2f189ac463dbfa7cd6a4b2c
--- /dev/null
+++ b/resnet18-resisc45-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset resisc45.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: resisc45
+    pretrained: true
+test_datasets: null
+train_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: train
+type: transformers
+val_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: test
+```
+
diff --git a/resnet18-resisc45-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/config.json b/resnet18-resisc45-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..92840a13704fe0d58f3cc8774361fed5e980dc70
--- /dev/null
+++ b/resnet18-resisc45-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,133 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "airport",
+    "2": "baseball diamond",
+    "3": "basketball court",
+    "4": "beach",
+    "5": "bridge",
+    "6": "chaparral",
+    "7": "church",
+    "8": "circular farmland",
+    "9": "cloud",
+    "10": "commercial area",
+    "11": "dense residential",
+    "12": "desert",
+    "13": "forest",
+    "14": "freeway",
+    "15": "golf course",
+    "16": "ground track field",
+    "17": "harbor",
+    "18": "industrial area",
+    "19": "intersection",
+    "20": "island",
+    "21": "lake",
+    "22": "meadow",
+    "23": "medium residential",
+    "24": "mobile home park",
+    "25": "mountain",
+    "26": "overpass",
+    "27": "palace",
+    "28": "parking lot",
+    "29": "railway",
+    "30": "railway station",
+    "31": "rectangular farmland",
+    "32": "river",
+    "33": "roundabout",
+    "34": "runway",
+    "35": "sea ice",
+    "36": "ship",
+    "37": "snowberg",
+    "38": "sparse residential",
+    "39": "stadium",
+    "40": "storage tank",
+    "41": "tennis court",
+    "42": "terrace",
+    "43": "thermal power station",
+    "44": "wetland"
+  },
+  "label2id": {
+    "airplane": 0,
+    "airport": 1,
+    "baseball diamond": 2,
+    "basketball court": 3,
+    "beach": 4,
+    "bridge": 5,
+    "chaparral": 6,
+    "church": 7,
+    "circular farmland": 8,
+    "cloud": 9,
+    "commercial area": 10,
+    "dense residential": 11,
+    "desert": 12,
+    "forest": 13,
+    "freeway": 14,
+    "golf course": 15,
+    "ground track field": 16,
+    "harbor": 17,
+    "industrial area": 18,
+    "intersection": 19,
+    "island": 20,
+    "lake": 21,
+    "meadow": 22,
+    "medium residential": 23,
+    "mobile home park": 24,
+    "mountain": 25,
+    "overpass": 26,
+    "palace": 27,
+    "parking lot": 28,
+    "railway": 29,
+    "railway station": 30,
+    "rectangular farmland": 31,
+    "river": 32,
+    "roundabout": 33,
+    "runway": 34,
+    "sea ice": 35,
+    "ship": 36,
+    "snowberg": 37,
+    "sparse residential": 38,
+    "stadium": 39,
+    "storage tank": 40,
+    "tennis court": 41,
+    "terrace": 42,
+    "thermal power station": 43,
+    "wetland": 44
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-resisc45-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet18-resisc45-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-resisc45-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-resisc45-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/README.md b/resnet18-resisc45-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..43f3bf4b5550ef895944066db027fd45de9a26d1
--- /dev/null
+++ b/resnet18-resisc45-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset resisc45.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: resisc45
+    pretrained: true
+test_datasets: null
+train_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: train
+type: transformers
+val_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: test
+```
+
diff --git a/resnet18-resisc45-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/config.json b/resnet18-resisc45-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..92840a13704fe0d58f3cc8774361fed5e980dc70
--- /dev/null
+++ b/resnet18-resisc45-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,133 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "airport",
+    "2": "baseball diamond",
+    "3": "basketball court",
+    "4": "beach",
+    "5": "bridge",
+    "6": "chaparral",
+    "7": "church",
+    "8": "circular farmland",
+    "9": "cloud",
+    "10": "commercial area",
+    "11": "dense residential",
+    "12": "desert",
+    "13": "forest",
+    "14": "freeway",
+    "15": "golf course",
+    "16": "ground track field",
+    "17": "harbor",
+    "18": "industrial area",
+    "19": "intersection",
+    "20": "island",
+    "21": "lake",
+    "22": "meadow",
+    "23": "medium residential",
+    "24": "mobile home park",
+    "25": "mountain",
+    "26": "overpass",
+    "27": "palace",
+    "28": "parking lot",
+    "29": "railway",
+    "30": "railway station",
+    "31": "rectangular farmland",
+    "32": "river",
+    "33": "roundabout",
+    "34": "runway",
+    "35": "sea ice",
+    "36": "ship",
+    "37": "snowberg",
+    "38": "sparse residential",
+    "39": "stadium",
+    "40": "storage tank",
+    "41": "tennis court",
+    "42": "terrace",
+    "43": "thermal power station",
+    "44": "wetland"
+  },
+  "label2id": {
+    "airplane": 0,
+    "airport": 1,
+    "baseball diamond": 2,
+    "basketball court": 3,
+    "beach": 4,
+    "bridge": 5,
+    "chaparral": 6,
+    "church": 7,
+    "circular farmland": 8,
+    "cloud": 9,
+    "commercial area": 10,
+    "dense residential": 11,
+    "desert": 12,
+    "forest": 13,
+    "freeway": 14,
+    "golf course": 15,
+    "ground track field": 16,
+    "harbor": 17,
+    "industrial area": 18,
+    "intersection": 19,
+    "island": 20,
+    "lake": 21,
+    "meadow": 22,
+    "medium residential": 23,
+    "mobile home park": 24,
+    "mountain": 25,
+    "overpass": 26,
+    "palace": 27,
+    "parking lot": 28,
+    "railway": 29,
+    "railway station": 30,
+    "rectangular farmland": 31,
+    "river": 32,
+    "roundabout": 33,
+    "runway": 34,
+    "sea ice": 35,
+    "ship": 36,
+    "snowberg": 37,
+    "sparse residential": 38,
+    "stadium": 39,
+    "storage tank": 40,
+    "tennis court": 41,
+    "terrace": 42,
+    "thermal power station": 43,
+    "wetland": 44
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-resisc45-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet18-resisc45-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-resisc45-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/README.md b/resnet18-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..aa25f41b2d648e593e599b0f0cb768bf49a721a6
--- /dev/null
+++ b/resnet18-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset resisc45.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: resisc45
+    pretrained: true
+test_datasets: null
+train_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: train
+type: transformers
+val_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: test
+```
+
diff --git a/resnet18-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/config.json b/resnet18-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..92840a13704fe0d58f3cc8774361fed5e980dc70
--- /dev/null
+++ b/resnet18-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,133 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "airport",
+    "2": "baseball diamond",
+    "3": "basketball court",
+    "4": "beach",
+    "5": "bridge",
+    "6": "chaparral",
+    "7": "church",
+    "8": "circular farmland",
+    "9": "cloud",
+    "10": "commercial area",
+    "11": "dense residential",
+    "12": "desert",
+    "13": "forest",
+    "14": "freeway",
+    "15": "golf course",
+    "16": "ground track field",
+    "17": "harbor",
+    "18": "industrial area",
+    "19": "intersection",
+    "20": "island",
+    "21": "lake",
+    "22": "meadow",
+    "23": "medium residential",
+    "24": "mobile home park",
+    "25": "mountain",
+    "26": "overpass",
+    "27": "palace",
+    "28": "parking lot",
+    "29": "railway",
+    "30": "railway station",
+    "31": "rectangular farmland",
+    "32": "river",
+    "33": "roundabout",
+    "34": "runway",
+    "35": "sea ice",
+    "36": "ship",
+    "37": "snowberg",
+    "38": "sparse residential",
+    "39": "stadium",
+    "40": "storage tank",
+    "41": "tennis court",
+    "42": "terrace",
+    "43": "thermal power station",
+    "44": "wetland"
+  },
+  "label2id": {
+    "airplane": 0,
+    "airport": 1,
+    "baseball diamond": 2,
+    "basketball court": 3,
+    "beach": 4,
+    "bridge": 5,
+    "chaparral": 6,
+    "church": 7,
+    "circular farmland": 8,
+    "cloud": 9,
+    "commercial area": 10,
+    "dense residential": 11,
+    "desert": 12,
+    "forest": 13,
+    "freeway": 14,
+    "golf course": 15,
+    "ground track field": 16,
+    "harbor": 17,
+    "industrial area": 18,
+    "intersection": 19,
+    "island": 20,
+    "lake": 21,
+    "meadow": 22,
+    "medium residential": 23,
+    "mobile home park": 24,
+    "mountain": 25,
+    "overpass": 26,
+    "palace": 27,
+    "parking lot": 28,
+    "railway": 29,
+    "railway station": 30,
+    "rectangular farmland": 31,
+    "river": 32,
+    "roundabout": 33,
+    "runway": 34,
+    "sea ice": 35,
+    "ship": 36,
+    "snowberg": 37,
+    "sparse residential": 38,
+    "stadium": 39,
+    "storage tank": 40,
+    "tennis court": 41,
+    "terrace": 42,
+    "thermal power station": 43,
+    "wetland": 44
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet18-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-resisc45-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/README.md b/resnet18-resisc45-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..f1ac265120a40de02cb741e7b6869c2e323f3ccb
--- /dev/null
+++ b/resnet18-resisc45-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset resisc45.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: resisc45
+    pretrained: true
+test_datasets: null
+train_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: train
+type: transformers
+val_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: test
+```
+
diff --git a/resnet18-resisc45-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/config.json b/resnet18-resisc45-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..92840a13704fe0d58f3cc8774361fed5e980dc70
--- /dev/null
+++ b/resnet18-resisc45-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,133 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "airport",
+    "2": "baseball diamond",
+    "3": "basketball court",
+    "4": "beach",
+    "5": "bridge",
+    "6": "chaparral",
+    "7": "church",
+    "8": "circular farmland",
+    "9": "cloud",
+    "10": "commercial area",
+    "11": "dense residential",
+    "12": "desert",
+    "13": "forest",
+    "14": "freeway",
+    "15": "golf course",
+    "16": "ground track field",
+    "17": "harbor",
+    "18": "industrial area",
+    "19": "intersection",
+    "20": "island",
+    "21": "lake",
+    "22": "meadow",
+    "23": "medium residential",
+    "24": "mobile home park",
+    "25": "mountain",
+    "26": "overpass",
+    "27": "palace",
+    "28": "parking lot",
+    "29": "railway",
+    "30": "railway station",
+    "31": "rectangular farmland",
+    "32": "river",
+    "33": "roundabout",
+    "34": "runway",
+    "35": "sea ice",
+    "36": "ship",
+    "37": "snowberg",
+    "38": "sparse residential",
+    "39": "stadium",
+    "40": "storage tank",
+    "41": "tennis court",
+    "42": "terrace",
+    "43": "thermal power station",
+    "44": "wetland"
+  },
+  "label2id": {
+    "airplane": 0,
+    "airport": 1,
+    "baseball diamond": 2,
+    "basketball court": 3,
+    "beach": 4,
+    "bridge": 5,
+    "chaparral": 6,
+    "church": 7,
+    "circular farmland": 8,
+    "cloud": 9,
+    "commercial area": 10,
+    "dense residential": 11,
+    "desert": 12,
+    "forest": 13,
+    "freeway": 14,
+    "golf course": 15,
+    "ground track field": 16,
+    "harbor": 17,
+    "industrial area": 18,
+    "intersection": 19,
+    "island": 20,
+    "lake": 21,
+    "meadow": 22,
+    "medium residential": 23,
+    "mobile home park": 24,
+    "mountain": 25,
+    "overpass": 26,
+    "palace": 27,
+    "parking lot": 28,
+    "railway": 29,
+    "railway station": 30,
+    "rectangular farmland": 31,
+    "river": 32,
+    "roundabout": 33,
+    "runway": 34,
+    "sea ice": 35,
+    "ship": 36,
+    "snowberg": 37,
+    "sparse residential": 38,
+    "stadium": 39,
+    "storage tank": 40,
+    "tennis court": 41,
+    "terrace": 42,
+    "thermal power station": 43,
+    "wetland": 44
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-resisc45-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet18-resisc45-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-resisc45-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-resisc45-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/README.md b/resnet18-resisc45-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..6d613130e429d57d862e265f740cf6dc399b969c
--- /dev/null
+++ b/resnet18-resisc45-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset resisc45.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: resisc45
+    pretrained: true
+test_datasets: null
+train_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: train
+type: transformers
+val_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: test
+```
+
diff --git a/resnet18-resisc45-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/config.json b/resnet18-resisc45-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..92840a13704fe0d58f3cc8774361fed5e980dc70
--- /dev/null
+++ b/resnet18-resisc45-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/config.json
@@ -0,0 +1,133 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "airport",
+    "2": "baseball diamond",
+    "3": "basketball court",
+    "4": "beach",
+    "5": "bridge",
+    "6": "chaparral",
+    "7": "church",
+    "8": "circular farmland",
+    "9": "cloud",
+    "10": "commercial area",
+    "11": "dense residential",
+    "12": "desert",
+    "13": "forest",
+    "14": "freeway",
+    "15": "golf course",
+    "16": "ground track field",
+    "17": "harbor",
+    "18": "industrial area",
+    "19": "intersection",
+    "20": "island",
+    "21": "lake",
+    "22": "meadow",
+    "23": "medium residential",
+    "24": "mobile home park",
+    "25": "mountain",
+    "26": "overpass",
+    "27": "palace",
+    "28": "parking lot",
+    "29": "railway",
+    "30": "railway station",
+    "31": "rectangular farmland",
+    "32": "river",
+    "33": "roundabout",
+    "34": "runway",
+    "35": "sea ice",
+    "36": "ship",
+    "37": "snowberg",
+    "38": "sparse residential",
+    "39": "stadium",
+    "40": "storage tank",
+    "41": "tennis court",
+    "42": "terrace",
+    "43": "thermal power station",
+    "44": "wetland"
+  },
+  "label2id": {
+    "airplane": 0,
+    "airport": 1,
+    "baseball diamond": 2,
+    "basketball court": 3,
+    "beach": 4,
+    "bridge": 5,
+    "chaparral": 6,
+    "church": 7,
+    "circular farmland": 8,
+    "cloud": 9,
+    "commercial area": 10,
+    "dense residential": 11,
+    "desert": 12,
+    "forest": 13,
+    "freeway": 14,
+    "golf course": 15,
+    "ground track field": 16,
+    "harbor": 17,
+    "industrial area": 18,
+    "intersection": 19,
+    "island": 20,
+    "lake": 21,
+    "meadow": 22,
+    "medium residential": 23,
+    "mobile home park": 24,
+    "mountain": 25,
+    "overpass": 26,
+    "palace": 27,
+    "parking lot": 28,
+    "railway": 29,
+    "railway station": 30,
+    "rectangular farmland": 31,
+    "river": 32,
+    "roundabout": 33,
+    "runway": 34,
+    "sea ice": 35,
+    "ship": 36,
+    "snowberg": 37,
+    "sparse residential": 38,
+    "stadium": 39,
+    "storage tank": 40,
+    "tennis court": 41,
+    "terrace": 42,
+    "thermal power station": 43,
+    "wetland": 44
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-resisc45-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet18-resisc45-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-resisc45-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-resisc45-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/README.md b/resnet18-resisc45-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..2eed7926b52f582181e58f47a6a6cd22d0834d72
--- /dev/null
+++ b/resnet18-resisc45-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset resisc45.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: resisc45
+    pretrained: true
+test_datasets: null
+train_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: train
+type: transformers
+val_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: test
+```
+
diff --git a/resnet18-resisc45-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/config.json b/resnet18-resisc45-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..92840a13704fe0d58f3cc8774361fed5e980dc70
--- /dev/null
+++ b/resnet18-resisc45-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,133 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "airport",
+    "2": "baseball diamond",
+    "3": "basketball court",
+    "4": "beach",
+    "5": "bridge",
+    "6": "chaparral",
+    "7": "church",
+    "8": "circular farmland",
+    "9": "cloud",
+    "10": "commercial area",
+    "11": "dense residential",
+    "12": "desert",
+    "13": "forest",
+    "14": "freeway",
+    "15": "golf course",
+    "16": "ground track field",
+    "17": "harbor",
+    "18": "industrial area",
+    "19": "intersection",
+    "20": "island",
+    "21": "lake",
+    "22": "meadow",
+    "23": "medium residential",
+    "24": "mobile home park",
+    "25": "mountain",
+    "26": "overpass",
+    "27": "palace",
+    "28": "parking lot",
+    "29": "railway",
+    "30": "railway station",
+    "31": "rectangular farmland",
+    "32": "river",
+    "33": "roundabout",
+    "34": "runway",
+    "35": "sea ice",
+    "36": "ship",
+    "37": "snowberg",
+    "38": "sparse residential",
+    "39": "stadium",
+    "40": "storage tank",
+    "41": "tennis court",
+    "42": "terrace",
+    "43": "thermal power station",
+    "44": "wetland"
+  },
+  "label2id": {
+    "airplane": 0,
+    "airport": 1,
+    "baseball diamond": 2,
+    "basketball court": 3,
+    "beach": 4,
+    "bridge": 5,
+    "chaparral": 6,
+    "church": 7,
+    "circular farmland": 8,
+    "cloud": 9,
+    "commercial area": 10,
+    "dense residential": 11,
+    "desert": 12,
+    "forest": 13,
+    "freeway": 14,
+    "golf course": 15,
+    "ground track field": 16,
+    "harbor": 17,
+    "industrial area": 18,
+    "intersection": 19,
+    "island": 20,
+    "lake": 21,
+    "meadow": 22,
+    "medium residential": 23,
+    "mobile home park": 24,
+    "mountain": 25,
+    "overpass": 26,
+    "palace": 27,
+    "parking lot": 28,
+    "railway": 29,
+    "railway station": 30,
+    "rectangular farmland": 31,
+    "river": 32,
+    "roundabout": 33,
+    "runway": 34,
+    "sea ice": 35,
+    "ship": 36,
+    "snowberg": 37,
+    "sparse residential": 38,
+    "stadium": 39,
+    "storage tank": 40,
+    "tennis court": 41,
+    "terrace": 42,
+    "thermal power station": 43,
+    "wetland": 44
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-resisc45-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet18-resisc45-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-resisc45-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/README.md b/resnet18-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..36c4b40c21d97eed539b84dd0d47d79314d53ce4
--- /dev/null
+++ b/resnet18-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stanford-cars.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: stanford-cars
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: train
+type: transformers
+val_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: test
+```
+
diff --git a/resnet18-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/config.json b/resnet18-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..ea904dca37c3e1bd676cdab8c844dff369a4e286
--- /dev/null
+++ b/resnet18-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,435 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "AM General Hummer SUV 2000",
+    "1": "Acura RL Sedan 2012",
+    "2": "Acura TL Sedan 2012",
+    "3": "Acura TL Type-S 2008",
+    "4": "Acura TSX Sedan 2012",
+    "5": "Acura Integra Type R 2001",
+    "6": "Acura ZDX Hatchback 2012",
+    "7": "Aston Martin V8 Vantage Convertible 2012",
+    "8": "Aston Martin V8 Vantage Coupe 2012",
+    "9": "Aston Martin Virage Convertible 2012",
+    "10": "Aston Martin Virage Coupe 2012",
+    "11": "Audi RS 4 Convertible 2008",
+    "12": "Audi A5 Coupe 2012",
+    "13": "Audi TTS Coupe 2012",
+    "14": "Audi R8 Coupe 2012",
+    "15": "Audi V8 Sedan 1994",
+    "16": "Audi 100 Sedan 1994",
+    "17": "Audi 100 Wagon 1994",
+    "18": "Audi TT Hatchback 2011",
+    "19": "Audi S6 Sedan 2011",
+    "20": "Audi S5 Convertible 2012",
+    "21": "Audi S5 Coupe 2012",
+    "22": "Audi S4 Sedan 2012",
+    "23": "Audi S4 Sedan 2007",
+    "24": "Audi TT RS Coupe 2012",
+    "25": "BMW ActiveHybrid 5 Sedan 2012",
+    "26": "BMW 1 Series Convertible 2012",
+    "27": "BMW 1 Series Coupe 2012",
+    "28": "BMW 3 Series Sedan 2012",
+    "29": "BMW 3 Series Wagon 2012",
+    "30": "BMW 6 Series Convertible 2007",
+    "31": "BMW X5 SUV 2007",
+    "32": "BMW X6 SUV 2012",
+    "33": "BMW M3 Coupe 2012",
+    "34": "BMW M5 Sedan 2010",
+    "35": "BMW M6 Convertible 2010",
+    "36": "BMW X3 SUV 2012",
+    "37": "BMW Z4 Convertible 2012",
+    "38": "Bentley Continental Supersports Conv. Convertible 2012",
+    "39": "Bentley Arnage Sedan 2009",
+    "40": "Bentley Mulsanne Sedan 2011",
+    "41": "Bentley Continental GT Coupe 2012",
+    "42": "Bentley Continental GT Coupe 2007",
+    "43": "Bentley Continental Flying Spur Sedan 2007",
+    "44": "Bugatti Veyron 16.4 Convertible 2009",
+    "45": "Bugatti Veyron 16.4 Coupe 2009",
+    "46": "Buick Regal GS 2012",
+    "47": "Buick Rainier SUV 2007",
+    "48": "Buick Verano Sedan 2012",
+    "49": "Buick Enclave SUV 2012",
+    "50": "Cadillac CTS-V Sedan 2012",
+    "51": "Cadillac SRX SUV 2012",
+    "52": "Cadillac Escalade EXT Crew Cab 2007",
+    "53": "Chevrolet Silverado 1500 Hybrid Crew Cab 2012",
+    "54": "Chevrolet Corvette Convertible 2012",
+    "55": "Chevrolet Corvette ZR1 2012",
+    "56": "Chevrolet Corvette Ron Fellows Edition Z06 2007",
+    "57": "Chevrolet Traverse SUV 2012",
+    "58": "Chevrolet Camaro Convertible 2012",
+    "59": "Chevrolet HHR SS 2010",
+    "60": "Chevrolet Impala Sedan 2007",
+    "61": "Chevrolet Tahoe Hybrid SUV 2012",
+    "62": "Chevrolet Sonic Sedan 2012",
+    "63": "Chevrolet Express Cargo Van 2007",
+    "64": "Chevrolet Avalanche Crew Cab 2012",
+    "65": "Chevrolet Cobalt SS 2010",
+    "66": "Chevrolet Malibu Hybrid Sedan 2010",
+    "67": "Chevrolet TrailBlazer SS 2009",
+    "68": "Chevrolet Silverado 2500HD Regular Cab 2012",
+    "69": "Chevrolet Silverado 1500 Classic Extended Cab 2007",
+    "70": "Chevrolet Express Van 2007",
+    "71": "Chevrolet Monte Carlo Coupe 2007",
+    "72": "Chevrolet Malibu Sedan 2007",
+    "73": "Chevrolet Silverado 1500 Extended Cab 2012",
+    "74": "Chevrolet Silverado 1500 Regular Cab 2012",
+    "75": "Chrysler Aspen SUV 2009",
+    "76": "Chrysler Sebring Convertible 2010",
+    "77": "Chrysler Town and Country Minivan 2012",
+    "78": "Chrysler 300 SRT-8 2010",
+    "79": "Chrysler Crossfire Convertible 2008",
+    "80": "Chrysler PT Cruiser Convertible 2008",
+    "81": "Daewoo Nubira Wagon 2002",
+    "82": "Dodge Caliber Wagon 2012",
+    "83": "Dodge Caliber Wagon 2007",
+    "84": "Dodge Caravan Minivan 1997",
+    "85": "Dodge Ram Pickup 3500 Crew Cab 2010",
+    "86": "Dodge Ram Pickup 3500 Quad Cab 2009",
+    "87": "Dodge Sprinter Cargo Van 2009",
+    "88": "Dodge Journey SUV 2012",
+    "89": "Dodge Dakota Crew Cab 2010",
+    "90": "Dodge Dakota Club Cab 2007",
+    "91": "Dodge Magnum Wagon 2008",
+    "92": "Dodge Challenger SRT8 2011",
+    "93": "Dodge Durango SUV 2012",
+    "94": "Dodge Durango SUV 2007",
+    "95": "Dodge Charger Sedan 2012",
+    "96": "Dodge Charger SRT-8 2009",
+    "97": "Eagle Talon Hatchback 1998",
+    "98": "FIAT 500 Abarth 2012",
+    "99": "FIAT 500 Convertible 2012",
+    "100": "Ferrari FF Coupe 2012",
+    "101": "Ferrari California Convertible 2012",
+    "102": "Ferrari 458 Italia Convertible 2012",
+    "103": "Ferrari 458 Italia Coupe 2012",
+    "104": "Fisker Karma Sedan 2012",
+    "105": "Ford F-450 Super Duty Crew Cab 2012",
+    "106": "Ford Mustang Convertible 2007",
+    "107": "Ford Freestar Minivan 2007",
+    "108": "Ford Expedition EL SUV 2009",
+    "109": "Ford Edge SUV 2012",
+    "110": "Ford Ranger SuperCab 2011",
+    "111": "Ford GT Coupe 2006",
+    "112": "Ford F-150 Regular Cab 2012",
+    "113": "Ford F-150 Regular Cab 2007",
+    "114": "Ford Focus Sedan 2007",
+    "115": "Ford E-Series Wagon Van 2012",
+    "116": "Ford Fiesta Sedan 2012",
+    "117": "GMC Terrain SUV 2012",
+    "118": "GMC Savana Van 2012",
+    "119": "GMC Yukon Hybrid SUV 2012",
+    "120": "GMC Acadia SUV 2012",
+    "121": "GMC Canyon Extended Cab 2012",
+    "122": "Geo Metro Convertible 1993",
+    "123": "HUMMER H3T Crew Cab 2010",
+    "124": "HUMMER H2 SUT Crew Cab 2009",
+    "125": "Honda Odyssey Minivan 2012",
+    "126": "Honda Odyssey Minivan 2007",
+    "127": "Honda Accord Coupe 2012",
+    "128": "Honda Accord Sedan 2012",
+    "129": "Hyundai Veloster Hatchback 2012",
+    "130": "Hyundai Santa Fe SUV 2012",
+    "131": "Hyundai Tucson SUV 2012",
+    "132": "Hyundai Veracruz SUV 2012",
+    "133": "Hyundai Sonata Hybrid Sedan 2012",
+    "134": "Hyundai Elantra Sedan 2007",
+    "135": "Hyundai Accent Sedan 2012",
+    "136": "Hyundai Genesis Sedan 2012",
+    "137": "Hyundai Sonata Sedan 2012",
+    "138": "Hyundai Elantra Touring Hatchback 2012",
+    "139": "Hyundai Azera Sedan 2012",
+    "140": "Infiniti G Coupe IPL 2012",
+    "141": "Infiniti QX56 SUV 2011",
+    "142": "Isuzu Ascender SUV 2008",
+    "143": "Jaguar XK XKR 2012",
+    "144": "Jeep Patriot SUV 2012",
+    "145": "Jeep Wrangler SUV 2012",
+    "146": "Jeep Liberty SUV 2012",
+    "147": "Jeep Grand Cherokee SUV 2012",
+    "148": "Jeep Compass SUV 2012",
+    "149": "Lamborghini Reventon Coupe 2008",
+    "150": "Lamborghini Aventador Coupe 2012",
+    "151": "Lamborghini Gallardo LP 570-4 Superleggera 2012",
+    "152": "Lamborghini Diablo Coupe 2001",
+    "153": "Land Rover Range Rover SUV 2012",
+    "154": "Land Rover LR2 SUV 2012",
+    "155": "Lincoln Town Car Sedan 2011",
+    "156": "MINI Cooper Roadster Convertible 2012",
+    "157": "Maybach Landaulet Convertible 2012",
+    "158": "Mazda Tribute SUV 2011",
+    "159": "McLaren MP4-12C Coupe 2012",
+    "160": "Mercedes-Benz 300-Class Convertible 1993",
+    "161": "Mercedes-Benz C-Class Sedan 2012",
+    "162": "Mercedes-Benz SL-Class Coupe 2009",
+    "163": "Mercedes-Benz E-Class Sedan 2012",
+    "164": "Mercedes-Benz S-Class Sedan 2012",
+    "165": "Mercedes-Benz Sprinter Van 2012",
+    "166": "Mitsubishi Lancer Sedan 2012",
+    "167": "Nissan Leaf Hatchback 2012",
+    "168": "Nissan NV Passenger Van 2012",
+    "169": "Nissan Juke Hatchback 2012",
+    "170": "Nissan 240SX Coupe 1998",
+    "171": "Plymouth Neon Coupe 1999",
+    "172": "Porsche Panamera Sedan 2012",
+    "173": "Ram C/V Cargo Van Minivan 2012",
+    "174": "Rolls-Royce Phantom Drophead Coupe Convertible 2012",
+    "175": "Rolls-Royce Ghost Sedan 2012",
+    "176": "Rolls-Royce Phantom Sedan 2012",
+    "177": "Scion xD Hatchback 2012",
+    "178": "Spyker C8 Convertible 2009",
+    "179": "Spyker C8 Coupe 2009",
+    "180": "Suzuki Aerio Sedan 2007",
+    "181": "Suzuki Kizashi Sedan 2012",
+    "182": "Suzuki SX4 Hatchback 2012",
+    "183": "Suzuki SX4 Sedan 2012",
+    "184": "Tesla Model S Sedan 2012",
+    "185": "Toyota Sequoia SUV 2012",
+    "186": "Toyota Camry Sedan 2012",
+    "187": "Toyota Corolla Sedan 2012",
+    "188": "Toyota 4Runner SUV 2012",
+    "189": "Volkswagen Golf Hatchback 2012",
+    "190": "Volkswagen Golf Hatchback 1991",
+    "191": "Volkswagen Beetle Hatchback 2012",
+    "192": "Volvo C30 Hatchback 2012",
+    "193": "Volvo 240 Sedan 1993",
+    "194": "Volvo XC90 SUV 2007",
+    "195": "smart fortwo Convertible 2012"
+  },
+  "label2id": {
+    "AM General Hummer SUV 2000": 0,
+    "Acura Integra Type R 2001": 5,
+    "Acura RL Sedan 2012": 1,
+    "Acura TL Sedan 2012": 2,
+    "Acura TL Type-S 2008": 3,
+    "Acura TSX Sedan 2012": 4,
+    "Acura ZDX Hatchback 2012": 6,
+    "Aston Martin V8 Vantage Convertible 2012": 7,
+    "Aston Martin V8 Vantage Coupe 2012": 8,
+    "Aston Martin Virage Convertible 2012": 9,
+    "Aston Martin Virage Coupe 2012": 10,
+    "Audi 100 Sedan 1994": 16,
+    "Audi 100 Wagon 1994": 17,
+    "Audi A5 Coupe 2012": 12,
+    "Audi R8 Coupe 2012": 14,
+    "Audi RS 4 Convertible 2008": 11,
+    "Audi S4 Sedan 2007": 23,
+    "Audi S4 Sedan 2012": 22,
+    "Audi S5 Convertible 2012": 20,
+    "Audi S5 Coupe 2012": 21,
+    "Audi S6 Sedan 2011": 19,
+    "Audi TT Hatchback 2011": 18,
+    "Audi TT RS Coupe 2012": 24,
+    "Audi TTS Coupe 2012": 13,
+    "Audi V8 Sedan 1994": 15,
+    "BMW 1 Series Convertible 2012": 26,
+    "BMW 1 Series Coupe 2012": 27,
+    "BMW 3 Series Sedan 2012": 28,
+    "BMW 3 Series Wagon 2012": 29,
+    "BMW 6 Series Convertible 2007": 30,
+    "BMW ActiveHybrid 5 Sedan 2012": 25,
+    "BMW M3 Coupe 2012": 33,
+    "BMW M5 Sedan 2010": 34,
+    "BMW M6 Convertible 2010": 35,
+    "BMW X3 SUV 2012": 36,
+    "BMW X5 SUV 2007": 31,
+    "BMW X6 SUV 2012": 32,
+    "BMW Z4 Convertible 2012": 37,
+    "Bentley Arnage Sedan 2009": 39,
+    "Bentley Continental Flying Spur Sedan 2007": 43,
+    "Bentley Continental GT Coupe 2007": 42,
+    "Bentley Continental GT Coupe 2012": 41,
+    "Bentley Continental Supersports Conv. Convertible 2012": 38,
+    "Bentley Mulsanne Sedan 2011": 40,
+    "Bugatti Veyron 16.4 Convertible 2009": 44,
+    "Bugatti Veyron 16.4 Coupe 2009": 45,
+    "Buick Enclave SUV 2012": 49,
+    "Buick Rainier SUV 2007": 47,
+    "Buick Regal GS 2012": 46,
+    "Buick Verano Sedan 2012": 48,
+    "Cadillac CTS-V Sedan 2012": 50,
+    "Cadillac Escalade EXT Crew Cab 2007": 52,
+    "Cadillac SRX SUV 2012": 51,
+    "Chevrolet Avalanche Crew Cab 2012": 64,
+    "Chevrolet Camaro Convertible 2012": 58,
+    "Chevrolet Cobalt SS 2010": 65,
+    "Chevrolet Corvette Convertible 2012": 54,
+    "Chevrolet Corvette Ron Fellows Edition Z06 2007": 56,
+    "Chevrolet Corvette ZR1 2012": 55,
+    "Chevrolet Express Cargo Van 2007": 63,
+    "Chevrolet Express Van 2007": 70,
+    "Chevrolet HHR SS 2010": 59,
+    "Chevrolet Impala Sedan 2007": 60,
+    "Chevrolet Malibu Hybrid Sedan 2010": 66,
+    "Chevrolet Malibu Sedan 2007": 72,
+    "Chevrolet Monte Carlo Coupe 2007": 71,
+    "Chevrolet Silverado 1500 Classic Extended Cab 2007": 69,
+    "Chevrolet Silverado 1500 Extended Cab 2012": 73,
+    "Chevrolet Silverado 1500 Hybrid Crew Cab 2012": 53,
+    "Chevrolet Silverado 1500 Regular Cab 2012": 74,
+    "Chevrolet Silverado 2500HD Regular Cab 2012": 68,
+    "Chevrolet Sonic Sedan 2012": 62,
+    "Chevrolet Tahoe Hybrid SUV 2012": 61,
+    "Chevrolet TrailBlazer SS 2009": 67,
+    "Chevrolet Traverse SUV 2012": 57,
+    "Chrysler 300 SRT-8 2010": 78,
+    "Chrysler Aspen SUV 2009": 75,
+    "Chrysler Crossfire Convertible 2008": 79,
+    "Chrysler PT Cruiser Convertible 2008": 80,
+    "Chrysler Sebring Convertible 2010": 76,
+    "Chrysler Town and Country Minivan 2012": 77,
+    "Daewoo Nubira Wagon 2002": 81,
+    "Dodge Caliber Wagon 2007": 83,
+    "Dodge Caliber Wagon 2012": 82,
+    "Dodge Caravan Minivan 1997": 84,
+    "Dodge Challenger SRT8 2011": 92,
+    "Dodge Charger SRT-8 2009": 96,
+    "Dodge Charger Sedan 2012": 95,
+    "Dodge Dakota Club Cab 2007": 90,
+    "Dodge Dakota Crew Cab 2010": 89,
+    "Dodge Durango SUV 2007": 94,
+    "Dodge Durango SUV 2012": 93,
+    "Dodge Journey SUV 2012": 88,
+    "Dodge Magnum Wagon 2008": 91,
+    "Dodge Ram Pickup 3500 Crew Cab 2010": 85,
+    "Dodge Ram Pickup 3500 Quad Cab 2009": 86,
+    "Dodge Sprinter Cargo Van 2009": 87,
+    "Eagle Talon Hatchback 1998": 97,
+    "FIAT 500 Abarth 2012": 98,
+    "FIAT 500 Convertible 2012": 99,
+    "Ferrari 458 Italia Convertible 2012": 102,
+    "Ferrari 458 Italia Coupe 2012": 103,
+    "Ferrari California Convertible 2012": 101,
+    "Ferrari FF Coupe 2012": 100,
+    "Fisker Karma Sedan 2012": 104,
+    "Ford E-Series Wagon Van 2012": 115,
+    "Ford Edge SUV 2012": 109,
+    "Ford Expedition EL SUV 2009": 108,
+    "Ford F-150 Regular Cab 2007": 113,
+    "Ford F-150 Regular Cab 2012": 112,
+    "Ford F-450 Super Duty Crew Cab 2012": 105,
+    "Ford Fiesta Sedan 2012": 116,
+    "Ford Focus Sedan 2007": 114,
+    "Ford Freestar Minivan 2007": 107,
+    "Ford GT Coupe 2006": 111,
+    "Ford Mustang Convertible 2007": 106,
+    "Ford Ranger SuperCab 2011": 110,
+    "GMC Acadia SUV 2012": 120,
+    "GMC Canyon Extended Cab 2012": 121,
+    "GMC Savana Van 2012": 118,
+    "GMC Terrain SUV 2012": 117,
+    "GMC Yukon Hybrid SUV 2012": 119,
+    "Geo Metro Convertible 1993": 122,
+    "HUMMER H2 SUT Crew Cab 2009": 124,
+    "HUMMER H3T Crew Cab 2010": 123,
+    "Honda Accord Coupe 2012": 127,
+    "Honda Accord Sedan 2012": 128,
+    "Honda Odyssey Minivan 2007": 126,
+    "Honda Odyssey Minivan 2012": 125,
+    "Hyundai Accent Sedan 2012": 135,
+    "Hyundai Azera Sedan 2012": 139,
+    "Hyundai Elantra Sedan 2007": 134,
+    "Hyundai Elantra Touring Hatchback 2012": 138,
+    "Hyundai Genesis Sedan 2012": 136,
+    "Hyundai Santa Fe SUV 2012": 130,
+    "Hyundai Sonata Hybrid Sedan 2012": 133,
+    "Hyundai Sonata Sedan 2012": 137,
+    "Hyundai Tucson SUV 2012": 131,
+    "Hyundai Veloster Hatchback 2012": 129,
+    "Hyundai Veracruz SUV 2012": 132,
+    "Infiniti G Coupe IPL 2012": 140,
+    "Infiniti QX56 SUV 2011": 141,
+    "Isuzu Ascender SUV 2008": 142,
+    "Jaguar XK XKR 2012": 143,
+    "Jeep Compass SUV 2012": 148,
+    "Jeep Grand Cherokee SUV 2012": 147,
+    "Jeep Liberty SUV 2012": 146,
+    "Jeep Patriot SUV 2012": 144,
+    "Jeep Wrangler SUV 2012": 145,
+    "Lamborghini Aventador Coupe 2012": 150,
+    "Lamborghini Diablo Coupe 2001": 152,
+    "Lamborghini Gallardo LP 570-4 Superleggera 2012": 151,
+    "Lamborghini Reventon Coupe 2008": 149,
+    "Land Rover LR2 SUV 2012": 154,
+    "Land Rover Range Rover SUV 2012": 153,
+    "Lincoln Town Car Sedan 2011": 155,
+    "MINI Cooper Roadster Convertible 2012": 156,
+    "Maybach Landaulet Convertible 2012": 157,
+    "Mazda Tribute SUV 2011": 158,
+    "McLaren MP4-12C Coupe 2012": 159,
+    "Mercedes-Benz 300-Class Convertible 1993": 160,
+    "Mercedes-Benz C-Class Sedan 2012": 161,
+    "Mercedes-Benz E-Class Sedan 2012": 163,
+    "Mercedes-Benz S-Class Sedan 2012": 164,
+    "Mercedes-Benz SL-Class Coupe 2009": 162,
+    "Mercedes-Benz Sprinter Van 2012": 165,
+    "Mitsubishi Lancer Sedan 2012": 166,
+    "Nissan 240SX Coupe 1998": 170,
+    "Nissan Juke Hatchback 2012": 169,
+    "Nissan Leaf Hatchback 2012": 167,
+    "Nissan NV Passenger Van 2012": 168,
+    "Plymouth Neon Coupe 1999": 171,
+    "Porsche Panamera Sedan 2012": 172,
+    "Ram C/V Cargo Van Minivan 2012": 173,
+    "Rolls-Royce Ghost Sedan 2012": 175,
+    "Rolls-Royce Phantom Drophead Coupe Convertible 2012": 174,
+    "Rolls-Royce Phantom Sedan 2012": 176,
+    "Scion xD Hatchback 2012": 177,
+    "Spyker C8 Convertible 2009": 178,
+    "Spyker C8 Coupe 2009": 179,
+    "Suzuki Aerio Sedan 2007": 180,
+    "Suzuki Kizashi Sedan 2012": 181,
+    "Suzuki SX4 Hatchback 2012": 182,
+    "Suzuki SX4 Sedan 2012": 183,
+    "Tesla Model S Sedan 2012": 184,
+    "Toyota 4Runner SUV 2012": 188,
+    "Toyota Camry Sedan 2012": 186,
+    "Toyota Corolla Sedan 2012": 187,
+    "Toyota Sequoia SUV 2012": 185,
+    "Volkswagen Beetle Hatchback 2012": 191,
+    "Volkswagen Golf Hatchback 1991": 190,
+    "Volkswagen Golf Hatchback 2012": 189,
+    "Volvo 240 Sedan 1993": 193,
+    "Volvo C30 Hatchback 2012": 192,
+    "Volvo XC90 SUV 2007": 194,
+    "smart fortwo Convertible 2012": 195
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet18-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-stanford-cars-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/README.md b/resnet18-stanford-cars-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..b7c3e6503b92a0bdc1b791701ac48cd6b306515f
--- /dev/null
+++ b/resnet18-stanford-cars-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stanford-cars.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: stanford-cars
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: train
+type: transformers
+val_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: test
+```
+
diff --git a/resnet18-stanford-cars-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/config.json b/resnet18-stanford-cars-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..ea904dca37c3e1bd676cdab8c844dff369a4e286
--- /dev/null
+++ b/resnet18-stanford-cars-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,435 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "AM General Hummer SUV 2000",
+    "1": "Acura RL Sedan 2012",
+    "2": "Acura TL Sedan 2012",
+    "3": "Acura TL Type-S 2008",
+    "4": "Acura TSX Sedan 2012",
+    "5": "Acura Integra Type R 2001",
+    "6": "Acura ZDX Hatchback 2012",
+    "7": "Aston Martin V8 Vantage Convertible 2012",
+    "8": "Aston Martin V8 Vantage Coupe 2012",
+    "9": "Aston Martin Virage Convertible 2012",
+    "10": "Aston Martin Virage Coupe 2012",
+    "11": "Audi RS 4 Convertible 2008",
+    "12": "Audi A5 Coupe 2012",
+    "13": "Audi TTS Coupe 2012",
+    "14": "Audi R8 Coupe 2012",
+    "15": "Audi V8 Sedan 1994",
+    "16": "Audi 100 Sedan 1994",
+    "17": "Audi 100 Wagon 1994",
+    "18": "Audi TT Hatchback 2011",
+    "19": "Audi S6 Sedan 2011",
+    "20": "Audi S5 Convertible 2012",
+    "21": "Audi S5 Coupe 2012",
+    "22": "Audi S4 Sedan 2012",
+    "23": "Audi S4 Sedan 2007",
+    "24": "Audi TT RS Coupe 2012",
+    "25": "BMW ActiveHybrid 5 Sedan 2012",
+    "26": "BMW 1 Series Convertible 2012",
+    "27": "BMW 1 Series Coupe 2012",
+    "28": "BMW 3 Series Sedan 2012",
+    "29": "BMW 3 Series Wagon 2012",
+    "30": "BMW 6 Series Convertible 2007",
+    "31": "BMW X5 SUV 2007",
+    "32": "BMW X6 SUV 2012",
+    "33": "BMW M3 Coupe 2012",
+    "34": "BMW M5 Sedan 2010",
+    "35": "BMW M6 Convertible 2010",
+    "36": "BMW X3 SUV 2012",
+    "37": "BMW Z4 Convertible 2012",
+    "38": "Bentley Continental Supersports Conv. Convertible 2012",
+    "39": "Bentley Arnage Sedan 2009",
+    "40": "Bentley Mulsanne Sedan 2011",
+    "41": "Bentley Continental GT Coupe 2012",
+    "42": "Bentley Continental GT Coupe 2007",
+    "43": "Bentley Continental Flying Spur Sedan 2007",
+    "44": "Bugatti Veyron 16.4 Convertible 2009",
+    "45": "Bugatti Veyron 16.4 Coupe 2009",
+    "46": "Buick Regal GS 2012",
+    "47": "Buick Rainier SUV 2007",
+    "48": "Buick Verano Sedan 2012",
+    "49": "Buick Enclave SUV 2012",
+    "50": "Cadillac CTS-V Sedan 2012",
+    "51": "Cadillac SRX SUV 2012",
+    "52": "Cadillac Escalade EXT Crew Cab 2007",
+    "53": "Chevrolet Silverado 1500 Hybrid Crew Cab 2012",
+    "54": "Chevrolet Corvette Convertible 2012",
+    "55": "Chevrolet Corvette ZR1 2012",
+    "56": "Chevrolet Corvette Ron Fellows Edition Z06 2007",
+    "57": "Chevrolet Traverse SUV 2012",
+    "58": "Chevrolet Camaro Convertible 2012",
+    "59": "Chevrolet HHR SS 2010",
+    "60": "Chevrolet Impala Sedan 2007",
+    "61": "Chevrolet Tahoe Hybrid SUV 2012",
+    "62": "Chevrolet Sonic Sedan 2012",
+    "63": "Chevrolet Express Cargo Van 2007",
+    "64": "Chevrolet Avalanche Crew Cab 2012",
+    "65": "Chevrolet Cobalt SS 2010",
+    "66": "Chevrolet Malibu Hybrid Sedan 2010",
+    "67": "Chevrolet TrailBlazer SS 2009",
+    "68": "Chevrolet Silverado 2500HD Regular Cab 2012",
+    "69": "Chevrolet Silverado 1500 Classic Extended Cab 2007",
+    "70": "Chevrolet Express Van 2007",
+    "71": "Chevrolet Monte Carlo Coupe 2007",
+    "72": "Chevrolet Malibu Sedan 2007",
+    "73": "Chevrolet Silverado 1500 Extended Cab 2012",
+    "74": "Chevrolet Silverado 1500 Regular Cab 2012",
+    "75": "Chrysler Aspen SUV 2009",
+    "76": "Chrysler Sebring Convertible 2010",
+    "77": "Chrysler Town and Country Minivan 2012",
+    "78": "Chrysler 300 SRT-8 2010",
+    "79": "Chrysler Crossfire Convertible 2008",
+    "80": "Chrysler PT Cruiser Convertible 2008",
+    "81": "Daewoo Nubira Wagon 2002",
+    "82": "Dodge Caliber Wagon 2012",
+    "83": "Dodge Caliber Wagon 2007",
+    "84": "Dodge Caravan Minivan 1997",
+    "85": "Dodge Ram Pickup 3500 Crew Cab 2010",
+    "86": "Dodge Ram Pickup 3500 Quad Cab 2009",
+    "87": "Dodge Sprinter Cargo Van 2009",
+    "88": "Dodge Journey SUV 2012",
+    "89": "Dodge Dakota Crew Cab 2010",
+    "90": "Dodge Dakota Club Cab 2007",
+    "91": "Dodge Magnum Wagon 2008",
+    "92": "Dodge Challenger SRT8 2011",
+    "93": "Dodge Durango SUV 2012",
+    "94": "Dodge Durango SUV 2007",
+    "95": "Dodge Charger Sedan 2012",
+    "96": "Dodge Charger SRT-8 2009",
+    "97": "Eagle Talon Hatchback 1998",
+    "98": "FIAT 500 Abarth 2012",
+    "99": "FIAT 500 Convertible 2012",
+    "100": "Ferrari FF Coupe 2012",
+    "101": "Ferrari California Convertible 2012",
+    "102": "Ferrari 458 Italia Convertible 2012",
+    "103": "Ferrari 458 Italia Coupe 2012",
+    "104": "Fisker Karma Sedan 2012",
+    "105": "Ford F-450 Super Duty Crew Cab 2012",
+    "106": "Ford Mustang Convertible 2007",
+    "107": "Ford Freestar Minivan 2007",
+    "108": "Ford Expedition EL SUV 2009",
+    "109": "Ford Edge SUV 2012",
+    "110": "Ford Ranger SuperCab 2011",
+    "111": "Ford GT Coupe 2006",
+    "112": "Ford F-150 Regular Cab 2012",
+    "113": "Ford F-150 Regular Cab 2007",
+    "114": "Ford Focus Sedan 2007",
+    "115": "Ford E-Series Wagon Van 2012",
+    "116": "Ford Fiesta Sedan 2012",
+    "117": "GMC Terrain SUV 2012",
+    "118": "GMC Savana Van 2012",
+    "119": "GMC Yukon Hybrid SUV 2012",
+    "120": "GMC Acadia SUV 2012",
+    "121": "GMC Canyon Extended Cab 2012",
+    "122": "Geo Metro Convertible 1993",
+    "123": "HUMMER H3T Crew Cab 2010",
+    "124": "HUMMER H2 SUT Crew Cab 2009",
+    "125": "Honda Odyssey Minivan 2012",
+    "126": "Honda Odyssey Minivan 2007",
+    "127": "Honda Accord Coupe 2012",
+    "128": "Honda Accord Sedan 2012",
+    "129": "Hyundai Veloster Hatchback 2012",
+    "130": "Hyundai Santa Fe SUV 2012",
+    "131": "Hyundai Tucson SUV 2012",
+    "132": "Hyundai Veracruz SUV 2012",
+    "133": "Hyundai Sonata Hybrid Sedan 2012",
+    "134": "Hyundai Elantra Sedan 2007",
+    "135": "Hyundai Accent Sedan 2012",
+    "136": "Hyundai Genesis Sedan 2012",
+    "137": "Hyundai Sonata Sedan 2012",
+    "138": "Hyundai Elantra Touring Hatchback 2012",
+    "139": "Hyundai Azera Sedan 2012",
+    "140": "Infiniti G Coupe IPL 2012",
+    "141": "Infiniti QX56 SUV 2011",
+    "142": "Isuzu Ascender SUV 2008",
+    "143": "Jaguar XK XKR 2012",
+    "144": "Jeep Patriot SUV 2012",
+    "145": "Jeep Wrangler SUV 2012",
+    "146": "Jeep Liberty SUV 2012",
+    "147": "Jeep Grand Cherokee SUV 2012",
+    "148": "Jeep Compass SUV 2012",
+    "149": "Lamborghini Reventon Coupe 2008",
+    "150": "Lamborghini Aventador Coupe 2012",
+    "151": "Lamborghini Gallardo LP 570-4 Superleggera 2012",
+    "152": "Lamborghini Diablo Coupe 2001",
+    "153": "Land Rover Range Rover SUV 2012",
+    "154": "Land Rover LR2 SUV 2012",
+    "155": "Lincoln Town Car Sedan 2011",
+    "156": "MINI Cooper Roadster Convertible 2012",
+    "157": "Maybach Landaulet Convertible 2012",
+    "158": "Mazda Tribute SUV 2011",
+    "159": "McLaren MP4-12C Coupe 2012",
+    "160": "Mercedes-Benz 300-Class Convertible 1993",
+    "161": "Mercedes-Benz C-Class Sedan 2012",
+    "162": "Mercedes-Benz SL-Class Coupe 2009",
+    "163": "Mercedes-Benz E-Class Sedan 2012",
+    "164": "Mercedes-Benz S-Class Sedan 2012",
+    "165": "Mercedes-Benz Sprinter Van 2012",
+    "166": "Mitsubishi Lancer Sedan 2012",
+    "167": "Nissan Leaf Hatchback 2012",
+    "168": "Nissan NV Passenger Van 2012",
+    "169": "Nissan Juke Hatchback 2012",
+    "170": "Nissan 240SX Coupe 1998",
+    "171": "Plymouth Neon Coupe 1999",
+    "172": "Porsche Panamera Sedan 2012",
+    "173": "Ram C/V Cargo Van Minivan 2012",
+    "174": "Rolls-Royce Phantom Drophead Coupe Convertible 2012",
+    "175": "Rolls-Royce Ghost Sedan 2012",
+    "176": "Rolls-Royce Phantom Sedan 2012",
+    "177": "Scion xD Hatchback 2012",
+    "178": "Spyker C8 Convertible 2009",
+    "179": "Spyker C8 Coupe 2009",
+    "180": "Suzuki Aerio Sedan 2007",
+    "181": "Suzuki Kizashi Sedan 2012",
+    "182": "Suzuki SX4 Hatchback 2012",
+    "183": "Suzuki SX4 Sedan 2012",
+    "184": "Tesla Model S Sedan 2012",
+    "185": "Toyota Sequoia SUV 2012",
+    "186": "Toyota Camry Sedan 2012",
+    "187": "Toyota Corolla Sedan 2012",
+    "188": "Toyota 4Runner SUV 2012",
+    "189": "Volkswagen Golf Hatchback 2012",
+    "190": "Volkswagen Golf Hatchback 1991",
+    "191": "Volkswagen Beetle Hatchback 2012",
+    "192": "Volvo C30 Hatchback 2012",
+    "193": "Volvo 240 Sedan 1993",
+    "194": "Volvo XC90 SUV 2007",
+    "195": "smart fortwo Convertible 2012"
+  },
+  "label2id": {
+    "AM General Hummer SUV 2000": 0,
+    "Acura Integra Type R 2001": 5,
+    "Acura RL Sedan 2012": 1,
+    "Acura TL Sedan 2012": 2,
+    "Acura TL Type-S 2008": 3,
+    "Acura TSX Sedan 2012": 4,
+    "Acura ZDX Hatchback 2012": 6,
+    "Aston Martin V8 Vantage Convertible 2012": 7,
+    "Aston Martin V8 Vantage Coupe 2012": 8,
+    "Aston Martin Virage Convertible 2012": 9,
+    "Aston Martin Virage Coupe 2012": 10,
+    "Audi 100 Sedan 1994": 16,
+    "Audi 100 Wagon 1994": 17,
+    "Audi A5 Coupe 2012": 12,
+    "Audi R8 Coupe 2012": 14,
+    "Audi RS 4 Convertible 2008": 11,
+    "Audi S4 Sedan 2007": 23,
+    "Audi S4 Sedan 2012": 22,
+    "Audi S5 Convertible 2012": 20,
+    "Audi S5 Coupe 2012": 21,
+    "Audi S6 Sedan 2011": 19,
+    "Audi TT Hatchback 2011": 18,
+    "Audi TT RS Coupe 2012": 24,
+    "Audi TTS Coupe 2012": 13,
+    "Audi V8 Sedan 1994": 15,
+    "BMW 1 Series Convertible 2012": 26,
+    "BMW 1 Series Coupe 2012": 27,
+    "BMW 3 Series Sedan 2012": 28,
+    "BMW 3 Series Wagon 2012": 29,
+    "BMW 6 Series Convertible 2007": 30,
+    "BMW ActiveHybrid 5 Sedan 2012": 25,
+    "BMW M3 Coupe 2012": 33,
+    "BMW M5 Sedan 2010": 34,
+    "BMW M6 Convertible 2010": 35,
+    "BMW X3 SUV 2012": 36,
+    "BMW X5 SUV 2007": 31,
+    "BMW X6 SUV 2012": 32,
+    "BMW Z4 Convertible 2012": 37,
+    "Bentley Arnage Sedan 2009": 39,
+    "Bentley Continental Flying Spur Sedan 2007": 43,
+    "Bentley Continental GT Coupe 2007": 42,
+    "Bentley Continental GT Coupe 2012": 41,
+    "Bentley Continental Supersports Conv. Convertible 2012": 38,
+    "Bentley Mulsanne Sedan 2011": 40,
+    "Bugatti Veyron 16.4 Convertible 2009": 44,
+    "Bugatti Veyron 16.4 Coupe 2009": 45,
+    "Buick Enclave SUV 2012": 49,
+    "Buick Rainier SUV 2007": 47,
+    "Buick Regal GS 2012": 46,
+    "Buick Verano Sedan 2012": 48,
+    "Cadillac CTS-V Sedan 2012": 50,
+    "Cadillac Escalade EXT Crew Cab 2007": 52,
+    "Cadillac SRX SUV 2012": 51,
+    "Chevrolet Avalanche Crew Cab 2012": 64,
+    "Chevrolet Camaro Convertible 2012": 58,
+    "Chevrolet Cobalt SS 2010": 65,
+    "Chevrolet Corvette Convertible 2012": 54,
+    "Chevrolet Corvette Ron Fellows Edition Z06 2007": 56,
+    "Chevrolet Corvette ZR1 2012": 55,
+    "Chevrolet Express Cargo Van 2007": 63,
+    "Chevrolet Express Van 2007": 70,
+    "Chevrolet HHR SS 2010": 59,
+    "Chevrolet Impala Sedan 2007": 60,
+    "Chevrolet Malibu Hybrid Sedan 2010": 66,
+    "Chevrolet Malibu Sedan 2007": 72,
+    "Chevrolet Monte Carlo Coupe 2007": 71,
+    "Chevrolet Silverado 1500 Classic Extended Cab 2007": 69,
+    "Chevrolet Silverado 1500 Extended Cab 2012": 73,
+    "Chevrolet Silverado 1500 Hybrid Crew Cab 2012": 53,
+    "Chevrolet Silverado 1500 Regular Cab 2012": 74,
+    "Chevrolet Silverado 2500HD Regular Cab 2012": 68,
+    "Chevrolet Sonic Sedan 2012": 62,
+    "Chevrolet Tahoe Hybrid SUV 2012": 61,
+    "Chevrolet TrailBlazer SS 2009": 67,
+    "Chevrolet Traverse SUV 2012": 57,
+    "Chrysler 300 SRT-8 2010": 78,
+    "Chrysler Aspen SUV 2009": 75,
+    "Chrysler Crossfire Convertible 2008": 79,
+    "Chrysler PT Cruiser Convertible 2008": 80,
+    "Chrysler Sebring Convertible 2010": 76,
+    "Chrysler Town and Country Minivan 2012": 77,
+    "Daewoo Nubira Wagon 2002": 81,
+    "Dodge Caliber Wagon 2007": 83,
+    "Dodge Caliber Wagon 2012": 82,
+    "Dodge Caravan Minivan 1997": 84,
+    "Dodge Challenger SRT8 2011": 92,
+    "Dodge Charger SRT-8 2009": 96,
+    "Dodge Charger Sedan 2012": 95,
+    "Dodge Dakota Club Cab 2007": 90,
+    "Dodge Dakota Crew Cab 2010": 89,
+    "Dodge Durango SUV 2007": 94,
+    "Dodge Durango SUV 2012": 93,
+    "Dodge Journey SUV 2012": 88,
+    "Dodge Magnum Wagon 2008": 91,
+    "Dodge Ram Pickup 3500 Crew Cab 2010": 85,
+    "Dodge Ram Pickup 3500 Quad Cab 2009": 86,
+    "Dodge Sprinter Cargo Van 2009": 87,
+    "Eagle Talon Hatchback 1998": 97,
+    "FIAT 500 Abarth 2012": 98,
+    "FIAT 500 Convertible 2012": 99,
+    "Ferrari 458 Italia Convertible 2012": 102,
+    "Ferrari 458 Italia Coupe 2012": 103,
+    "Ferrari California Convertible 2012": 101,
+    "Ferrari FF Coupe 2012": 100,
+    "Fisker Karma Sedan 2012": 104,
+    "Ford E-Series Wagon Van 2012": 115,
+    "Ford Edge SUV 2012": 109,
+    "Ford Expedition EL SUV 2009": 108,
+    "Ford F-150 Regular Cab 2007": 113,
+    "Ford F-150 Regular Cab 2012": 112,
+    "Ford F-450 Super Duty Crew Cab 2012": 105,
+    "Ford Fiesta Sedan 2012": 116,
+    "Ford Focus Sedan 2007": 114,
+    "Ford Freestar Minivan 2007": 107,
+    "Ford GT Coupe 2006": 111,
+    "Ford Mustang Convertible 2007": 106,
+    "Ford Ranger SuperCab 2011": 110,
+    "GMC Acadia SUV 2012": 120,
+    "GMC Canyon Extended Cab 2012": 121,
+    "GMC Savana Van 2012": 118,
+    "GMC Terrain SUV 2012": 117,
+    "GMC Yukon Hybrid SUV 2012": 119,
+    "Geo Metro Convertible 1993": 122,
+    "HUMMER H2 SUT Crew Cab 2009": 124,
+    "HUMMER H3T Crew Cab 2010": 123,
+    "Honda Accord Coupe 2012": 127,
+    "Honda Accord Sedan 2012": 128,
+    "Honda Odyssey Minivan 2007": 126,
+    "Honda Odyssey Minivan 2012": 125,
+    "Hyundai Accent Sedan 2012": 135,
+    "Hyundai Azera Sedan 2012": 139,
+    "Hyundai Elantra Sedan 2007": 134,
+    "Hyundai Elantra Touring Hatchback 2012": 138,
+    "Hyundai Genesis Sedan 2012": 136,
+    "Hyundai Santa Fe SUV 2012": 130,
+    "Hyundai Sonata Hybrid Sedan 2012": 133,
+    "Hyundai Sonata Sedan 2012": 137,
+    "Hyundai Tucson SUV 2012": 131,
+    "Hyundai Veloster Hatchback 2012": 129,
+    "Hyundai Veracruz SUV 2012": 132,
+    "Infiniti G Coupe IPL 2012": 140,
+    "Infiniti QX56 SUV 2011": 141,
+    "Isuzu Ascender SUV 2008": 142,
+    "Jaguar XK XKR 2012": 143,
+    "Jeep Compass SUV 2012": 148,
+    "Jeep Grand Cherokee SUV 2012": 147,
+    "Jeep Liberty SUV 2012": 146,
+    "Jeep Patriot SUV 2012": 144,
+    "Jeep Wrangler SUV 2012": 145,
+    "Lamborghini Aventador Coupe 2012": 150,
+    "Lamborghini Diablo Coupe 2001": 152,
+    "Lamborghini Gallardo LP 570-4 Superleggera 2012": 151,
+    "Lamborghini Reventon Coupe 2008": 149,
+    "Land Rover LR2 SUV 2012": 154,
+    "Land Rover Range Rover SUV 2012": 153,
+    "Lincoln Town Car Sedan 2011": 155,
+    "MINI Cooper Roadster Convertible 2012": 156,
+    "Maybach Landaulet Convertible 2012": 157,
+    "Mazda Tribute SUV 2011": 158,
+    "McLaren MP4-12C Coupe 2012": 159,
+    "Mercedes-Benz 300-Class Convertible 1993": 160,
+    "Mercedes-Benz C-Class Sedan 2012": 161,
+    "Mercedes-Benz E-Class Sedan 2012": 163,
+    "Mercedes-Benz S-Class Sedan 2012": 164,
+    "Mercedes-Benz SL-Class Coupe 2009": 162,
+    "Mercedes-Benz Sprinter Van 2012": 165,
+    "Mitsubishi Lancer Sedan 2012": 166,
+    "Nissan 240SX Coupe 1998": 170,
+    "Nissan Juke Hatchback 2012": 169,
+    "Nissan Leaf Hatchback 2012": 167,
+    "Nissan NV Passenger Van 2012": 168,
+    "Plymouth Neon Coupe 1999": 171,
+    "Porsche Panamera Sedan 2012": 172,
+    "Ram C/V Cargo Van Minivan 2012": 173,
+    "Rolls-Royce Ghost Sedan 2012": 175,
+    "Rolls-Royce Phantom Drophead Coupe Convertible 2012": 174,
+    "Rolls-Royce Phantom Sedan 2012": 176,
+    "Scion xD Hatchback 2012": 177,
+    "Spyker C8 Convertible 2009": 178,
+    "Spyker C8 Coupe 2009": 179,
+    "Suzuki Aerio Sedan 2007": 180,
+    "Suzuki Kizashi Sedan 2012": 181,
+    "Suzuki SX4 Hatchback 2012": 182,
+    "Suzuki SX4 Sedan 2012": 183,
+    "Tesla Model S Sedan 2012": 184,
+    "Toyota 4Runner SUV 2012": 188,
+    "Toyota Camry Sedan 2012": 186,
+    "Toyota Corolla Sedan 2012": 187,
+    "Toyota Sequoia SUV 2012": 185,
+    "Volkswagen Beetle Hatchback 2012": 191,
+    "Volkswagen Golf Hatchback 1991": 190,
+    "Volkswagen Golf Hatchback 2012": 189,
+    "Volvo 240 Sedan 1993": 193,
+    "Volvo C30 Hatchback 2012": 192,
+    "Volvo XC90 SUV 2007": 194,
+    "smart fortwo Convertible 2012": 195
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-stanford-cars-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet18-stanford-cars-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-stanford-cars-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-stanford-cars-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/README.md b/resnet18-stanford-cars-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..49ccebcffeea8d03df7419e1c1de629573b7a0b0
--- /dev/null
+++ b/resnet18-stanford-cars-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stanford-cars.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: stanford-cars
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: train
+type: transformers
+val_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: test
+```
+
diff --git a/resnet18-stanford-cars-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/config.json b/resnet18-stanford-cars-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..ea904dca37c3e1bd676cdab8c844dff369a4e286
--- /dev/null
+++ b/resnet18-stanford-cars-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,435 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "AM General Hummer SUV 2000",
+    "1": "Acura RL Sedan 2012",
+    "2": "Acura TL Sedan 2012",
+    "3": "Acura TL Type-S 2008",
+    "4": "Acura TSX Sedan 2012",
+    "5": "Acura Integra Type R 2001",
+    "6": "Acura ZDX Hatchback 2012",
+    "7": "Aston Martin V8 Vantage Convertible 2012",
+    "8": "Aston Martin V8 Vantage Coupe 2012",
+    "9": "Aston Martin Virage Convertible 2012",
+    "10": "Aston Martin Virage Coupe 2012",
+    "11": "Audi RS 4 Convertible 2008",
+    "12": "Audi A5 Coupe 2012",
+    "13": "Audi TTS Coupe 2012",
+    "14": "Audi R8 Coupe 2012",
+    "15": "Audi V8 Sedan 1994",
+    "16": "Audi 100 Sedan 1994",
+    "17": "Audi 100 Wagon 1994",
+    "18": "Audi TT Hatchback 2011",
+    "19": "Audi S6 Sedan 2011",
+    "20": "Audi S5 Convertible 2012",
+    "21": "Audi S5 Coupe 2012",
+    "22": "Audi S4 Sedan 2012",
+    "23": "Audi S4 Sedan 2007",
+    "24": "Audi TT RS Coupe 2012",
+    "25": "BMW ActiveHybrid 5 Sedan 2012",
+    "26": "BMW 1 Series Convertible 2012",
+    "27": "BMW 1 Series Coupe 2012",
+    "28": "BMW 3 Series Sedan 2012",
+    "29": "BMW 3 Series Wagon 2012",
+    "30": "BMW 6 Series Convertible 2007",
+    "31": "BMW X5 SUV 2007",
+    "32": "BMW X6 SUV 2012",
+    "33": "BMW M3 Coupe 2012",
+    "34": "BMW M5 Sedan 2010",
+    "35": "BMW M6 Convertible 2010",
+    "36": "BMW X3 SUV 2012",
+    "37": "BMW Z4 Convertible 2012",
+    "38": "Bentley Continental Supersports Conv. Convertible 2012",
+    "39": "Bentley Arnage Sedan 2009",
+    "40": "Bentley Mulsanne Sedan 2011",
+    "41": "Bentley Continental GT Coupe 2012",
+    "42": "Bentley Continental GT Coupe 2007",
+    "43": "Bentley Continental Flying Spur Sedan 2007",
+    "44": "Bugatti Veyron 16.4 Convertible 2009",
+    "45": "Bugatti Veyron 16.4 Coupe 2009",
+    "46": "Buick Regal GS 2012",
+    "47": "Buick Rainier SUV 2007",
+    "48": "Buick Verano Sedan 2012",
+    "49": "Buick Enclave SUV 2012",
+    "50": "Cadillac CTS-V Sedan 2012",
+    "51": "Cadillac SRX SUV 2012",
+    "52": "Cadillac Escalade EXT Crew Cab 2007",
+    "53": "Chevrolet Silverado 1500 Hybrid Crew Cab 2012",
+    "54": "Chevrolet Corvette Convertible 2012",
+    "55": "Chevrolet Corvette ZR1 2012",
+    "56": "Chevrolet Corvette Ron Fellows Edition Z06 2007",
+    "57": "Chevrolet Traverse SUV 2012",
+    "58": "Chevrolet Camaro Convertible 2012",
+    "59": "Chevrolet HHR SS 2010",
+    "60": "Chevrolet Impala Sedan 2007",
+    "61": "Chevrolet Tahoe Hybrid SUV 2012",
+    "62": "Chevrolet Sonic Sedan 2012",
+    "63": "Chevrolet Express Cargo Van 2007",
+    "64": "Chevrolet Avalanche Crew Cab 2012",
+    "65": "Chevrolet Cobalt SS 2010",
+    "66": "Chevrolet Malibu Hybrid Sedan 2010",
+    "67": "Chevrolet TrailBlazer SS 2009",
+    "68": "Chevrolet Silverado 2500HD Regular Cab 2012",
+    "69": "Chevrolet Silverado 1500 Classic Extended Cab 2007",
+    "70": "Chevrolet Express Van 2007",
+    "71": "Chevrolet Monte Carlo Coupe 2007",
+    "72": "Chevrolet Malibu Sedan 2007",
+    "73": "Chevrolet Silverado 1500 Extended Cab 2012",
+    "74": "Chevrolet Silverado 1500 Regular Cab 2012",
+    "75": "Chrysler Aspen SUV 2009",
+    "76": "Chrysler Sebring Convertible 2010",
+    "77": "Chrysler Town and Country Minivan 2012",
+    "78": "Chrysler 300 SRT-8 2010",
+    "79": "Chrysler Crossfire Convertible 2008",
+    "80": "Chrysler PT Cruiser Convertible 2008",
+    "81": "Daewoo Nubira Wagon 2002",
+    "82": "Dodge Caliber Wagon 2012",
+    "83": "Dodge Caliber Wagon 2007",
+    "84": "Dodge Caravan Minivan 1997",
+    "85": "Dodge Ram Pickup 3500 Crew Cab 2010",
+    "86": "Dodge Ram Pickup 3500 Quad Cab 2009",
+    "87": "Dodge Sprinter Cargo Van 2009",
+    "88": "Dodge Journey SUV 2012",
+    "89": "Dodge Dakota Crew Cab 2010",
+    "90": "Dodge Dakota Club Cab 2007",
+    "91": "Dodge Magnum Wagon 2008",
+    "92": "Dodge Challenger SRT8 2011",
+    "93": "Dodge Durango SUV 2012",
+    "94": "Dodge Durango SUV 2007",
+    "95": "Dodge Charger Sedan 2012",
+    "96": "Dodge Charger SRT-8 2009",
+    "97": "Eagle Talon Hatchback 1998",
+    "98": "FIAT 500 Abarth 2012",
+    "99": "FIAT 500 Convertible 2012",
+    "100": "Ferrari FF Coupe 2012",
+    "101": "Ferrari California Convertible 2012",
+    "102": "Ferrari 458 Italia Convertible 2012",
+    "103": "Ferrari 458 Italia Coupe 2012",
+    "104": "Fisker Karma Sedan 2012",
+    "105": "Ford F-450 Super Duty Crew Cab 2012",
+    "106": "Ford Mustang Convertible 2007",
+    "107": "Ford Freestar Minivan 2007",
+    "108": "Ford Expedition EL SUV 2009",
+    "109": "Ford Edge SUV 2012",
+    "110": "Ford Ranger SuperCab 2011",
+    "111": "Ford GT Coupe 2006",
+    "112": "Ford F-150 Regular Cab 2012",
+    "113": "Ford F-150 Regular Cab 2007",
+    "114": "Ford Focus Sedan 2007",
+    "115": "Ford E-Series Wagon Van 2012",
+    "116": "Ford Fiesta Sedan 2012",
+    "117": "GMC Terrain SUV 2012",
+    "118": "GMC Savana Van 2012",
+    "119": "GMC Yukon Hybrid SUV 2012",
+    "120": "GMC Acadia SUV 2012",
+    "121": "GMC Canyon Extended Cab 2012",
+    "122": "Geo Metro Convertible 1993",
+    "123": "HUMMER H3T Crew Cab 2010",
+    "124": "HUMMER H2 SUT Crew Cab 2009",
+    "125": "Honda Odyssey Minivan 2012",
+    "126": "Honda Odyssey Minivan 2007",
+    "127": "Honda Accord Coupe 2012",
+    "128": "Honda Accord Sedan 2012",
+    "129": "Hyundai Veloster Hatchback 2012",
+    "130": "Hyundai Santa Fe SUV 2012",
+    "131": "Hyundai Tucson SUV 2012",
+    "132": "Hyundai Veracruz SUV 2012",
+    "133": "Hyundai Sonata Hybrid Sedan 2012",
+    "134": "Hyundai Elantra Sedan 2007",
+    "135": "Hyundai Accent Sedan 2012",
+    "136": "Hyundai Genesis Sedan 2012",
+    "137": "Hyundai Sonata Sedan 2012",
+    "138": "Hyundai Elantra Touring Hatchback 2012",
+    "139": "Hyundai Azera Sedan 2012",
+    "140": "Infiniti G Coupe IPL 2012",
+    "141": "Infiniti QX56 SUV 2011",
+    "142": "Isuzu Ascender SUV 2008",
+    "143": "Jaguar XK XKR 2012",
+    "144": "Jeep Patriot SUV 2012",
+    "145": "Jeep Wrangler SUV 2012",
+    "146": "Jeep Liberty SUV 2012",
+    "147": "Jeep Grand Cherokee SUV 2012",
+    "148": "Jeep Compass SUV 2012",
+    "149": "Lamborghini Reventon Coupe 2008",
+    "150": "Lamborghini Aventador Coupe 2012",
+    "151": "Lamborghini Gallardo LP 570-4 Superleggera 2012",
+    "152": "Lamborghini Diablo Coupe 2001",
+    "153": "Land Rover Range Rover SUV 2012",
+    "154": "Land Rover LR2 SUV 2012",
+    "155": "Lincoln Town Car Sedan 2011",
+    "156": "MINI Cooper Roadster Convertible 2012",
+    "157": "Maybach Landaulet Convertible 2012",
+    "158": "Mazda Tribute SUV 2011",
+    "159": "McLaren MP4-12C Coupe 2012",
+    "160": "Mercedes-Benz 300-Class Convertible 1993",
+    "161": "Mercedes-Benz C-Class Sedan 2012",
+    "162": "Mercedes-Benz SL-Class Coupe 2009",
+    "163": "Mercedes-Benz E-Class Sedan 2012",
+    "164": "Mercedes-Benz S-Class Sedan 2012",
+    "165": "Mercedes-Benz Sprinter Van 2012",
+    "166": "Mitsubishi Lancer Sedan 2012",
+    "167": "Nissan Leaf Hatchback 2012",
+    "168": "Nissan NV Passenger Van 2012",
+    "169": "Nissan Juke Hatchback 2012",
+    "170": "Nissan 240SX Coupe 1998",
+    "171": "Plymouth Neon Coupe 1999",
+    "172": "Porsche Panamera Sedan 2012",
+    "173": "Ram C/V Cargo Van Minivan 2012",
+    "174": "Rolls-Royce Phantom Drophead Coupe Convertible 2012",
+    "175": "Rolls-Royce Ghost Sedan 2012",
+    "176": "Rolls-Royce Phantom Sedan 2012",
+    "177": "Scion xD Hatchback 2012",
+    "178": "Spyker C8 Convertible 2009",
+    "179": "Spyker C8 Coupe 2009",
+    "180": "Suzuki Aerio Sedan 2007",
+    "181": "Suzuki Kizashi Sedan 2012",
+    "182": "Suzuki SX4 Hatchback 2012",
+    "183": "Suzuki SX4 Sedan 2012",
+    "184": "Tesla Model S Sedan 2012",
+    "185": "Toyota Sequoia SUV 2012",
+    "186": "Toyota Camry Sedan 2012",
+    "187": "Toyota Corolla Sedan 2012",
+    "188": "Toyota 4Runner SUV 2012",
+    "189": "Volkswagen Golf Hatchback 2012",
+    "190": "Volkswagen Golf Hatchback 1991",
+    "191": "Volkswagen Beetle Hatchback 2012",
+    "192": "Volvo C30 Hatchback 2012",
+    "193": "Volvo 240 Sedan 1993",
+    "194": "Volvo XC90 SUV 2007",
+    "195": "smart fortwo Convertible 2012"
+  },
+  "label2id": {
+    "AM General Hummer SUV 2000": 0,
+    "Acura Integra Type R 2001": 5,
+    "Acura RL Sedan 2012": 1,
+    "Acura TL Sedan 2012": 2,
+    "Acura TL Type-S 2008": 3,
+    "Acura TSX Sedan 2012": 4,
+    "Acura ZDX Hatchback 2012": 6,
+    "Aston Martin V8 Vantage Convertible 2012": 7,
+    "Aston Martin V8 Vantage Coupe 2012": 8,
+    "Aston Martin Virage Convertible 2012": 9,
+    "Aston Martin Virage Coupe 2012": 10,
+    "Audi 100 Sedan 1994": 16,
+    "Audi 100 Wagon 1994": 17,
+    "Audi A5 Coupe 2012": 12,
+    "Audi R8 Coupe 2012": 14,
+    "Audi RS 4 Convertible 2008": 11,
+    "Audi S4 Sedan 2007": 23,
+    "Audi S4 Sedan 2012": 22,
+    "Audi S5 Convertible 2012": 20,
+    "Audi S5 Coupe 2012": 21,
+    "Audi S6 Sedan 2011": 19,
+    "Audi TT Hatchback 2011": 18,
+    "Audi TT RS Coupe 2012": 24,
+    "Audi TTS Coupe 2012": 13,
+    "Audi V8 Sedan 1994": 15,
+    "BMW 1 Series Convertible 2012": 26,
+    "BMW 1 Series Coupe 2012": 27,
+    "BMW 3 Series Sedan 2012": 28,
+    "BMW 3 Series Wagon 2012": 29,
+    "BMW 6 Series Convertible 2007": 30,
+    "BMW ActiveHybrid 5 Sedan 2012": 25,
+    "BMW M3 Coupe 2012": 33,
+    "BMW M5 Sedan 2010": 34,
+    "BMW M6 Convertible 2010": 35,
+    "BMW X3 SUV 2012": 36,
+    "BMW X5 SUV 2007": 31,
+    "BMW X6 SUV 2012": 32,
+    "BMW Z4 Convertible 2012": 37,
+    "Bentley Arnage Sedan 2009": 39,
+    "Bentley Continental Flying Spur Sedan 2007": 43,
+    "Bentley Continental GT Coupe 2007": 42,
+    "Bentley Continental GT Coupe 2012": 41,
+    "Bentley Continental Supersports Conv. Convertible 2012": 38,
+    "Bentley Mulsanne Sedan 2011": 40,
+    "Bugatti Veyron 16.4 Convertible 2009": 44,
+    "Bugatti Veyron 16.4 Coupe 2009": 45,
+    "Buick Enclave SUV 2012": 49,
+    "Buick Rainier SUV 2007": 47,
+    "Buick Regal GS 2012": 46,
+    "Buick Verano Sedan 2012": 48,
+    "Cadillac CTS-V Sedan 2012": 50,
+    "Cadillac Escalade EXT Crew Cab 2007": 52,
+    "Cadillac SRX SUV 2012": 51,
+    "Chevrolet Avalanche Crew Cab 2012": 64,
+    "Chevrolet Camaro Convertible 2012": 58,
+    "Chevrolet Cobalt SS 2010": 65,
+    "Chevrolet Corvette Convertible 2012": 54,
+    "Chevrolet Corvette Ron Fellows Edition Z06 2007": 56,
+    "Chevrolet Corvette ZR1 2012": 55,
+    "Chevrolet Express Cargo Van 2007": 63,
+    "Chevrolet Express Van 2007": 70,
+    "Chevrolet HHR SS 2010": 59,
+    "Chevrolet Impala Sedan 2007": 60,
+    "Chevrolet Malibu Hybrid Sedan 2010": 66,
+    "Chevrolet Malibu Sedan 2007": 72,
+    "Chevrolet Monte Carlo Coupe 2007": 71,
+    "Chevrolet Silverado 1500 Classic Extended Cab 2007": 69,
+    "Chevrolet Silverado 1500 Extended Cab 2012": 73,
+    "Chevrolet Silverado 1500 Hybrid Crew Cab 2012": 53,
+    "Chevrolet Silverado 1500 Regular Cab 2012": 74,
+    "Chevrolet Silverado 2500HD Regular Cab 2012": 68,
+    "Chevrolet Sonic Sedan 2012": 62,
+    "Chevrolet Tahoe Hybrid SUV 2012": 61,
+    "Chevrolet TrailBlazer SS 2009": 67,
+    "Chevrolet Traverse SUV 2012": 57,
+    "Chrysler 300 SRT-8 2010": 78,
+    "Chrysler Aspen SUV 2009": 75,
+    "Chrysler Crossfire Convertible 2008": 79,
+    "Chrysler PT Cruiser Convertible 2008": 80,
+    "Chrysler Sebring Convertible 2010": 76,
+    "Chrysler Town and Country Minivan 2012": 77,
+    "Daewoo Nubira Wagon 2002": 81,
+    "Dodge Caliber Wagon 2007": 83,
+    "Dodge Caliber Wagon 2012": 82,
+    "Dodge Caravan Minivan 1997": 84,
+    "Dodge Challenger SRT8 2011": 92,
+    "Dodge Charger SRT-8 2009": 96,
+    "Dodge Charger Sedan 2012": 95,
+    "Dodge Dakota Club Cab 2007": 90,
+    "Dodge Dakota Crew Cab 2010": 89,
+    "Dodge Durango SUV 2007": 94,
+    "Dodge Durango SUV 2012": 93,
+    "Dodge Journey SUV 2012": 88,
+    "Dodge Magnum Wagon 2008": 91,
+    "Dodge Ram Pickup 3500 Crew Cab 2010": 85,
+    "Dodge Ram Pickup 3500 Quad Cab 2009": 86,
+    "Dodge Sprinter Cargo Van 2009": 87,
+    "Eagle Talon Hatchback 1998": 97,
+    "FIAT 500 Abarth 2012": 98,
+    "FIAT 500 Convertible 2012": 99,
+    "Ferrari 458 Italia Convertible 2012": 102,
+    "Ferrari 458 Italia Coupe 2012": 103,
+    "Ferrari California Convertible 2012": 101,
+    "Ferrari FF Coupe 2012": 100,
+    "Fisker Karma Sedan 2012": 104,
+    "Ford E-Series Wagon Van 2012": 115,
+    "Ford Edge SUV 2012": 109,
+    "Ford Expedition EL SUV 2009": 108,
+    "Ford F-150 Regular Cab 2007": 113,
+    "Ford F-150 Regular Cab 2012": 112,
+    "Ford F-450 Super Duty Crew Cab 2012": 105,
+    "Ford Fiesta Sedan 2012": 116,
+    "Ford Focus Sedan 2007": 114,
+    "Ford Freestar Minivan 2007": 107,
+    "Ford GT Coupe 2006": 111,
+    "Ford Mustang Convertible 2007": 106,
+    "Ford Ranger SuperCab 2011": 110,
+    "GMC Acadia SUV 2012": 120,
+    "GMC Canyon Extended Cab 2012": 121,
+    "GMC Savana Van 2012": 118,
+    "GMC Terrain SUV 2012": 117,
+    "GMC Yukon Hybrid SUV 2012": 119,
+    "Geo Metro Convertible 1993": 122,
+    "HUMMER H2 SUT Crew Cab 2009": 124,
+    "HUMMER H3T Crew Cab 2010": 123,
+    "Honda Accord Coupe 2012": 127,
+    "Honda Accord Sedan 2012": 128,
+    "Honda Odyssey Minivan 2007": 126,
+    "Honda Odyssey Minivan 2012": 125,
+    "Hyundai Accent Sedan 2012": 135,
+    "Hyundai Azera Sedan 2012": 139,
+    "Hyundai Elantra Sedan 2007": 134,
+    "Hyundai Elantra Touring Hatchback 2012": 138,
+    "Hyundai Genesis Sedan 2012": 136,
+    "Hyundai Santa Fe SUV 2012": 130,
+    "Hyundai Sonata Hybrid Sedan 2012": 133,
+    "Hyundai Sonata Sedan 2012": 137,
+    "Hyundai Tucson SUV 2012": 131,
+    "Hyundai Veloster Hatchback 2012": 129,
+    "Hyundai Veracruz SUV 2012": 132,
+    "Infiniti G Coupe IPL 2012": 140,
+    "Infiniti QX56 SUV 2011": 141,
+    "Isuzu Ascender SUV 2008": 142,
+    "Jaguar XK XKR 2012": 143,
+    "Jeep Compass SUV 2012": 148,
+    "Jeep Grand Cherokee SUV 2012": 147,
+    "Jeep Liberty SUV 2012": 146,
+    "Jeep Patriot SUV 2012": 144,
+    "Jeep Wrangler SUV 2012": 145,
+    "Lamborghini Aventador Coupe 2012": 150,
+    "Lamborghini Diablo Coupe 2001": 152,
+    "Lamborghini Gallardo LP 570-4 Superleggera 2012": 151,
+    "Lamborghini Reventon Coupe 2008": 149,
+    "Land Rover LR2 SUV 2012": 154,
+    "Land Rover Range Rover SUV 2012": 153,
+    "Lincoln Town Car Sedan 2011": 155,
+    "MINI Cooper Roadster Convertible 2012": 156,
+    "Maybach Landaulet Convertible 2012": 157,
+    "Mazda Tribute SUV 2011": 158,
+    "McLaren MP4-12C Coupe 2012": 159,
+    "Mercedes-Benz 300-Class Convertible 1993": 160,
+    "Mercedes-Benz C-Class Sedan 2012": 161,
+    "Mercedes-Benz E-Class Sedan 2012": 163,
+    "Mercedes-Benz S-Class Sedan 2012": 164,
+    "Mercedes-Benz SL-Class Coupe 2009": 162,
+    "Mercedes-Benz Sprinter Van 2012": 165,
+    "Mitsubishi Lancer Sedan 2012": 166,
+    "Nissan 240SX Coupe 1998": 170,
+    "Nissan Juke Hatchback 2012": 169,
+    "Nissan Leaf Hatchback 2012": 167,
+    "Nissan NV Passenger Van 2012": 168,
+    "Plymouth Neon Coupe 1999": 171,
+    "Porsche Panamera Sedan 2012": 172,
+    "Ram C/V Cargo Van Minivan 2012": 173,
+    "Rolls-Royce Ghost Sedan 2012": 175,
+    "Rolls-Royce Phantom Drophead Coupe Convertible 2012": 174,
+    "Rolls-Royce Phantom Sedan 2012": 176,
+    "Scion xD Hatchback 2012": 177,
+    "Spyker C8 Convertible 2009": 178,
+    "Spyker C8 Coupe 2009": 179,
+    "Suzuki Aerio Sedan 2007": 180,
+    "Suzuki Kizashi Sedan 2012": 181,
+    "Suzuki SX4 Hatchback 2012": 182,
+    "Suzuki SX4 Sedan 2012": 183,
+    "Tesla Model S Sedan 2012": 184,
+    "Toyota 4Runner SUV 2012": 188,
+    "Toyota Camry Sedan 2012": 186,
+    "Toyota Corolla Sedan 2012": 187,
+    "Toyota Sequoia SUV 2012": 185,
+    "Volkswagen Beetle Hatchback 2012": 191,
+    "Volkswagen Golf Hatchback 1991": 190,
+    "Volkswagen Golf Hatchback 2012": 189,
+    "Volvo 240 Sedan 1993": 193,
+    "Volvo C30 Hatchback 2012": 192,
+    "Volvo XC90 SUV 2007": 194,
+    "smart fortwo Convertible 2012": 195
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-stanford-cars-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet18-stanford-cars-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-stanford-cars-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-stanford-cars-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/README.md b/resnet18-stanford-cars-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..5ade4bde497611f306a95dbea6eb954f28ac5ee8
--- /dev/null
+++ b/resnet18-stanford-cars-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stanford-cars.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: stanford-cars
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: train
+type: transformers
+val_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: test
+```
+
diff --git a/resnet18-stanford-cars-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/config.json b/resnet18-stanford-cars-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..ea904dca37c3e1bd676cdab8c844dff369a4e286
--- /dev/null
+++ b/resnet18-stanford-cars-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/config.json
@@ -0,0 +1,435 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "AM General Hummer SUV 2000",
+    "1": "Acura RL Sedan 2012",
+    "2": "Acura TL Sedan 2012",
+    "3": "Acura TL Type-S 2008",
+    "4": "Acura TSX Sedan 2012",
+    "5": "Acura Integra Type R 2001",
+    "6": "Acura ZDX Hatchback 2012",
+    "7": "Aston Martin V8 Vantage Convertible 2012",
+    "8": "Aston Martin V8 Vantage Coupe 2012",
+    "9": "Aston Martin Virage Convertible 2012",
+    "10": "Aston Martin Virage Coupe 2012",
+    "11": "Audi RS 4 Convertible 2008",
+    "12": "Audi A5 Coupe 2012",
+    "13": "Audi TTS Coupe 2012",
+    "14": "Audi R8 Coupe 2012",
+    "15": "Audi V8 Sedan 1994",
+    "16": "Audi 100 Sedan 1994",
+    "17": "Audi 100 Wagon 1994",
+    "18": "Audi TT Hatchback 2011",
+    "19": "Audi S6 Sedan 2011",
+    "20": "Audi S5 Convertible 2012",
+    "21": "Audi S5 Coupe 2012",
+    "22": "Audi S4 Sedan 2012",
+    "23": "Audi S4 Sedan 2007",
+    "24": "Audi TT RS Coupe 2012",
+    "25": "BMW ActiveHybrid 5 Sedan 2012",
+    "26": "BMW 1 Series Convertible 2012",
+    "27": "BMW 1 Series Coupe 2012",
+    "28": "BMW 3 Series Sedan 2012",
+    "29": "BMW 3 Series Wagon 2012",
+    "30": "BMW 6 Series Convertible 2007",
+    "31": "BMW X5 SUV 2007",
+    "32": "BMW X6 SUV 2012",
+    "33": "BMW M3 Coupe 2012",
+    "34": "BMW M5 Sedan 2010",
+    "35": "BMW M6 Convertible 2010",
+    "36": "BMW X3 SUV 2012",
+    "37": "BMW Z4 Convertible 2012",
+    "38": "Bentley Continental Supersports Conv. Convertible 2012",
+    "39": "Bentley Arnage Sedan 2009",
+    "40": "Bentley Mulsanne Sedan 2011",
+    "41": "Bentley Continental GT Coupe 2012",
+    "42": "Bentley Continental GT Coupe 2007",
+    "43": "Bentley Continental Flying Spur Sedan 2007",
+    "44": "Bugatti Veyron 16.4 Convertible 2009",
+    "45": "Bugatti Veyron 16.4 Coupe 2009",
+    "46": "Buick Regal GS 2012",
+    "47": "Buick Rainier SUV 2007",
+    "48": "Buick Verano Sedan 2012",
+    "49": "Buick Enclave SUV 2012",
+    "50": "Cadillac CTS-V Sedan 2012",
+    "51": "Cadillac SRX SUV 2012",
+    "52": "Cadillac Escalade EXT Crew Cab 2007",
+    "53": "Chevrolet Silverado 1500 Hybrid Crew Cab 2012",
+    "54": "Chevrolet Corvette Convertible 2012",
+    "55": "Chevrolet Corvette ZR1 2012",
+    "56": "Chevrolet Corvette Ron Fellows Edition Z06 2007",
+    "57": "Chevrolet Traverse SUV 2012",
+    "58": "Chevrolet Camaro Convertible 2012",
+    "59": "Chevrolet HHR SS 2010",
+    "60": "Chevrolet Impala Sedan 2007",
+    "61": "Chevrolet Tahoe Hybrid SUV 2012",
+    "62": "Chevrolet Sonic Sedan 2012",
+    "63": "Chevrolet Express Cargo Van 2007",
+    "64": "Chevrolet Avalanche Crew Cab 2012",
+    "65": "Chevrolet Cobalt SS 2010",
+    "66": "Chevrolet Malibu Hybrid Sedan 2010",
+    "67": "Chevrolet TrailBlazer SS 2009",
+    "68": "Chevrolet Silverado 2500HD Regular Cab 2012",
+    "69": "Chevrolet Silverado 1500 Classic Extended Cab 2007",
+    "70": "Chevrolet Express Van 2007",
+    "71": "Chevrolet Monte Carlo Coupe 2007",
+    "72": "Chevrolet Malibu Sedan 2007",
+    "73": "Chevrolet Silverado 1500 Extended Cab 2012",
+    "74": "Chevrolet Silverado 1500 Regular Cab 2012",
+    "75": "Chrysler Aspen SUV 2009",
+    "76": "Chrysler Sebring Convertible 2010",
+    "77": "Chrysler Town and Country Minivan 2012",
+    "78": "Chrysler 300 SRT-8 2010",
+    "79": "Chrysler Crossfire Convertible 2008",
+    "80": "Chrysler PT Cruiser Convertible 2008",
+    "81": "Daewoo Nubira Wagon 2002",
+    "82": "Dodge Caliber Wagon 2012",
+    "83": "Dodge Caliber Wagon 2007",
+    "84": "Dodge Caravan Minivan 1997",
+    "85": "Dodge Ram Pickup 3500 Crew Cab 2010",
+    "86": "Dodge Ram Pickup 3500 Quad Cab 2009",
+    "87": "Dodge Sprinter Cargo Van 2009",
+    "88": "Dodge Journey SUV 2012",
+    "89": "Dodge Dakota Crew Cab 2010",
+    "90": "Dodge Dakota Club Cab 2007",
+    "91": "Dodge Magnum Wagon 2008",
+    "92": "Dodge Challenger SRT8 2011",
+    "93": "Dodge Durango SUV 2012",
+    "94": "Dodge Durango SUV 2007",
+    "95": "Dodge Charger Sedan 2012",
+    "96": "Dodge Charger SRT-8 2009",
+    "97": "Eagle Talon Hatchback 1998",
+    "98": "FIAT 500 Abarth 2012",
+    "99": "FIAT 500 Convertible 2012",
+    "100": "Ferrari FF Coupe 2012",
+    "101": "Ferrari California Convertible 2012",
+    "102": "Ferrari 458 Italia Convertible 2012",
+    "103": "Ferrari 458 Italia Coupe 2012",
+    "104": "Fisker Karma Sedan 2012",
+    "105": "Ford F-450 Super Duty Crew Cab 2012",
+    "106": "Ford Mustang Convertible 2007",
+    "107": "Ford Freestar Minivan 2007",
+    "108": "Ford Expedition EL SUV 2009",
+    "109": "Ford Edge SUV 2012",
+    "110": "Ford Ranger SuperCab 2011",
+    "111": "Ford GT Coupe 2006",
+    "112": "Ford F-150 Regular Cab 2012",
+    "113": "Ford F-150 Regular Cab 2007",
+    "114": "Ford Focus Sedan 2007",
+    "115": "Ford E-Series Wagon Van 2012",
+    "116": "Ford Fiesta Sedan 2012",
+    "117": "GMC Terrain SUV 2012",
+    "118": "GMC Savana Van 2012",
+    "119": "GMC Yukon Hybrid SUV 2012",
+    "120": "GMC Acadia SUV 2012",
+    "121": "GMC Canyon Extended Cab 2012",
+    "122": "Geo Metro Convertible 1993",
+    "123": "HUMMER H3T Crew Cab 2010",
+    "124": "HUMMER H2 SUT Crew Cab 2009",
+    "125": "Honda Odyssey Minivan 2012",
+    "126": "Honda Odyssey Minivan 2007",
+    "127": "Honda Accord Coupe 2012",
+    "128": "Honda Accord Sedan 2012",
+    "129": "Hyundai Veloster Hatchback 2012",
+    "130": "Hyundai Santa Fe SUV 2012",
+    "131": "Hyundai Tucson SUV 2012",
+    "132": "Hyundai Veracruz SUV 2012",
+    "133": "Hyundai Sonata Hybrid Sedan 2012",
+    "134": "Hyundai Elantra Sedan 2007",
+    "135": "Hyundai Accent Sedan 2012",
+    "136": "Hyundai Genesis Sedan 2012",
+    "137": "Hyundai Sonata Sedan 2012",
+    "138": "Hyundai Elantra Touring Hatchback 2012",
+    "139": "Hyundai Azera Sedan 2012",
+    "140": "Infiniti G Coupe IPL 2012",
+    "141": "Infiniti QX56 SUV 2011",
+    "142": "Isuzu Ascender SUV 2008",
+    "143": "Jaguar XK XKR 2012",
+    "144": "Jeep Patriot SUV 2012",
+    "145": "Jeep Wrangler SUV 2012",
+    "146": "Jeep Liberty SUV 2012",
+    "147": "Jeep Grand Cherokee SUV 2012",
+    "148": "Jeep Compass SUV 2012",
+    "149": "Lamborghini Reventon Coupe 2008",
+    "150": "Lamborghini Aventador Coupe 2012",
+    "151": "Lamborghini Gallardo LP 570-4 Superleggera 2012",
+    "152": "Lamborghini Diablo Coupe 2001",
+    "153": "Land Rover Range Rover SUV 2012",
+    "154": "Land Rover LR2 SUV 2012",
+    "155": "Lincoln Town Car Sedan 2011",
+    "156": "MINI Cooper Roadster Convertible 2012",
+    "157": "Maybach Landaulet Convertible 2012",
+    "158": "Mazda Tribute SUV 2011",
+    "159": "McLaren MP4-12C Coupe 2012",
+    "160": "Mercedes-Benz 300-Class Convertible 1993",
+    "161": "Mercedes-Benz C-Class Sedan 2012",
+    "162": "Mercedes-Benz SL-Class Coupe 2009",
+    "163": "Mercedes-Benz E-Class Sedan 2012",
+    "164": "Mercedes-Benz S-Class Sedan 2012",
+    "165": "Mercedes-Benz Sprinter Van 2012",
+    "166": "Mitsubishi Lancer Sedan 2012",
+    "167": "Nissan Leaf Hatchback 2012",
+    "168": "Nissan NV Passenger Van 2012",
+    "169": "Nissan Juke Hatchback 2012",
+    "170": "Nissan 240SX Coupe 1998",
+    "171": "Plymouth Neon Coupe 1999",
+    "172": "Porsche Panamera Sedan 2012",
+    "173": "Ram C/V Cargo Van Minivan 2012",
+    "174": "Rolls-Royce Phantom Drophead Coupe Convertible 2012",
+    "175": "Rolls-Royce Ghost Sedan 2012",
+    "176": "Rolls-Royce Phantom Sedan 2012",
+    "177": "Scion xD Hatchback 2012",
+    "178": "Spyker C8 Convertible 2009",
+    "179": "Spyker C8 Coupe 2009",
+    "180": "Suzuki Aerio Sedan 2007",
+    "181": "Suzuki Kizashi Sedan 2012",
+    "182": "Suzuki SX4 Hatchback 2012",
+    "183": "Suzuki SX4 Sedan 2012",
+    "184": "Tesla Model S Sedan 2012",
+    "185": "Toyota Sequoia SUV 2012",
+    "186": "Toyota Camry Sedan 2012",
+    "187": "Toyota Corolla Sedan 2012",
+    "188": "Toyota 4Runner SUV 2012",
+    "189": "Volkswagen Golf Hatchback 2012",
+    "190": "Volkswagen Golf Hatchback 1991",
+    "191": "Volkswagen Beetle Hatchback 2012",
+    "192": "Volvo C30 Hatchback 2012",
+    "193": "Volvo 240 Sedan 1993",
+    "194": "Volvo XC90 SUV 2007",
+    "195": "smart fortwo Convertible 2012"
+  },
+  "label2id": {
+    "AM General Hummer SUV 2000": 0,
+    "Acura Integra Type R 2001": 5,
+    "Acura RL Sedan 2012": 1,
+    "Acura TL Sedan 2012": 2,
+    "Acura TL Type-S 2008": 3,
+    "Acura TSX Sedan 2012": 4,
+    "Acura ZDX Hatchback 2012": 6,
+    "Aston Martin V8 Vantage Convertible 2012": 7,
+    "Aston Martin V8 Vantage Coupe 2012": 8,
+    "Aston Martin Virage Convertible 2012": 9,
+    "Aston Martin Virage Coupe 2012": 10,
+    "Audi 100 Sedan 1994": 16,
+    "Audi 100 Wagon 1994": 17,
+    "Audi A5 Coupe 2012": 12,
+    "Audi R8 Coupe 2012": 14,
+    "Audi RS 4 Convertible 2008": 11,
+    "Audi S4 Sedan 2007": 23,
+    "Audi S4 Sedan 2012": 22,
+    "Audi S5 Convertible 2012": 20,
+    "Audi S5 Coupe 2012": 21,
+    "Audi S6 Sedan 2011": 19,
+    "Audi TT Hatchback 2011": 18,
+    "Audi TT RS Coupe 2012": 24,
+    "Audi TTS Coupe 2012": 13,
+    "Audi V8 Sedan 1994": 15,
+    "BMW 1 Series Convertible 2012": 26,
+    "BMW 1 Series Coupe 2012": 27,
+    "BMW 3 Series Sedan 2012": 28,
+    "BMW 3 Series Wagon 2012": 29,
+    "BMW 6 Series Convertible 2007": 30,
+    "BMW ActiveHybrid 5 Sedan 2012": 25,
+    "BMW M3 Coupe 2012": 33,
+    "BMW M5 Sedan 2010": 34,
+    "BMW M6 Convertible 2010": 35,
+    "BMW X3 SUV 2012": 36,
+    "BMW X5 SUV 2007": 31,
+    "BMW X6 SUV 2012": 32,
+    "BMW Z4 Convertible 2012": 37,
+    "Bentley Arnage Sedan 2009": 39,
+    "Bentley Continental Flying Spur Sedan 2007": 43,
+    "Bentley Continental GT Coupe 2007": 42,
+    "Bentley Continental GT Coupe 2012": 41,
+    "Bentley Continental Supersports Conv. Convertible 2012": 38,
+    "Bentley Mulsanne Sedan 2011": 40,
+    "Bugatti Veyron 16.4 Convertible 2009": 44,
+    "Bugatti Veyron 16.4 Coupe 2009": 45,
+    "Buick Enclave SUV 2012": 49,
+    "Buick Rainier SUV 2007": 47,
+    "Buick Regal GS 2012": 46,
+    "Buick Verano Sedan 2012": 48,
+    "Cadillac CTS-V Sedan 2012": 50,
+    "Cadillac Escalade EXT Crew Cab 2007": 52,
+    "Cadillac SRX SUV 2012": 51,
+    "Chevrolet Avalanche Crew Cab 2012": 64,
+    "Chevrolet Camaro Convertible 2012": 58,
+    "Chevrolet Cobalt SS 2010": 65,
+    "Chevrolet Corvette Convertible 2012": 54,
+    "Chevrolet Corvette Ron Fellows Edition Z06 2007": 56,
+    "Chevrolet Corvette ZR1 2012": 55,
+    "Chevrolet Express Cargo Van 2007": 63,
+    "Chevrolet Express Van 2007": 70,
+    "Chevrolet HHR SS 2010": 59,
+    "Chevrolet Impala Sedan 2007": 60,
+    "Chevrolet Malibu Hybrid Sedan 2010": 66,
+    "Chevrolet Malibu Sedan 2007": 72,
+    "Chevrolet Monte Carlo Coupe 2007": 71,
+    "Chevrolet Silverado 1500 Classic Extended Cab 2007": 69,
+    "Chevrolet Silverado 1500 Extended Cab 2012": 73,
+    "Chevrolet Silverado 1500 Hybrid Crew Cab 2012": 53,
+    "Chevrolet Silverado 1500 Regular Cab 2012": 74,
+    "Chevrolet Silverado 2500HD Regular Cab 2012": 68,
+    "Chevrolet Sonic Sedan 2012": 62,
+    "Chevrolet Tahoe Hybrid SUV 2012": 61,
+    "Chevrolet TrailBlazer SS 2009": 67,
+    "Chevrolet Traverse SUV 2012": 57,
+    "Chrysler 300 SRT-8 2010": 78,
+    "Chrysler Aspen SUV 2009": 75,
+    "Chrysler Crossfire Convertible 2008": 79,
+    "Chrysler PT Cruiser Convertible 2008": 80,
+    "Chrysler Sebring Convertible 2010": 76,
+    "Chrysler Town and Country Minivan 2012": 77,
+    "Daewoo Nubira Wagon 2002": 81,
+    "Dodge Caliber Wagon 2007": 83,
+    "Dodge Caliber Wagon 2012": 82,
+    "Dodge Caravan Minivan 1997": 84,
+    "Dodge Challenger SRT8 2011": 92,
+    "Dodge Charger SRT-8 2009": 96,
+    "Dodge Charger Sedan 2012": 95,
+    "Dodge Dakota Club Cab 2007": 90,
+    "Dodge Dakota Crew Cab 2010": 89,
+    "Dodge Durango SUV 2007": 94,
+    "Dodge Durango SUV 2012": 93,
+    "Dodge Journey SUV 2012": 88,
+    "Dodge Magnum Wagon 2008": 91,
+    "Dodge Ram Pickup 3500 Crew Cab 2010": 85,
+    "Dodge Ram Pickup 3500 Quad Cab 2009": 86,
+    "Dodge Sprinter Cargo Van 2009": 87,
+    "Eagle Talon Hatchback 1998": 97,
+    "FIAT 500 Abarth 2012": 98,
+    "FIAT 500 Convertible 2012": 99,
+    "Ferrari 458 Italia Convertible 2012": 102,
+    "Ferrari 458 Italia Coupe 2012": 103,
+    "Ferrari California Convertible 2012": 101,
+    "Ferrari FF Coupe 2012": 100,
+    "Fisker Karma Sedan 2012": 104,
+    "Ford E-Series Wagon Van 2012": 115,
+    "Ford Edge SUV 2012": 109,
+    "Ford Expedition EL SUV 2009": 108,
+    "Ford F-150 Regular Cab 2007": 113,
+    "Ford F-150 Regular Cab 2012": 112,
+    "Ford F-450 Super Duty Crew Cab 2012": 105,
+    "Ford Fiesta Sedan 2012": 116,
+    "Ford Focus Sedan 2007": 114,
+    "Ford Freestar Minivan 2007": 107,
+    "Ford GT Coupe 2006": 111,
+    "Ford Mustang Convertible 2007": 106,
+    "Ford Ranger SuperCab 2011": 110,
+    "GMC Acadia SUV 2012": 120,
+    "GMC Canyon Extended Cab 2012": 121,
+    "GMC Savana Van 2012": 118,
+    "GMC Terrain SUV 2012": 117,
+    "GMC Yukon Hybrid SUV 2012": 119,
+    "Geo Metro Convertible 1993": 122,
+    "HUMMER H2 SUT Crew Cab 2009": 124,
+    "HUMMER H3T Crew Cab 2010": 123,
+    "Honda Accord Coupe 2012": 127,
+    "Honda Accord Sedan 2012": 128,
+    "Honda Odyssey Minivan 2007": 126,
+    "Honda Odyssey Minivan 2012": 125,
+    "Hyundai Accent Sedan 2012": 135,
+    "Hyundai Azera Sedan 2012": 139,
+    "Hyundai Elantra Sedan 2007": 134,
+    "Hyundai Elantra Touring Hatchback 2012": 138,
+    "Hyundai Genesis Sedan 2012": 136,
+    "Hyundai Santa Fe SUV 2012": 130,
+    "Hyundai Sonata Hybrid Sedan 2012": 133,
+    "Hyundai Sonata Sedan 2012": 137,
+    "Hyundai Tucson SUV 2012": 131,
+    "Hyundai Veloster Hatchback 2012": 129,
+    "Hyundai Veracruz SUV 2012": 132,
+    "Infiniti G Coupe IPL 2012": 140,
+    "Infiniti QX56 SUV 2011": 141,
+    "Isuzu Ascender SUV 2008": 142,
+    "Jaguar XK XKR 2012": 143,
+    "Jeep Compass SUV 2012": 148,
+    "Jeep Grand Cherokee SUV 2012": 147,
+    "Jeep Liberty SUV 2012": 146,
+    "Jeep Patriot SUV 2012": 144,
+    "Jeep Wrangler SUV 2012": 145,
+    "Lamborghini Aventador Coupe 2012": 150,
+    "Lamborghini Diablo Coupe 2001": 152,
+    "Lamborghini Gallardo LP 570-4 Superleggera 2012": 151,
+    "Lamborghini Reventon Coupe 2008": 149,
+    "Land Rover LR2 SUV 2012": 154,
+    "Land Rover Range Rover SUV 2012": 153,
+    "Lincoln Town Car Sedan 2011": 155,
+    "MINI Cooper Roadster Convertible 2012": 156,
+    "Maybach Landaulet Convertible 2012": 157,
+    "Mazda Tribute SUV 2011": 158,
+    "McLaren MP4-12C Coupe 2012": 159,
+    "Mercedes-Benz 300-Class Convertible 1993": 160,
+    "Mercedes-Benz C-Class Sedan 2012": 161,
+    "Mercedes-Benz E-Class Sedan 2012": 163,
+    "Mercedes-Benz S-Class Sedan 2012": 164,
+    "Mercedes-Benz SL-Class Coupe 2009": 162,
+    "Mercedes-Benz Sprinter Van 2012": 165,
+    "Mitsubishi Lancer Sedan 2012": 166,
+    "Nissan 240SX Coupe 1998": 170,
+    "Nissan Juke Hatchback 2012": 169,
+    "Nissan Leaf Hatchback 2012": 167,
+    "Nissan NV Passenger Van 2012": 168,
+    "Plymouth Neon Coupe 1999": 171,
+    "Porsche Panamera Sedan 2012": 172,
+    "Ram C/V Cargo Van Minivan 2012": 173,
+    "Rolls-Royce Ghost Sedan 2012": 175,
+    "Rolls-Royce Phantom Drophead Coupe Convertible 2012": 174,
+    "Rolls-Royce Phantom Sedan 2012": 176,
+    "Scion xD Hatchback 2012": 177,
+    "Spyker C8 Convertible 2009": 178,
+    "Spyker C8 Coupe 2009": 179,
+    "Suzuki Aerio Sedan 2007": 180,
+    "Suzuki Kizashi Sedan 2012": 181,
+    "Suzuki SX4 Hatchback 2012": 182,
+    "Suzuki SX4 Sedan 2012": 183,
+    "Tesla Model S Sedan 2012": 184,
+    "Toyota 4Runner SUV 2012": 188,
+    "Toyota Camry Sedan 2012": 186,
+    "Toyota Corolla Sedan 2012": 187,
+    "Toyota Sequoia SUV 2012": 185,
+    "Volkswagen Beetle Hatchback 2012": 191,
+    "Volkswagen Golf Hatchback 1991": 190,
+    "Volkswagen Golf Hatchback 2012": 189,
+    "Volvo 240 Sedan 1993": 193,
+    "Volvo C30 Hatchback 2012": 192,
+    "Volvo XC90 SUV 2007": 194,
+    "smart fortwo Convertible 2012": 195
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-stanford-cars-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet18-stanford-cars-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-stanford-cars-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-stl10-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md b/resnet18-stl10-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..301d92dbb7fef24fa1a2d142614f846a26b2fa82
--- /dev/null
+++ b/resnet18-stl10-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stl10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: stl10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: train
+type: transformers
+val_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: test
+```
+
diff --git a/resnet18-stl10-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/config.json b/resnet18-stl10-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..29c93b2c12685a5b5caf379e93026d934c412298
--- /dev/null
+++ b/resnet18-stl10-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "bird",
+    "2": "car",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "horse",
+    "7": "monkey",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "bird": 1,
+    "car": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "horse": 6,
+    "monkey": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-stl10-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet18-stl10-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-stl10-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-stl10-batch_size_256_lr_0.005_training_data_ratio_0.8-3000/README.md b/resnet18-stl10-batch_size_256_lr_0.005_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..bcda3a04f2fd753af05509528c5c7a7a30b75ab3
--- /dev/null
+++ b/resnet18-stl10-batch_size_256_lr_0.005_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stl10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: stl10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: train
+type: transformers
+val_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: test
+```
+
diff --git a/resnet18-stl10-batch_size_256_lr_0.005_training_data_ratio_0.8-3000/config.json b/resnet18-stl10-batch_size_256_lr_0.005_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..29c93b2c12685a5b5caf379e93026d934c412298
--- /dev/null
+++ b/resnet18-stl10-batch_size_256_lr_0.005_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "bird",
+    "2": "car",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "horse",
+    "7": "monkey",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "bird": 1,
+    "car": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "horse": 6,
+    "monkey": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-stl10-batch_size_256_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet18-stl10-batch_size_256_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-stl10-batch_size_256_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-stl10-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/README.md b/resnet18-stl10-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..c9113682c7b2afca8ddb52dbdd0cf01584b1ae35
--- /dev/null
+++ b/resnet18-stl10-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stl10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: stl10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: train
+type: transformers
+val_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: test
+```
+
diff --git a/resnet18-stl10-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/config.json b/resnet18-stl10-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..29c93b2c12685a5b5caf379e93026d934c412298
--- /dev/null
+++ b/resnet18-stl10-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "bird",
+    "2": "car",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "horse",
+    "7": "monkey",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "bird": 1,
+    "car": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "horse": 6,
+    "monkey": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-stl10-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet18-stl10-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-stl10-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-stl10-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/README.md b/resnet18-stl10-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..48a8f470acac9b17f8bdd8dc6716585c748ef835
--- /dev/null
+++ b/resnet18-stl10-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stl10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: stl10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: train
+type: transformers
+val_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: test
+```
+
diff --git a/resnet18-stl10-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/config.json b/resnet18-stl10-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..29c93b2c12685a5b5caf379e93026d934c412298
--- /dev/null
+++ b/resnet18-stl10-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "bird",
+    "2": "car",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "horse",
+    "7": "monkey",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "bird": 1,
+    "car": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "horse": 6,
+    "monkey": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-stl10-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet18-stl10-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-stl10-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-stl10-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/README.md b/resnet18-stl10-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..23dc6ac5c24562f607f2992b8b3a9d4fefa6d26e
--- /dev/null
+++ b/resnet18-stl10-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stl10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: stl10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: train
+type: transformers
+val_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: test
+```
+
diff --git a/resnet18-stl10-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/config.json b/resnet18-stl10-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..29c93b2c12685a5b5caf379e93026d934c412298
--- /dev/null
+++ b/resnet18-stl10-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "bird",
+    "2": "car",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "horse",
+    "7": "monkey",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "bird": 1,
+    "car": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "horse": 6,
+    "monkey": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-stl10-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet18-stl10-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-stl10-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-sun397-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/README.md b/resnet18-sun397-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..45116283da7a8a58a4d726f0c2e22891c463d504
--- /dev/null
+++ b/resnet18-sun397-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset sun397.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: sun397
+    pretrained: true
+test_datasets: null
+train_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: train
+type: transformers
+val_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: test
+```
+
diff --git a/resnet18-sun397-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/config.json b/resnet18-sun397-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..886da3497a7114ff31c2408ec559a773285de738
--- /dev/null
+++ b/resnet18-sun397-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,837 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "abbey",
+    "1": "airplane cabin",
+    "2": "airport terminal",
+    "3": "alley",
+    "4": "amphitheater",
+    "5": "amusement arcade",
+    "6": "amusement park",
+    "7": "anechoic chamber",
+    "8": "apartment building outdoor",
+    "9": "apse indoor",
+    "10": "aquarium",
+    "11": "aqueduct",
+    "12": "arch",
+    "13": "archive",
+    "14": "arrival gate outdoor",
+    "15": "art gallery",
+    "16": "art school",
+    "17": "art studio",
+    "18": "assembly line",
+    "19": "athletic field outdoor",
+    "20": "atrium public",
+    "21": "attic",
+    "22": "auditorium",
+    "23": "auto factory",
+    "24": "badlands",
+    "25": "badminton court indoor",
+    "26": "baggage claim",
+    "27": "bakery shop",
+    "28": "balcony exterior",
+    "29": "balcony interior",
+    "30": "ball pit",
+    "31": "ballroom",
+    "32": "bamboo forest",
+    "33": "banquet hall",
+    "34": "bar",
+    "35": "barn",
+    "36": "barndoor",
+    "37": "baseball field",
+    "38": "basement",
+    "39": "basilica",
+    "40": "basketball court outdoor",
+    "41": "bathroom",
+    "42": "batters box",
+    "43": "bayou",
+    "44": "bazaar indoor",
+    "45": "bazaar outdoor",
+    "46": "beach",
+    "47": "beauty salon",
+    "48": "bedroom",
+    "49": "berth",
+    "50": "biology laboratory",
+    "51": "bistro indoor",
+    "52": "boardwalk",
+    "53": "boat deck",
+    "54": "boathouse",
+    "55": "bookstore",
+    "56": "booth indoor",
+    "57": "botanical garden",
+    "58": "bow window indoor",
+    "59": "bow window outdoor",
+    "60": "bowling alley",
+    "61": "boxing ring",
+    "62": "brewery indoor",
+    "63": "bridge",
+    "64": "building facade",
+    "65": "bullring",
+    "66": "burial chamber",
+    "67": "bus interior",
+    "68": "butchers shop",
+    "69": "butte",
+    "70": "cabin outdoor",
+    "71": "cafeteria",
+    "72": "campsite",
+    "73": "campus",
+    "74": "canal natural",
+    "75": "canal urban",
+    "76": "candy store",
+    "77": "canyon",
+    "78": "car interior backseat",
+    "79": "car interior frontseat",
+    "80": "carrousel",
+    "81": "casino indoor",
+    "82": "castle",
+    "83": "catacomb",
+    "84": "cathedral indoor",
+    "85": "cathedral outdoor",
+    "86": "cavern indoor",
+    "87": "cemetery",
+    "88": "chalet",
+    "89": "cheese factory",
+    "90": "chemistry lab",
+    "91": "chicken coop indoor",
+    "92": "chicken coop outdoor",
+    "93": "childs room",
+    "94": "church indoor",
+    "95": "church outdoor",
+    "96": "classroom",
+    "97": "clean room",
+    "98": "cliff",
+    "99": "cloister indoor",
+    "100": "closet",
+    "101": "clothing store",
+    "102": "coast",
+    "103": "cockpit",
+    "104": "coffee shop",
+    "105": "computer room",
+    "106": "conference center",
+    "107": "conference room",
+    "108": "construction site",
+    "109": "control room",
+    "110": "control tower outdoor",
+    "111": "corn field",
+    "112": "corral",
+    "113": "corridor",
+    "114": "cottage garden",
+    "115": "courthouse",
+    "116": "courtroom",
+    "117": "courtyard",
+    "118": "covered bridge exterior",
+    "119": "creek",
+    "120": "crevasse",
+    "121": "crosswalk",
+    "122": "cubicle office",
+    "123": "dam",
+    "124": "delicatessen",
+    "125": "dentists office",
+    "126": "desert sand",
+    "127": "desert vegetation",
+    "128": "diner indoor",
+    "129": "diner outdoor",
+    "130": "dinette home",
+    "131": "dinette vehicle",
+    "132": "dining car",
+    "133": "dining room",
+    "134": "discotheque",
+    "135": "dock",
+    "136": "doorway outdoor",
+    "137": "dorm room",
+    "138": "driveway",
+    "139": "driving range outdoor",
+    "140": "drugstore",
+    "141": "electrical substation",
+    "142": "elevator door",
+    "143": "elevator interior",
+    "144": "elevator shaft",
+    "145": "engine room",
+    "146": "escalator indoor",
+    "147": "excavation",
+    "148": "factory indoor",
+    "149": "fairway",
+    "150": "fastfood restaurant",
+    "151": "field cultivated",
+    "152": "field wild",
+    "153": "fire escape",
+    "154": "fire station",
+    "155": "firing range indoor",
+    "156": "fishpond",
+    "157": "florist shop indoor",
+    "158": "food court",
+    "159": "forest broadleaf",
+    "160": "forest needleleaf",
+    "161": "forest path",
+    "162": "forest road",
+    "163": "formal garden",
+    "164": "fountain",
+    "165": "galley",
+    "166": "game room",
+    "167": "garage indoor",
+    "168": "garbage dump",
+    "169": "gas station",
+    "170": "gazebo exterior",
+    "171": "general store indoor",
+    "172": "general store outdoor",
+    "173": "gift shop",
+    "174": "golf course",
+    "175": "greenhouse indoor",
+    "176": "greenhouse outdoor",
+    "177": "gymnasium indoor",
+    "178": "hangar indoor",
+    "179": "hangar outdoor",
+    "180": "harbor",
+    "181": "hayfield",
+    "182": "heliport",
+    "183": "herb garden",
+    "184": "highway",
+    "185": "hill",
+    "186": "home office",
+    "187": "hospital",
+    "188": "hospital room",
+    "189": "hot spring",
+    "190": "hot tub outdoor",
+    "191": "hotel outdoor",
+    "192": "hotel room",
+    "193": "house",
+    "194": "hunting lodge outdoor",
+    "195": "ice cream parlor",
+    "196": "ice floe",
+    "197": "ice shelf",
+    "198": "ice skating rink indoor",
+    "199": "ice skating rink outdoor",
+    "200": "iceberg",
+    "201": "igloo",
+    "202": "industrial area",
+    "203": "inn outdoor",
+    "204": "islet",
+    "205": "jacuzzi indoor",
+    "206": "jail cell",
+    "207": "jail indoor",
+    "208": "jewelry shop",
+    "209": "kasbah",
+    "210": "kennel indoor",
+    "211": "kennel outdoor",
+    "212": "kindergarden classroom",
+    "213": "kitchen",
+    "214": "kitchenette",
+    "215": "labyrinth outdoor",
+    "216": "lake natural",
+    "217": "landfill",
+    "218": "landing deck",
+    "219": "laundromat",
+    "220": "lecture room",
+    "221": "library indoor",
+    "222": "library outdoor",
+    "223": "lido deck outdoor",
+    "224": "lift bridge",
+    "225": "lighthouse",
+    "226": "limousine interior",
+    "227": "living room",
+    "228": "lobby",
+    "229": "lock chamber",
+    "230": "locker room",
+    "231": "mansion",
+    "232": "manufactured home",
+    "233": "market indoor",
+    "234": "market outdoor",
+    "235": "marsh",
+    "236": "martial arts gym",
+    "237": "mausoleum",
+    "238": "medina",
+    "239": "moat water",
+    "240": "monastery outdoor",
+    "241": "mosque indoor",
+    "242": "mosque outdoor",
+    "243": "motel",
+    "244": "mountain",
+    "245": "mountain snowy",
+    "246": "movie theater indoor",
+    "247": "museum indoor",
+    "248": "music store",
+    "249": "music studio",
+    "250": "nuclear power plant outdoor",
+    "251": "nursery",
+    "252": "oast house",
+    "253": "observatory outdoor",
+    "254": "ocean",
+    "255": "office",
+    "256": "office building",
+    "257": "oil refinery outdoor",
+    "258": "oilrig",
+    "259": "operating room",
+    "260": "orchard",
+    "261": "outhouse outdoor",
+    "262": "pagoda",
+    "263": "palace",
+    "264": "pantry",
+    "265": "park",
+    "266": "parking garage indoor",
+    "267": "parking garage outdoor",
+    "268": "parking lot",
+    "269": "parlor",
+    "270": "pasture",
+    "271": "patio",
+    "272": "pavilion",
+    "273": "pharmacy",
+    "274": "phone booth",
+    "275": "physics laboratory",
+    "276": "picnic area",
+    "277": "pilothouse indoor",
+    "278": "planetarium outdoor",
+    "279": "playground",
+    "280": "playroom",
+    "281": "plaza",
+    "282": "podium indoor",
+    "283": "podium outdoor",
+    "284": "pond",
+    "285": "poolroom establishment",
+    "286": "poolroom home",
+    "287": "power plant outdoor",
+    "288": "promenade deck",
+    "289": "pub indoor",
+    "290": "pulpit",
+    "291": "putting green",
+    "292": "racecourse",
+    "293": "raceway",
+    "294": "raft",
+    "295": "railroad track",
+    "296": "rainforest",
+    "297": "reception",
+    "298": "recreation room",
+    "299": "residential neighborhood",
+    "300": "restaurant",
+    "301": "restaurant kitchen",
+    "302": "restaurant patio",
+    "303": "rice paddy",
+    "304": "riding arena",
+    "305": "river",
+    "306": "rock arch",
+    "307": "rope bridge",
+    "308": "ruin",
+    "309": "runway",
+    "310": "sandbar",
+    "311": "sandbox",
+    "312": "sauna",
+    "313": "schoolhouse",
+    "314": "sea cliff",
+    "315": "server room",
+    "316": "shed",
+    "317": "shoe shop",
+    "318": "shopfront",
+    "319": "shopping mall indoor",
+    "320": "shower",
+    "321": "skatepark",
+    "322": "ski lodge",
+    "323": "ski resort",
+    "324": "ski slope",
+    "325": "sky",
+    "326": "skyscraper",
+    "327": "slum",
+    "328": "snowfield",
+    "329": "squash court",
+    "330": "stable",
+    "331": "stadium baseball",
+    "332": "stadium football",
+    "333": "stage indoor",
+    "334": "staircase",
+    "335": "street",
+    "336": "subway interior",
+    "337": "subway station platform",
+    "338": "supermarket",
+    "339": "sushi bar",
+    "340": "swamp",
+    "341": "swimming pool indoor",
+    "342": "swimming pool outdoor",
+    "343": "synagogue indoor",
+    "344": "synagogue outdoor",
+    "345": "television studio",
+    "346": "temple east asia",
+    "347": "temple south asia",
+    "348": "tennis court indoor",
+    "349": "tennis court outdoor",
+    "350": "tent outdoor",
+    "351": "theater indoor procenium",
+    "352": "theater indoor seats",
+    "353": "thriftshop",
+    "354": "throne room",
+    "355": "ticket booth",
+    "356": "toll plaza",
+    "357": "topiary garden",
+    "358": "tower",
+    "359": "toyshop",
+    "360": "track outdoor",
+    "361": "train railway",
+    "362": "train station platform",
+    "363": "tree farm",
+    "364": "tree house",
+    "365": "trench",
+    "366": "underwater coral reef",
+    "367": "utility room",
+    "368": "valley",
+    "369": "van interior",
+    "370": "vegetable garden",
+    "371": "veranda",
+    "372": "veterinarians office",
+    "373": "viaduct",
+    "374": "videostore",
+    "375": "village",
+    "376": "vineyard",
+    "377": "volcano",
+    "378": "volleyball court indoor",
+    "379": "volleyball court outdoor",
+    "380": "waiting room",
+    "381": "warehouse indoor",
+    "382": "water tower",
+    "383": "waterfall block",
+    "384": "waterfall fan",
+    "385": "waterfall plunge",
+    "386": "watering hole",
+    "387": "wave",
+    "388": "wet bar",
+    "389": "wheat field",
+    "390": "wind farm",
+    "391": "windmill",
+    "392": "wine cellar barrel storage",
+    "393": "wine cellar bottle storage",
+    "394": "wrestling ring indoor",
+    "395": "yard",
+    "396": "youth hostel"
+  },
+  "label2id": {
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+    "airplane cabin": 1,
+    "airport terminal": 2,
+    "alley": 3,
+    "amphitheater": 4,
+    "amusement arcade": 5,
+    "amusement park": 6,
+    "anechoic chamber": 7,
+    "apartment building outdoor": 8,
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+    "aquarium": 10,
+    "aqueduct": 11,
+    "arch": 12,
+    "archive": 13,
+    "arrival gate outdoor": 14,
+    "art gallery": 15,
+    "art school": 16,
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+    "assembly line": 18,
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+    "atrium public": 20,
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+    "auditorium": 22,
+    "auto factory": 23,
+    "badlands": 24,
+    "badminton court indoor": 25,
+    "baggage claim": 26,
+    "bakery shop": 27,
+    "balcony exterior": 28,
+    "balcony interior": 29,
+    "ball pit": 30,
+    "ballroom": 31,
+    "bamboo forest": 32,
+    "banquet hall": 33,
+    "bar": 34,
+    "barn": 35,
+    "barndoor": 36,
+    "baseball field": 37,
+    "basement": 38,
+    "basilica": 39,
+    "basketball court outdoor": 40,
+    "bathroom": 41,
+    "batters box": 42,
+    "bayou": 43,
+    "bazaar indoor": 44,
+    "bazaar outdoor": 45,
+    "beach": 46,
+    "beauty salon": 47,
+    "bedroom": 48,
+    "berth": 49,
+    "biology laboratory": 50,
+    "bistro indoor": 51,
+    "boardwalk": 52,
+    "boat deck": 53,
+    "boathouse": 54,
+    "bookstore": 55,
+    "booth indoor": 56,
+    "botanical garden": 57,
+    "bow window indoor": 58,
+    "bow window outdoor": 59,
+    "bowling alley": 60,
+    "boxing ring": 61,
+    "brewery indoor": 62,
+    "bridge": 63,
+    "building facade": 64,
+    "bullring": 65,
+    "burial chamber": 66,
+    "bus interior": 67,
+    "butchers shop": 68,
+    "butte": 69,
+    "cabin outdoor": 70,
+    "cafeteria": 71,
+    "campsite": 72,
+    "campus": 73,
+    "canal natural": 74,
+    "canal urban": 75,
+    "candy store": 76,
+    "canyon": 77,
+    "car interior backseat": 78,
+    "car interior frontseat": 79,
+    "carrousel": 80,
+    "casino indoor": 81,
+    "castle": 82,
+    "catacomb": 83,
+    "cathedral indoor": 84,
+    "cathedral outdoor": 85,
+    "cavern indoor": 86,
+    "cemetery": 87,
+    "chalet": 88,
+    "cheese factory": 89,
+    "chemistry lab": 90,
+    "chicken coop indoor": 91,
+    "chicken coop outdoor": 92,
+    "childs room": 93,
+    "church indoor": 94,
+    "church outdoor": 95,
+    "classroom": 96,
+    "clean room": 97,
+    "cliff": 98,
+    "cloister indoor": 99,
+    "closet": 100,
+    "clothing store": 101,
+    "coast": 102,
+    "cockpit": 103,
+    "coffee shop": 104,
+    "computer room": 105,
+    "conference center": 106,
+    "conference room": 107,
+    "construction site": 108,
+    "control room": 109,
+    "control tower outdoor": 110,
+    "corn field": 111,
+    "corral": 112,
+    "corridor": 113,
+    "cottage garden": 114,
+    "courthouse": 115,
+    "courtroom": 116,
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+    "creek": 119,
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+    "crosswalk": 121,
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+    "dam": 123,
+    "delicatessen": 124,
+    "dentists office": 125,
+    "desert sand": 126,
+    "desert vegetation": 127,
+    "diner indoor": 128,
+    "diner outdoor": 129,
+    "dinette home": 130,
+    "dinette vehicle": 131,
+    "dining car": 132,
+    "dining room": 133,
+    "discotheque": 134,
+    "dock": 135,
+    "doorway outdoor": 136,
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+    "driveway": 138,
+    "driving range outdoor": 139,
+    "drugstore": 140,
+    "electrical substation": 141,
+    "elevator door": 142,
+    "elevator interior": 143,
+    "elevator shaft": 144,
+    "engine room": 145,
+    "escalator indoor": 146,
+    "excavation": 147,
+    "factory indoor": 148,
+    "fairway": 149,
+    "fastfood restaurant": 150,
+    "field cultivated": 151,
+    "field wild": 152,
+    "fire escape": 153,
+    "fire station": 154,
+    "firing range indoor": 155,
+    "fishpond": 156,
+    "florist shop indoor": 157,
+    "food court": 158,
+    "forest broadleaf": 159,
+    "forest needleleaf": 160,
+    "forest path": 161,
+    "forest road": 162,
+    "formal garden": 163,
+    "fountain": 164,
+    "galley": 165,
+    "game room": 166,
+    "garage indoor": 167,
+    "garbage dump": 168,
+    "gas station": 169,
+    "gazebo exterior": 170,
+    "general store indoor": 171,
+    "general store outdoor": 172,
+    "gift shop": 173,
+    "golf course": 174,
+    "greenhouse indoor": 175,
+    "greenhouse outdoor": 176,
+    "gymnasium indoor": 177,
+    "hangar indoor": 178,
+    "hangar outdoor": 179,
+    "harbor": 180,
+    "hayfield": 181,
+    "heliport": 182,
+    "herb garden": 183,
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+    "hill": 185,
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+    "hospital": 187,
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+    "hot tub outdoor": 190,
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+    "hotel room": 192,
+    "house": 193,
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+    "ice cream parlor": 195,
+    "ice floe": 196,
+    "ice shelf": 197,
+    "ice skating rink indoor": 198,
+    "ice skating rink outdoor": 199,
+    "iceberg": 200,
+    "igloo": 201,
+    "industrial area": 202,
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+    "islet": 204,
+    "jacuzzi indoor": 205,
+    "jail cell": 206,
+    "jail indoor": 207,
+    "jewelry shop": 208,
+    "kasbah": 209,
+    "kennel indoor": 210,
+    "kennel outdoor": 211,
+    "kindergarden classroom": 212,
+    "kitchen": 213,
+    "kitchenette": 214,
+    "labyrinth outdoor": 215,
+    "lake natural": 216,
+    "landfill": 217,
+    "landing deck": 218,
+    "laundromat": 219,
+    "lecture room": 220,
+    "library indoor": 221,
+    "library outdoor": 222,
+    "lido deck outdoor": 223,
+    "lift bridge": 224,
+    "lighthouse": 225,
+    "limousine interior": 226,
+    "living room": 227,
+    "lobby": 228,
+    "lock chamber": 229,
+    "locker room": 230,
+    "mansion": 231,
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+    "market indoor": 233,
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+    "martial arts gym": 236,
+    "mausoleum": 237,
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+    "monastery outdoor": 240,
+    "mosque indoor": 241,
+    "mosque outdoor": 242,
+    "motel": 243,
+    "mountain": 244,
+    "mountain snowy": 245,
+    "movie theater indoor": 246,
+    "museum indoor": 247,
+    "music store": 248,
+    "music studio": 249,
+    "nuclear power plant outdoor": 250,
+    "nursery": 251,
+    "oast house": 252,
+    "observatory outdoor": 253,
+    "ocean": 254,
+    "office": 255,
+    "office building": 256,
+    "oil refinery outdoor": 257,
+    "oilrig": 258,
+    "operating room": 259,
+    "orchard": 260,
+    "outhouse outdoor": 261,
+    "pagoda": 262,
+    "palace": 263,
+    "pantry": 264,
+    "park": 265,
+    "parking garage indoor": 266,
+    "parking garage outdoor": 267,
+    "parking lot": 268,
+    "parlor": 269,
+    "pasture": 270,
+    "patio": 271,
+    "pavilion": 272,
+    "pharmacy": 273,
+    "phone booth": 274,
+    "physics laboratory": 275,
+    "picnic area": 276,
+    "pilothouse indoor": 277,
+    "planetarium outdoor": 278,
+    "playground": 279,
+    "playroom": 280,
+    "plaza": 281,
+    "podium indoor": 282,
+    "podium outdoor": 283,
+    "pond": 284,
+    "poolroom establishment": 285,
+    "poolroom home": 286,
+    "power plant outdoor": 287,
+    "promenade deck": 288,
+    "pub indoor": 289,
+    "pulpit": 290,
+    "putting green": 291,
+    "racecourse": 292,
+    "raceway": 293,
+    "raft": 294,
+    "railroad track": 295,
+    "rainforest": 296,
+    "reception": 297,
+    "recreation room": 298,
+    "residential neighborhood": 299,
+    "restaurant": 300,
+    "restaurant kitchen": 301,
+    "restaurant patio": 302,
+    "rice paddy": 303,
+    "riding arena": 304,
+    "river": 305,
+    "rock arch": 306,
+    "rope bridge": 307,
+    "ruin": 308,
+    "runway": 309,
+    "sandbar": 310,
+    "sandbox": 311,
+    "sauna": 312,
+    "schoolhouse": 313,
+    "sea cliff": 314,
+    "server room": 315,
+    "shed": 316,
+    "shoe shop": 317,
+    "shopfront": 318,
+    "shopping mall indoor": 319,
+    "shower": 320,
+    "skatepark": 321,
+    "ski lodge": 322,
+    "ski resort": 323,
+    "ski slope": 324,
+    "sky": 325,
+    "skyscraper": 326,
+    "slum": 327,
+    "snowfield": 328,
+    "squash court": 329,
+    "stable": 330,
+    "stadium baseball": 331,
+    "stadium football": 332,
+    "stage indoor": 333,
+    "staircase": 334,
+    "street": 335,
+    "subway interior": 336,
+    "subway station platform": 337,
+    "supermarket": 338,
+    "sushi bar": 339,
+    "swamp": 340,
+    "swimming pool indoor": 341,
+    "swimming pool outdoor": 342,
+    "synagogue indoor": 343,
+    "synagogue outdoor": 344,
+    "television studio": 345,
+    "temple east asia": 346,
+    "temple south asia": 347,
+    "tennis court indoor": 348,
+    "tennis court outdoor": 349,
+    "tent outdoor": 350,
+    "theater indoor procenium": 351,
+    "theater indoor seats": 352,
+    "thriftshop": 353,
+    "throne room": 354,
+    "ticket booth": 355,
+    "toll plaza": 356,
+    "topiary garden": 357,
+    "tower": 358,
+    "toyshop": 359,
+    "track outdoor": 360,
+    "train railway": 361,
+    "train station platform": 362,
+    "tree farm": 363,
+    "tree house": 364,
+    "trench": 365,
+    "underwater coral reef": 366,
+    "utility room": 367,
+    "valley": 368,
+    "van interior": 369,
+    "vegetable garden": 370,
+    "veranda": 371,
+    "veterinarians office": 372,
+    "viaduct": 373,
+    "videostore": 374,
+    "village": 375,
+    "vineyard": 376,
+    "volcano": 377,
+    "volleyball court indoor": 378,
+    "volleyball court outdoor": 379,
+    "waiting room": 380,
+    "warehouse indoor": 381,
+    "water tower": 382,
+    "waterfall block": 383,
+    "waterfall fan": 384,
+    "waterfall plunge": 385,
+    "watering hole": 386,
+    "wave": 387,
+    "wet bar": 388,
+    "wheat field": 389,
+    "wind farm": 390,
+    "windmill": 391,
+    "wine cellar barrel storage": 392,
+    "wine cellar bottle storage": 393,
+    "wrestling ring indoor": 394,
+    "yard": 395,
+    "youth hostel": 396
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-sun397-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet18-sun397-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-sun397-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-sun397-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/config.json b/resnet18-sun397-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..886da3497a7114ff31c2408ec559a773285de738
--- /dev/null
+++ b/resnet18-sun397-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,837 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "abbey",
+    "1": "airplane cabin",
+    "2": "airport terminal",
+    "3": "alley",
+    "4": "amphitheater",
+    "5": "amusement arcade",
+    "6": "amusement park",
+    "7": "anechoic chamber",
+    "8": "apartment building outdoor",
+    "9": "apse indoor",
+    "10": "aquarium",
+    "11": "aqueduct",
+    "12": "arch",
+    "13": "archive",
+    "14": "arrival gate outdoor",
+    "15": "art gallery",
+    "16": "art school",
+    "17": "art studio",
+    "18": "assembly line",
+    "19": "athletic field outdoor",
+    "20": "atrium public",
+    "21": "attic",
+    "22": "auditorium",
+    "23": "auto factory",
+    "24": "badlands",
+    "25": "badminton court indoor",
+    "26": "baggage claim",
+    "27": "bakery shop",
+    "28": "balcony exterior",
+    "29": "balcony interior",
+    "30": "ball pit",
+    "31": "ballroom",
+    "32": "bamboo forest",
+    "33": "banquet hall",
+    "34": "bar",
+    "35": "barn",
+    "36": "barndoor",
+    "37": "baseball field",
+    "38": "basement",
+    "39": "basilica",
+    "40": "basketball court outdoor",
+    "41": "bathroom",
+    "42": "batters box",
+    "43": "bayou",
+    "44": "bazaar indoor",
+    "45": "bazaar outdoor",
+    "46": "beach",
+    "47": "beauty salon",
+    "48": "bedroom",
+    "49": "berth",
+    "50": "biology laboratory",
+    "51": "bistro indoor",
+    "52": "boardwalk",
+    "53": "boat deck",
+    "54": "boathouse",
+    "55": "bookstore",
+    "56": "booth indoor",
+    "57": "botanical garden",
+    "58": "bow window indoor",
+    "59": "bow window outdoor",
+    "60": "bowling alley",
+    "61": "boxing ring",
+    "62": "brewery indoor",
+    "63": "bridge",
+    "64": "building facade",
+    "65": "bullring",
+    "66": "burial chamber",
+    "67": "bus interior",
+    "68": "butchers shop",
+    "69": "butte",
+    "70": "cabin outdoor",
+    "71": "cafeteria",
+    "72": "campsite",
+    "73": "campus",
+    "74": "canal natural",
+    "75": "canal urban",
+    "76": "candy store",
+    "77": "canyon",
+    "78": "car interior backseat",
+    "79": "car interior frontseat",
+    "80": "carrousel",
+    "81": "casino indoor",
+    "82": "castle",
+    "83": "catacomb",
+    "84": "cathedral indoor",
+    "85": "cathedral outdoor",
+    "86": "cavern indoor",
+    "87": "cemetery",
+    "88": "chalet",
+    "89": "cheese factory",
+    "90": "chemistry lab",
+    "91": "chicken coop indoor",
+    "92": "chicken coop outdoor",
+    "93": "childs room",
+    "94": "church indoor",
+    "95": "church outdoor",
+    "96": "classroom",
+    "97": "clean room",
+    "98": "cliff",
+    "99": "cloister indoor",
+    "100": "closet",
+    "101": "clothing store",
+    "102": "coast",
+    "103": "cockpit",
+    "104": "coffee shop",
+    "105": "computer room",
+    "106": "conference center",
+    "107": "conference room",
+    "108": "construction site",
+    "109": "control room",
+    "110": "control tower outdoor",
+    "111": "corn field",
+    "112": "corral",
+    "113": "corridor",
+    "114": "cottage garden",
+    "115": "courthouse",
+    "116": "courtroom",
+    "117": "courtyard",
+    "118": "covered bridge exterior",
+    "119": "creek",
+    "120": "crevasse",
+    "121": "crosswalk",
+    "122": "cubicle office",
+    "123": "dam",
+    "124": "delicatessen",
+    "125": "dentists office",
+    "126": "desert sand",
+    "127": "desert vegetation",
+    "128": "diner indoor",
+    "129": "diner outdoor",
+    "130": "dinette home",
+    "131": "dinette vehicle",
+    "132": "dining car",
+    "133": "dining room",
+    "134": "discotheque",
+    "135": "dock",
+    "136": "doorway outdoor",
+    "137": "dorm room",
+    "138": "driveway",
+    "139": "driving range outdoor",
+    "140": "drugstore",
+    "141": "electrical substation",
+    "142": "elevator door",
+    "143": "elevator interior",
+    "144": "elevator shaft",
+    "145": "engine room",
+    "146": "escalator indoor",
+    "147": "excavation",
+    "148": "factory indoor",
+    "149": "fairway",
+    "150": "fastfood restaurant",
+    "151": "field cultivated",
+    "152": "field wild",
+    "153": "fire escape",
+    "154": "fire station",
+    "155": "firing range indoor",
+    "156": "fishpond",
+    "157": "florist shop indoor",
+    "158": "food court",
+    "159": "forest broadleaf",
+    "160": "forest needleleaf",
+    "161": "forest path",
+    "162": "forest road",
+    "163": "formal garden",
+    "164": "fountain",
+    "165": "galley",
+    "166": "game room",
+    "167": "garage indoor",
+    "168": "garbage dump",
+    "169": "gas station",
+    "170": "gazebo exterior",
+    "171": "general store indoor",
+    "172": "general store outdoor",
+    "173": "gift shop",
+    "174": "golf course",
+    "175": "greenhouse indoor",
+    "176": "greenhouse outdoor",
+    "177": "gymnasium indoor",
+    "178": "hangar indoor",
+    "179": "hangar outdoor",
+    "180": "harbor",
+    "181": "hayfield",
+    "182": "heliport",
+    "183": "herb garden",
+    "184": "highway",
+    "185": "hill",
+    "186": "home office",
+    "187": "hospital",
+    "188": "hospital room",
+    "189": "hot spring",
+    "190": "hot tub outdoor",
+    "191": "hotel outdoor",
+    "192": "hotel room",
+    "193": "house",
+    "194": "hunting lodge outdoor",
+    "195": "ice cream parlor",
+    "196": "ice floe",
+    "197": "ice shelf",
+    "198": "ice skating rink indoor",
+    "199": "ice skating rink outdoor",
+    "200": "iceberg",
+    "201": "igloo",
+    "202": "industrial area",
+    "203": "inn outdoor",
+    "204": "islet",
+    "205": "jacuzzi indoor",
+    "206": "jail cell",
+    "207": "jail indoor",
+    "208": "jewelry shop",
+    "209": "kasbah",
+    "210": "kennel indoor",
+    "211": "kennel outdoor",
+    "212": "kindergarden classroom",
+    "213": "kitchen",
+    "214": "kitchenette",
+    "215": "labyrinth outdoor",
+    "216": "lake natural",
+    "217": "landfill",
+    "218": "landing deck",
+    "219": "laundromat",
+    "220": "lecture room",
+    "221": "library indoor",
+    "222": "library outdoor",
+    "223": "lido deck outdoor",
+    "224": "lift bridge",
+    "225": "lighthouse",
+    "226": "limousine interior",
+    "227": "living room",
+    "228": "lobby",
+    "229": "lock chamber",
+    "230": "locker room",
+    "231": "mansion",
+    "232": "manufactured home",
+    "233": "market indoor",
+    "234": "market outdoor",
+    "235": "marsh",
+    "236": "martial arts gym",
+    "237": "mausoleum",
+    "238": "medina",
+    "239": "moat water",
+    "240": "monastery outdoor",
+    "241": "mosque indoor",
+    "242": "mosque outdoor",
+    "243": "motel",
+    "244": "mountain",
+    "245": "mountain snowy",
+    "246": "movie theater indoor",
+    "247": "museum indoor",
+    "248": "music store",
+    "249": "music studio",
+    "250": "nuclear power plant outdoor",
+    "251": "nursery",
+    "252": "oast house",
+    "253": "observatory outdoor",
+    "254": "ocean",
+    "255": "office",
+    "256": "office building",
+    "257": "oil refinery outdoor",
+    "258": "oilrig",
+    "259": "operating room",
+    "260": "orchard",
+    "261": "outhouse outdoor",
+    "262": "pagoda",
+    "263": "palace",
+    "264": "pantry",
+    "265": "park",
+    "266": "parking garage indoor",
+    "267": "parking garage outdoor",
+    "268": "parking lot",
+    "269": "parlor",
+    "270": "pasture",
+    "271": "patio",
+    "272": "pavilion",
+    "273": "pharmacy",
+    "274": "phone booth",
+    "275": "physics laboratory",
+    "276": "picnic area",
+    "277": "pilothouse indoor",
+    "278": "planetarium outdoor",
+    "279": "playground",
+    "280": "playroom",
+    "281": "plaza",
+    "282": "podium indoor",
+    "283": "podium outdoor",
+    "284": "pond",
+    "285": "poolroom establishment",
+    "286": "poolroom home",
+    "287": "power plant outdoor",
+    "288": "promenade deck",
+    "289": "pub indoor",
+    "290": "pulpit",
+    "291": "putting green",
+    "292": "racecourse",
+    "293": "raceway",
+    "294": "raft",
+    "295": "railroad track",
+    "296": "rainforest",
+    "297": "reception",
+    "298": "recreation room",
+    "299": "residential neighborhood",
+    "300": "restaurant",
+    "301": "restaurant kitchen",
+    "302": "restaurant patio",
+    "303": "rice paddy",
+    "304": "riding arena",
+    "305": "river",
+    "306": "rock arch",
+    "307": "rope bridge",
+    "308": "ruin",
+    "309": "runway",
+    "310": "sandbar",
+    "311": "sandbox",
+    "312": "sauna",
+    "313": "schoolhouse",
+    "314": "sea cliff",
+    "315": "server room",
+    "316": "shed",
+    "317": "shoe shop",
+    "318": "shopfront",
+    "319": "shopping mall indoor",
+    "320": "shower",
+    "321": "skatepark",
+    "322": "ski lodge",
+    "323": "ski resort",
+    "324": "ski slope",
+    "325": "sky",
+    "326": "skyscraper",
+    "327": "slum",
+    "328": "snowfield",
+    "329": "squash court",
+    "330": "stable",
+    "331": "stadium baseball",
+    "332": "stadium football",
+    "333": "stage indoor",
+    "334": "staircase",
+    "335": "street",
+    "336": "subway interior",
+    "337": "subway station platform",
+    "338": "supermarket",
+    "339": "sushi bar",
+    "340": "swamp",
+    "341": "swimming pool indoor",
+    "342": "swimming pool outdoor",
+    "343": "synagogue indoor",
+    "344": "synagogue outdoor",
+    "345": "television studio",
+    "346": "temple east asia",
+    "347": "temple south asia",
+    "348": "tennis court indoor",
+    "349": "tennis court outdoor",
+    "350": "tent outdoor",
+    "351": "theater indoor procenium",
+    "352": "theater indoor seats",
+    "353": "thriftshop",
+    "354": "throne room",
+    "355": "ticket booth",
+    "356": "toll plaza",
+    "357": "topiary garden",
+    "358": "tower",
+    "359": "toyshop",
+    "360": "track outdoor",
+    "361": "train railway",
+    "362": "train station platform",
+    "363": "tree farm",
+    "364": "tree house",
+    "365": "trench",
+    "366": "underwater coral reef",
+    "367": "utility room",
+    "368": "valley",
+    "369": "van interior",
+    "370": "vegetable garden",
+    "371": "veranda",
+    "372": "veterinarians office",
+    "373": "viaduct",
+    "374": "videostore",
+    "375": "village",
+    "376": "vineyard",
+    "377": "volcano",
+    "378": "volleyball court indoor",
+    "379": "volleyball court outdoor",
+    "380": "waiting room",
+    "381": "warehouse indoor",
+    "382": "water tower",
+    "383": "waterfall block",
+    "384": "waterfall fan",
+    "385": "waterfall plunge",
+    "386": "watering hole",
+    "387": "wave",
+    "388": "wet bar",
+    "389": "wheat field",
+    "390": "wind farm",
+    "391": "windmill",
+    "392": "wine cellar barrel storage",
+    "393": "wine cellar bottle storage",
+    "394": "wrestling ring indoor",
+    "395": "yard",
+    "396": "youth hostel"
+  },
+  "label2id": {
+    "abbey": 0,
+    "airplane cabin": 1,
+    "airport terminal": 2,
+    "alley": 3,
+    "amphitheater": 4,
+    "amusement arcade": 5,
+    "amusement park": 6,
+    "anechoic chamber": 7,
+    "apartment building outdoor": 8,
+    "apse indoor": 9,
+    "aquarium": 10,
+    "aqueduct": 11,
+    "arch": 12,
+    "archive": 13,
+    "arrival gate outdoor": 14,
+    "art gallery": 15,
+    "art school": 16,
+    "art studio": 17,
+    "assembly line": 18,
+    "athletic field outdoor": 19,
+    "atrium public": 20,
+    "attic": 21,
+    "auditorium": 22,
+    "auto factory": 23,
+    "badlands": 24,
+    "badminton court indoor": 25,
+    "baggage claim": 26,
+    "bakery shop": 27,
+    "balcony exterior": 28,
+    "balcony interior": 29,
+    "ball pit": 30,
+    "ballroom": 31,
+    "bamboo forest": 32,
+    "banquet hall": 33,
+    "bar": 34,
+    "barn": 35,
+    "barndoor": 36,
+    "baseball field": 37,
+    "basement": 38,
+    "basilica": 39,
+    "basketball court outdoor": 40,
+    "bathroom": 41,
+    "batters box": 42,
+    "bayou": 43,
+    "bazaar indoor": 44,
+    "bazaar outdoor": 45,
+    "beach": 46,
+    "beauty salon": 47,
+    "bedroom": 48,
+    "berth": 49,
+    "biology laboratory": 50,
+    "bistro indoor": 51,
+    "boardwalk": 52,
+    "boat deck": 53,
+    "boathouse": 54,
+    "bookstore": 55,
+    "booth indoor": 56,
+    "botanical garden": 57,
+    "bow window indoor": 58,
+    "bow window outdoor": 59,
+    "bowling alley": 60,
+    "boxing ring": 61,
+    "brewery indoor": 62,
+    "bridge": 63,
+    "building facade": 64,
+    "bullring": 65,
+    "burial chamber": 66,
+    "bus interior": 67,
+    "butchers shop": 68,
+    "butte": 69,
+    "cabin outdoor": 70,
+    "cafeteria": 71,
+    "campsite": 72,
+    "campus": 73,
+    "canal natural": 74,
+    "canal urban": 75,
+    "candy store": 76,
+    "canyon": 77,
+    "car interior backseat": 78,
+    "car interior frontseat": 79,
+    "carrousel": 80,
+    "casino indoor": 81,
+    "castle": 82,
+    "catacomb": 83,
+    "cathedral indoor": 84,
+    "cathedral outdoor": 85,
+    "cavern indoor": 86,
+    "cemetery": 87,
+    "chalet": 88,
+    "cheese factory": 89,
+    "chemistry lab": 90,
+    "chicken coop indoor": 91,
+    "chicken coop outdoor": 92,
+    "childs room": 93,
+    "church indoor": 94,
+    "church outdoor": 95,
+    "classroom": 96,
+    "clean room": 97,
+    "cliff": 98,
+    "cloister indoor": 99,
+    "closet": 100,
+    "clothing store": 101,
+    "coast": 102,
+    "cockpit": 103,
+    "coffee shop": 104,
+    "computer room": 105,
+    "conference center": 106,
+    "conference room": 107,
+    "construction site": 108,
+    "control room": 109,
+    "control tower outdoor": 110,
+    "corn field": 111,
+    "corral": 112,
+    "corridor": 113,
+    "cottage garden": 114,
+    "courthouse": 115,
+    "courtroom": 116,
+    "courtyard": 117,
+    "covered bridge exterior": 118,
+    "creek": 119,
+    "crevasse": 120,
+    "crosswalk": 121,
+    "cubicle office": 122,
+    "dam": 123,
+    "delicatessen": 124,
+    "dentists office": 125,
+    "desert sand": 126,
+    "desert vegetation": 127,
+    "diner indoor": 128,
+    "diner outdoor": 129,
+    "dinette home": 130,
+    "dinette vehicle": 131,
+    "dining car": 132,
+    "dining room": 133,
+    "discotheque": 134,
+    "dock": 135,
+    "doorway outdoor": 136,
+    "dorm room": 137,
+    "driveway": 138,
+    "driving range outdoor": 139,
+    "drugstore": 140,
+    "electrical substation": 141,
+    "elevator door": 142,
+    "elevator interior": 143,
+    "elevator shaft": 144,
+    "engine room": 145,
+    "escalator indoor": 146,
+    "excavation": 147,
+    "factory indoor": 148,
+    "fairway": 149,
+    "fastfood restaurant": 150,
+    "field cultivated": 151,
+    "field wild": 152,
+    "fire escape": 153,
+    "fire station": 154,
+    "firing range indoor": 155,
+    "fishpond": 156,
+    "florist shop indoor": 157,
+    "food court": 158,
+    "forest broadleaf": 159,
+    "forest needleleaf": 160,
+    "forest path": 161,
+    "forest road": 162,
+    "formal garden": 163,
+    "fountain": 164,
+    "galley": 165,
+    "game room": 166,
+    "garage indoor": 167,
+    "garbage dump": 168,
+    "gas station": 169,
+    "gazebo exterior": 170,
+    "general store indoor": 171,
+    "general store outdoor": 172,
+    "gift shop": 173,
+    "golf course": 174,
+    "greenhouse indoor": 175,
+    "greenhouse outdoor": 176,
+    "gymnasium indoor": 177,
+    "hangar indoor": 178,
+    "hangar outdoor": 179,
+    "harbor": 180,
+    "hayfield": 181,
+    "heliport": 182,
+    "herb garden": 183,
+    "highway": 184,
+    "hill": 185,
+    "home office": 186,
+    "hospital": 187,
+    "hospital room": 188,
+    "hot spring": 189,
+    "hot tub outdoor": 190,
+    "hotel outdoor": 191,
+    "hotel room": 192,
+    "house": 193,
+    "hunting lodge outdoor": 194,
+    "ice cream parlor": 195,
+    "ice floe": 196,
+    "ice shelf": 197,
+    "ice skating rink indoor": 198,
+    "ice skating rink outdoor": 199,
+    "iceberg": 200,
+    "igloo": 201,
+    "industrial area": 202,
+    "inn outdoor": 203,
+    "islet": 204,
+    "jacuzzi indoor": 205,
+    "jail cell": 206,
+    "jail indoor": 207,
+    "jewelry shop": 208,
+    "kasbah": 209,
+    "kennel indoor": 210,
+    "kennel outdoor": 211,
+    "kindergarden classroom": 212,
+    "kitchen": 213,
+    "kitchenette": 214,
+    "labyrinth outdoor": 215,
+    "lake natural": 216,
+    "landfill": 217,
+    "landing deck": 218,
+    "laundromat": 219,
+    "lecture room": 220,
+    "library indoor": 221,
+    "library outdoor": 222,
+    "lido deck outdoor": 223,
+    "lift bridge": 224,
+    "lighthouse": 225,
+    "limousine interior": 226,
+    "living room": 227,
+    "lobby": 228,
+    "lock chamber": 229,
+    "locker room": 230,
+    "mansion": 231,
+    "manufactured home": 232,
+    "market indoor": 233,
+    "market outdoor": 234,
+    "marsh": 235,
+    "martial arts gym": 236,
+    "mausoleum": 237,
+    "medina": 238,
+    "moat water": 239,
+    "monastery outdoor": 240,
+    "mosque indoor": 241,
+    "mosque outdoor": 242,
+    "motel": 243,
+    "mountain": 244,
+    "mountain snowy": 245,
+    "movie theater indoor": 246,
+    "museum indoor": 247,
+    "music store": 248,
+    "music studio": 249,
+    "nuclear power plant outdoor": 250,
+    "nursery": 251,
+    "oast house": 252,
+    "observatory outdoor": 253,
+    "ocean": 254,
+    "office": 255,
+    "office building": 256,
+    "oil refinery outdoor": 257,
+    "oilrig": 258,
+    "operating room": 259,
+    "orchard": 260,
+    "outhouse outdoor": 261,
+    "pagoda": 262,
+    "palace": 263,
+    "pantry": 264,
+    "park": 265,
+    "parking garage indoor": 266,
+    "parking garage outdoor": 267,
+    "parking lot": 268,
+    "parlor": 269,
+    "pasture": 270,
+    "patio": 271,
+    "pavilion": 272,
+    "pharmacy": 273,
+    "phone booth": 274,
+    "physics laboratory": 275,
+    "picnic area": 276,
+    "pilothouse indoor": 277,
+    "planetarium outdoor": 278,
+    "playground": 279,
+    "playroom": 280,
+    "plaza": 281,
+    "podium indoor": 282,
+    "podium outdoor": 283,
+    "pond": 284,
+    "poolroom establishment": 285,
+    "poolroom home": 286,
+    "power plant outdoor": 287,
+    "promenade deck": 288,
+    "pub indoor": 289,
+    "pulpit": 290,
+    "putting green": 291,
+    "racecourse": 292,
+    "raceway": 293,
+    "raft": 294,
+    "railroad track": 295,
+    "rainforest": 296,
+    "reception": 297,
+    "recreation room": 298,
+    "residential neighborhood": 299,
+    "restaurant": 300,
+    "restaurant kitchen": 301,
+    "restaurant patio": 302,
+    "rice paddy": 303,
+    "riding arena": 304,
+    "river": 305,
+    "rock arch": 306,
+    "rope bridge": 307,
+    "ruin": 308,
+    "runway": 309,
+    "sandbar": 310,
+    "sandbox": 311,
+    "sauna": 312,
+    "schoolhouse": 313,
+    "sea cliff": 314,
+    "server room": 315,
+    "shed": 316,
+    "shoe shop": 317,
+    "shopfront": 318,
+    "shopping mall indoor": 319,
+    "shower": 320,
+    "skatepark": 321,
+    "ski lodge": 322,
+    "ski resort": 323,
+    "ski slope": 324,
+    "sky": 325,
+    "skyscraper": 326,
+    "slum": 327,
+    "snowfield": 328,
+    "squash court": 329,
+    "stable": 330,
+    "stadium baseball": 331,
+    "stadium football": 332,
+    "stage indoor": 333,
+    "staircase": 334,
+    "street": 335,
+    "subway interior": 336,
+    "subway station platform": 337,
+    "supermarket": 338,
+    "sushi bar": 339,
+    "swamp": 340,
+    "swimming pool indoor": 341,
+    "swimming pool outdoor": 342,
+    "synagogue indoor": 343,
+    "synagogue outdoor": 344,
+    "television studio": 345,
+    "temple east asia": 346,
+    "temple south asia": 347,
+    "tennis court indoor": 348,
+    "tennis court outdoor": 349,
+    "tent outdoor": 350,
+    "theater indoor procenium": 351,
+    "theater indoor seats": 352,
+    "thriftshop": 353,
+    "throne room": 354,
+    "ticket booth": 355,
+    "toll plaza": 356,
+    "topiary garden": 357,
+    "tower": 358,
+    "toyshop": 359,
+    "track outdoor": 360,
+    "train railway": 361,
+    "train station platform": 362,
+    "tree farm": 363,
+    "tree house": 364,
+    "trench": 365,
+    "underwater coral reef": 366,
+    "utility room": 367,
+    "valley": 368,
+    "van interior": 369,
+    "vegetable garden": 370,
+    "veranda": 371,
+    "veterinarians office": 372,
+    "viaduct": 373,
+    "videostore": 374,
+    "village": 375,
+    "vineyard": 376,
+    "volcano": 377,
+    "volleyball court indoor": 378,
+    "volleyball court outdoor": 379,
+    "waiting room": 380,
+    "warehouse indoor": 381,
+    "water tower": 382,
+    "waterfall block": 383,
+    "waterfall fan": 384,
+    "waterfall plunge": 385,
+    "watering hole": 386,
+    "wave": 387,
+    "wet bar": 388,
+    "wheat field": 389,
+    "wind farm": 390,
+    "windmill": 391,
+    "wine cellar barrel storage": 392,
+    "wine cellar bottle storage": 393,
+    "wrestling ring indoor": 394,
+    "yard": 395,
+    "youth hostel": 396
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-sun397-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md b/resnet18-sun397-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..bc11163a79204d3e72a9ede61dc474796b64397b
--- /dev/null
+++ b/resnet18-sun397-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset sun397.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: sun397
+    pretrained: true
+test_datasets: null
+train_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: train
+type: transformers
+val_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: test
+```
+
diff --git a/resnet18-sun397-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/config.json b/resnet18-sun397-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..886da3497a7114ff31c2408ec559a773285de738
--- /dev/null
+++ b/resnet18-sun397-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,837 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "abbey",
+    "1": "airplane cabin",
+    "2": "airport terminal",
+    "3": "alley",
+    "4": "amphitheater",
+    "5": "amusement arcade",
+    "6": "amusement park",
+    "7": "anechoic chamber",
+    "8": "apartment building outdoor",
+    "9": "apse indoor",
+    "10": "aquarium",
+    "11": "aqueduct",
+    "12": "arch",
+    "13": "archive",
+    "14": "arrival gate outdoor",
+    "15": "art gallery",
+    "16": "art school",
+    "17": "art studio",
+    "18": "assembly line",
+    "19": "athletic field outdoor",
+    "20": "atrium public",
+    "21": "attic",
+    "22": "auditorium",
+    "23": "auto factory",
+    "24": "badlands",
+    "25": "badminton court indoor",
+    "26": "baggage claim",
+    "27": "bakery shop",
+    "28": "balcony exterior",
+    "29": "balcony interior",
+    "30": "ball pit",
+    "31": "ballroom",
+    "32": "bamboo forest",
+    "33": "banquet hall",
+    "34": "bar",
+    "35": "barn",
+    "36": "barndoor",
+    "37": "baseball field",
+    "38": "basement",
+    "39": "basilica",
+    "40": "basketball court outdoor",
+    "41": "bathroom",
+    "42": "batters box",
+    "43": "bayou",
+    "44": "bazaar indoor",
+    "45": "bazaar outdoor",
+    "46": "beach",
+    "47": "beauty salon",
+    "48": "bedroom",
+    "49": "berth",
+    "50": "biology laboratory",
+    "51": "bistro indoor",
+    "52": "boardwalk",
+    "53": "boat deck",
+    "54": "boathouse",
+    "55": "bookstore",
+    "56": "booth indoor",
+    "57": "botanical garden",
+    "58": "bow window indoor",
+    "59": "bow window outdoor",
+    "60": "bowling alley",
+    "61": "boxing ring",
+    "62": "brewery indoor",
+    "63": "bridge",
+    "64": "building facade",
+    "65": "bullring",
+    "66": "burial chamber",
+    "67": "bus interior",
+    "68": "butchers shop",
+    "69": "butte",
+    "70": "cabin outdoor",
+    "71": "cafeteria",
+    "72": "campsite",
+    "73": "campus",
+    "74": "canal natural",
+    "75": "canal urban",
+    "76": "candy store",
+    "77": "canyon",
+    "78": "car interior backseat",
+    "79": "car interior frontseat",
+    "80": "carrousel",
+    "81": "casino indoor",
+    "82": "castle",
+    "83": "catacomb",
+    "84": "cathedral indoor",
+    "85": "cathedral outdoor",
+    "86": "cavern indoor",
+    "87": "cemetery",
+    "88": "chalet",
+    "89": "cheese factory",
+    "90": "chemistry lab",
+    "91": "chicken coop indoor",
+    "92": "chicken coop outdoor",
+    "93": "childs room",
+    "94": "church indoor",
+    "95": "church outdoor",
+    "96": "classroom",
+    "97": "clean room",
+    "98": "cliff",
+    "99": "cloister indoor",
+    "100": "closet",
+    "101": "clothing store",
+    "102": "coast",
+    "103": "cockpit",
+    "104": "coffee shop",
+    "105": "computer room",
+    "106": "conference center",
+    "107": "conference room",
+    "108": "construction site",
+    "109": "control room",
+    "110": "control tower outdoor",
+    "111": "corn field",
+    "112": "corral",
+    "113": "corridor",
+    "114": "cottage garden",
+    "115": "courthouse",
+    "116": "courtroom",
+    "117": "courtyard",
+    "118": "covered bridge exterior",
+    "119": "creek",
+    "120": "crevasse",
+    "121": "crosswalk",
+    "122": "cubicle office",
+    "123": "dam",
+    "124": "delicatessen",
+    "125": "dentists office",
+    "126": "desert sand",
+    "127": "desert vegetation",
+    "128": "diner indoor",
+    "129": "diner outdoor",
+    "130": "dinette home",
+    "131": "dinette vehicle",
+    "132": "dining car",
+    "133": "dining room",
+    "134": "discotheque",
+    "135": "dock",
+    "136": "doorway outdoor",
+    "137": "dorm room",
+    "138": "driveway",
+    "139": "driving range outdoor",
+    "140": "drugstore",
+    "141": "electrical substation",
+    "142": "elevator door",
+    "143": "elevator interior",
+    "144": "elevator shaft",
+    "145": "engine room",
+    "146": "escalator indoor",
+    "147": "excavation",
+    "148": "factory indoor",
+    "149": "fairway",
+    "150": "fastfood restaurant",
+    "151": "field cultivated",
+    "152": "field wild",
+    "153": "fire escape",
+    "154": "fire station",
+    "155": "firing range indoor",
+    "156": "fishpond",
+    "157": "florist shop indoor",
+    "158": "food court",
+    "159": "forest broadleaf",
+    "160": "forest needleleaf",
+    "161": "forest path",
+    "162": "forest road",
+    "163": "formal garden",
+    "164": "fountain",
+    "165": "galley",
+    "166": "game room",
+    "167": "garage indoor",
+    "168": "garbage dump",
+    "169": "gas station",
+    "170": "gazebo exterior",
+    "171": "general store indoor",
+    "172": "general store outdoor",
+    "173": "gift shop",
+    "174": "golf course",
+    "175": "greenhouse indoor",
+    "176": "greenhouse outdoor",
+    "177": "gymnasium indoor",
+    "178": "hangar indoor",
+    "179": "hangar outdoor",
+    "180": "harbor",
+    "181": "hayfield",
+    "182": "heliport",
+    "183": "herb garden",
+    "184": "highway",
+    "185": "hill",
+    "186": "home office",
+    "187": "hospital",
+    "188": "hospital room",
+    "189": "hot spring",
+    "190": "hot tub outdoor",
+    "191": "hotel outdoor",
+    "192": "hotel room",
+    "193": "house",
+    "194": "hunting lodge outdoor",
+    "195": "ice cream parlor",
+    "196": "ice floe",
+    "197": "ice shelf",
+    "198": "ice skating rink indoor",
+    "199": "ice skating rink outdoor",
+    "200": "iceberg",
+    "201": "igloo",
+    "202": "industrial area",
+    "203": "inn outdoor",
+    "204": "islet",
+    "205": "jacuzzi indoor",
+    "206": "jail cell",
+    "207": "jail indoor",
+    "208": "jewelry shop",
+    "209": "kasbah",
+    "210": "kennel indoor",
+    "211": "kennel outdoor",
+    "212": "kindergarden classroom",
+    "213": "kitchen",
+    "214": "kitchenette",
+    "215": "labyrinth outdoor",
+    "216": "lake natural",
+    "217": "landfill",
+    "218": "landing deck",
+    "219": "laundromat",
+    "220": "lecture room",
+    "221": "library indoor",
+    "222": "library outdoor",
+    "223": "lido deck outdoor",
+    "224": "lift bridge",
+    "225": "lighthouse",
+    "226": "limousine interior",
+    "227": "living room",
+    "228": "lobby",
+    "229": "lock chamber",
+    "230": "locker room",
+    "231": "mansion",
+    "232": "manufactured home",
+    "233": "market indoor",
+    "234": "market outdoor",
+    "235": "marsh",
+    "236": "martial arts gym",
+    "237": "mausoleum",
+    "238": "medina",
+    "239": "moat water",
+    "240": "monastery outdoor",
+    "241": "mosque indoor",
+    "242": "mosque outdoor",
+    "243": "motel",
+    "244": "mountain",
+    "245": "mountain snowy",
+    "246": "movie theater indoor",
+    "247": "museum indoor",
+    "248": "music store",
+    "249": "music studio",
+    "250": "nuclear power plant outdoor",
+    "251": "nursery",
+    "252": "oast house",
+    "253": "observatory outdoor",
+    "254": "ocean",
+    "255": "office",
+    "256": "office building",
+    "257": "oil refinery outdoor",
+    "258": "oilrig",
+    "259": "operating room",
+    "260": "orchard",
+    "261": "outhouse outdoor",
+    "262": "pagoda",
+    "263": "palace",
+    "264": "pantry",
+    "265": "park",
+    "266": "parking garage indoor",
+    "267": "parking garage outdoor",
+    "268": "parking lot",
+    "269": "parlor",
+    "270": "pasture",
+    "271": "patio",
+    "272": "pavilion",
+    "273": "pharmacy",
+    "274": "phone booth",
+    "275": "physics laboratory",
+    "276": "picnic area",
+    "277": "pilothouse indoor",
+    "278": "planetarium outdoor",
+    "279": "playground",
+    "280": "playroom",
+    "281": "plaza",
+    "282": "podium indoor",
+    "283": "podium outdoor",
+    "284": "pond",
+    "285": "poolroom establishment",
+    "286": "poolroom home",
+    "287": "power plant outdoor",
+    "288": "promenade deck",
+    "289": "pub indoor",
+    "290": "pulpit",
+    "291": "putting green",
+    "292": "racecourse",
+    "293": "raceway",
+    "294": "raft",
+    "295": "railroad track",
+    "296": "rainforest",
+    "297": "reception",
+    "298": "recreation room",
+    "299": "residential neighborhood",
+    "300": "restaurant",
+    "301": "restaurant kitchen",
+    "302": "restaurant patio",
+    "303": "rice paddy",
+    "304": "riding arena",
+    "305": "river",
+    "306": "rock arch",
+    "307": "rope bridge",
+    "308": "ruin",
+    "309": "runway",
+    "310": "sandbar",
+    "311": "sandbox",
+    "312": "sauna",
+    "313": "schoolhouse",
+    "314": "sea cliff",
+    "315": "server room",
+    "316": "shed",
+    "317": "shoe shop",
+    "318": "shopfront",
+    "319": "shopping mall indoor",
+    "320": "shower",
+    "321": "skatepark",
+    "322": "ski lodge",
+    "323": "ski resort",
+    "324": "ski slope",
+    "325": "sky",
+    "326": "skyscraper",
+    "327": "slum",
+    "328": "snowfield",
+    "329": "squash court",
+    "330": "stable",
+    "331": "stadium baseball",
+    "332": "stadium football",
+    "333": "stage indoor",
+    "334": "staircase",
+    "335": "street",
+    "336": "subway interior",
+    "337": "subway station platform",
+    "338": "supermarket",
+    "339": "sushi bar",
+    "340": "swamp",
+    "341": "swimming pool indoor",
+    "342": "swimming pool outdoor",
+    "343": "synagogue indoor",
+    "344": "synagogue outdoor",
+    "345": "television studio",
+    "346": "temple east asia",
+    "347": "temple south asia",
+    "348": "tennis court indoor",
+    "349": "tennis court outdoor",
+    "350": "tent outdoor",
+    "351": "theater indoor procenium",
+    "352": "theater indoor seats",
+    "353": "thriftshop",
+    "354": "throne room",
+    "355": "ticket booth",
+    "356": "toll plaza",
+    "357": "topiary garden",
+    "358": "tower",
+    "359": "toyshop",
+    "360": "track outdoor",
+    "361": "train railway",
+    "362": "train station platform",
+    "363": "tree farm",
+    "364": "tree house",
+    "365": "trench",
+    "366": "underwater coral reef",
+    "367": "utility room",
+    "368": "valley",
+    "369": "van interior",
+    "370": "vegetable garden",
+    "371": "veranda",
+    "372": "veterinarians office",
+    "373": "viaduct",
+    "374": "videostore",
+    "375": "village",
+    "376": "vineyard",
+    "377": "volcano",
+    "378": "volleyball court indoor",
+    "379": "volleyball court outdoor",
+    "380": "waiting room",
+    "381": "warehouse indoor",
+    "382": "water tower",
+    "383": "waterfall block",
+    "384": "waterfall fan",
+    "385": "waterfall plunge",
+    "386": "watering hole",
+    "387": "wave",
+    "388": "wet bar",
+    "389": "wheat field",
+    "390": "wind farm",
+    "391": "windmill",
+    "392": "wine cellar barrel storage",
+    "393": "wine cellar bottle storage",
+    "394": "wrestling ring indoor",
+    "395": "yard",
+    "396": "youth hostel"
+  },
+  "label2id": {
+    "abbey": 0,
+    "airplane cabin": 1,
+    "airport terminal": 2,
+    "alley": 3,
+    "amphitheater": 4,
+    "amusement arcade": 5,
+    "amusement park": 6,
+    "anechoic chamber": 7,
+    "apartment building outdoor": 8,
+    "apse indoor": 9,
+    "aquarium": 10,
+    "aqueduct": 11,
+    "arch": 12,
+    "archive": 13,
+    "arrival gate outdoor": 14,
+    "art gallery": 15,
+    "art school": 16,
+    "art studio": 17,
+    "assembly line": 18,
+    "athletic field outdoor": 19,
+    "atrium public": 20,
+    "attic": 21,
+    "auditorium": 22,
+    "auto factory": 23,
+    "badlands": 24,
+    "badminton court indoor": 25,
+    "baggage claim": 26,
+    "bakery shop": 27,
+    "balcony exterior": 28,
+    "balcony interior": 29,
+    "ball pit": 30,
+    "ballroom": 31,
+    "bamboo forest": 32,
+    "banquet hall": 33,
+    "bar": 34,
+    "barn": 35,
+    "barndoor": 36,
+    "baseball field": 37,
+    "basement": 38,
+    "basilica": 39,
+    "basketball court outdoor": 40,
+    "bathroom": 41,
+    "batters box": 42,
+    "bayou": 43,
+    "bazaar indoor": 44,
+    "bazaar outdoor": 45,
+    "beach": 46,
+    "beauty salon": 47,
+    "bedroom": 48,
+    "berth": 49,
+    "biology laboratory": 50,
+    "bistro indoor": 51,
+    "boardwalk": 52,
+    "boat deck": 53,
+    "boathouse": 54,
+    "bookstore": 55,
+    "booth indoor": 56,
+    "botanical garden": 57,
+    "bow window indoor": 58,
+    "bow window outdoor": 59,
+    "bowling alley": 60,
+    "boxing ring": 61,
+    "brewery indoor": 62,
+    "bridge": 63,
+    "building facade": 64,
+    "bullring": 65,
+    "burial chamber": 66,
+    "bus interior": 67,
+    "butchers shop": 68,
+    "butte": 69,
+    "cabin outdoor": 70,
+    "cafeteria": 71,
+    "campsite": 72,
+    "campus": 73,
+    "canal natural": 74,
+    "canal urban": 75,
+    "candy store": 76,
+    "canyon": 77,
+    "car interior backseat": 78,
+    "car interior frontseat": 79,
+    "carrousel": 80,
+    "casino indoor": 81,
+    "castle": 82,
+    "catacomb": 83,
+    "cathedral indoor": 84,
+    "cathedral outdoor": 85,
+    "cavern indoor": 86,
+    "cemetery": 87,
+    "chalet": 88,
+    "cheese factory": 89,
+    "chemistry lab": 90,
+    "chicken coop indoor": 91,
+    "chicken coop outdoor": 92,
+    "childs room": 93,
+    "church indoor": 94,
+    "church outdoor": 95,
+    "classroom": 96,
+    "clean room": 97,
+    "cliff": 98,
+    "cloister indoor": 99,
+    "closet": 100,
+    "clothing store": 101,
+    "coast": 102,
+    "cockpit": 103,
+    "coffee shop": 104,
+    "computer room": 105,
+    "conference center": 106,
+    "conference room": 107,
+    "construction site": 108,
+    "control room": 109,
+    "control tower outdoor": 110,
+    "corn field": 111,
+    "corral": 112,
+    "corridor": 113,
+    "cottage garden": 114,
+    "courthouse": 115,
+    "courtroom": 116,
+    "courtyard": 117,
+    "covered bridge exterior": 118,
+    "creek": 119,
+    "crevasse": 120,
+    "crosswalk": 121,
+    "cubicle office": 122,
+    "dam": 123,
+    "delicatessen": 124,
+    "dentists office": 125,
+    "desert sand": 126,
+    "desert vegetation": 127,
+    "diner indoor": 128,
+    "diner outdoor": 129,
+    "dinette home": 130,
+    "dinette vehicle": 131,
+    "dining car": 132,
+    "dining room": 133,
+    "discotheque": 134,
+    "dock": 135,
+    "doorway outdoor": 136,
+    "dorm room": 137,
+    "driveway": 138,
+    "driving range outdoor": 139,
+    "drugstore": 140,
+    "electrical substation": 141,
+    "elevator door": 142,
+    "elevator interior": 143,
+    "elevator shaft": 144,
+    "engine room": 145,
+    "escalator indoor": 146,
+    "excavation": 147,
+    "factory indoor": 148,
+    "fairway": 149,
+    "fastfood restaurant": 150,
+    "field cultivated": 151,
+    "field wild": 152,
+    "fire escape": 153,
+    "fire station": 154,
+    "firing range indoor": 155,
+    "fishpond": 156,
+    "florist shop indoor": 157,
+    "food court": 158,
+    "forest broadleaf": 159,
+    "forest needleleaf": 160,
+    "forest path": 161,
+    "forest road": 162,
+    "formal garden": 163,
+    "fountain": 164,
+    "galley": 165,
+    "game room": 166,
+    "garage indoor": 167,
+    "garbage dump": 168,
+    "gas station": 169,
+    "gazebo exterior": 170,
+    "general store indoor": 171,
+    "general store outdoor": 172,
+    "gift shop": 173,
+    "golf course": 174,
+    "greenhouse indoor": 175,
+    "greenhouse outdoor": 176,
+    "gymnasium indoor": 177,
+    "hangar indoor": 178,
+    "hangar outdoor": 179,
+    "harbor": 180,
+    "hayfield": 181,
+    "heliport": 182,
+    "herb garden": 183,
+    "highway": 184,
+    "hill": 185,
+    "home office": 186,
+    "hospital": 187,
+    "hospital room": 188,
+    "hot spring": 189,
+    "hot tub outdoor": 190,
+    "hotel outdoor": 191,
+    "hotel room": 192,
+    "house": 193,
+    "hunting lodge outdoor": 194,
+    "ice cream parlor": 195,
+    "ice floe": 196,
+    "ice shelf": 197,
+    "ice skating rink indoor": 198,
+    "ice skating rink outdoor": 199,
+    "iceberg": 200,
+    "igloo": 201,
+    "industrial area": 202,
+    "inn outdoor": 203,
+    "islet": 204,
+    "jacuzzi indoor": 205,
+    "jail cell": 206,
+    "jail indoor": 207,
+    "jewelry shop": 208,
+    "kasbah": 209,
+    "kennel indoor": 210,
+    "kennel outdoor": 211,
+    "kindergarden classroom": 212,
+    "kitchen": 213,
+    "kitchenette": 214,
+    "labyrinth outdoor": 215,
+    "lake natural": 216,
+    "landfill": 217,
+    "landing deck": 218,
+    "laundromat": 219,
+    "lecture room": 220,
+    "library indoor": 221,
+    "library outdoor": 222,
+    "lido deck outdoor": 223,
+    "lift bridge": 224,
+    "lighthouse": 225,
+    "limousine interior": 226,
+    "living room": 227,
+    "lobby": 228,
+    "lock chamber": 229,
+    "locker room": 230,
+    "mansion": 231,
+    "manufactured home": 232,
+    "market indoor": 233,
+    "market outdoor": 234,
+    "marsh": 235,
+    "martial arts gym": 236,
+    "mausoleum": 237,
+    "medina": 238,
+    "moat water": 239,
+    "monastery outdoor": 240,
+    "mosque indoor": 241,
+    "mosque outdoor": 242,
+    "motel": 243,
+    "mountain": 244,
+    "mountain snowy": 245,
+    "movie theater indoor": 246,
+    "museum indoor": 247,
+    "music store": 248,
+    "music studio": 249,
+    "nuclear power plant outdoor": 250,
+    "nursery": 251,
+    "oast house": 252,
+    "observatory outdoor": 253,
+    "ocean": 254,
+    "office": 255,
+    "office building": 256,
+    "oil refinery outdoor": 257,
+    "oilrig": 258,
+    "operating room": 259,
+    "orchard": 260,
+    "outhouse outdoor": 261,
+    "pagoda": 262,
+    "palace": 263,
+    "pantry": 264,
+    "park": 265,
+    "parking garage indoor": 266,
+    "parking garage outdoor": 267,
+    "parking lot": 268,
+    "parlor": 269,
+    "pasture": 270,
+    "patio": 271,
+    "pavilion": 272,
+    "pharmacy": 273,
+    "phone booth": 274,
+    "physics laboratory": 275,
+    "picnic area": 276,
+    "pilothouse indoor": 277,
+    "planetarium outdoor": 278,
+    "playground": 279,
+    "playroom": 280,
+    "plaza": 281,
+    "podium indoor": 282,
+    "podium outdoor": 283,
+    "pond": 284,
+    "poolroom establishment": 285,
+    "poolroom home": 286,
+    "power plant outdoor": 287,
+    "promenade deck": 288,
+    "pub indoor": 289,
+    "pulpit": 290,
+    "putting green": 291,
+    "racecourse": 292,
+    "raceway": 293,
+    "raft": 294,
+    "railroad track": 295,
+    "rainforest": 296,
+    "reception": 297,
+    "recreation room": 298,
+    "residential neighborhood": 299,
+    "restaurant": 300,
+    "restaurant kitchen": 301,
+    "restaurant patio": 302,
+    "rice paddy": 303,
+    "riding arena": 304,
+    "river": 305,
+    "rock arch": 306,
+    "rope bridge": 307,
+    "ruin": 308,
+    "runway": 309,
+    "sandbar": 310,
+    "sandbox": 311,
+    "sauna": 312,
+    "schoolhouse": 313,
+    "sea cliff": 314,
+    "server room": 315,
+    "shed": 316,
+    "shoe shop": 317,
+    "shopfront": 318,
+    "shopping mall indoor": 319,
+    "shower": 320,
+    "skatepark": 321,
+    "ski lodge": 322,
+    "ski resort": 323,
+    "ski slope": 324,
+    "sky": 325,
+    "skyscraper": 326,
+    "slum": 327,
+    "snowfield": 328,
+    "squash court": 329,
+    "stable": 330,
+    "stadium baseball": 331,
+    "stadium football": 332,
+    "stage indoor": 333,
+    "staircase": 334,
+    "street": 335,
+    "subway interior": 336,
+    "subway station platform": 337,
+    "supermarket": 338,
+    "sushi bar": 339,
+    "swamp": 340,
+    "swimming pool indoor": 341,
+    "swimming pool outdoor": 342,
+    "synagogue indoor": 343,
+    "synagogue outdoor": 344,
+    "television studio": 345,
+    "temple east asia": 346,
+    "temple south asia": 347,
+    "tennis court indoor": 348,
+    "tennis court outdoor": 349,
+    "tent outdoor": 350,
+    "theater indoor procenium": 351,
+    "theater indoor seats": 352,
+    "thriftshop": 353,
+    "throne room": 354,
+    "ticket booth": 355,
+    "toll plaza": 356,
+    "topiary garden": 357,
+    "tower": 358,
+    "toyshop": 359,
+    "track outdoor": 360,
+    "train railway": 361,
+    "train station platform": 362,
+    "tree farm": 363,
+    "tree house": 364,
+    "trench": 365,
+    "underwater coral reef": 366,
+    "utility room": 367,
+    "valley": 368,
+    "van interior": 369,
+    "vegetable garden": 370,
+    "veranda": 371,
+    "veterinarians office": 372,
+    "viaduct": 373,
+    "videostore": 374,
+    "village": 375,
+    "vineyard": 376,
+    "volcano": 377,
+    "volleyball court indoor": 378,
+    "volleyball court outdoor": 379,
+    "waiting room": 380,
+    "warehouse indoor": 381,
+    "water tower": 382,
+    "waterfall block": 383,
+    "waterfall fan": 384,
+    "waterfall plunge": 385,
+    "watering hole": 386,
+    "wave": 387,
+    "wet bar": 388,
+    "wheat field": 389,
+    "wind farm": 390,
+    "windmill": 391,
+    "wine cellar barrel storage": 392,
+    "wine cellar bottle storage": 393,
+    "wrestling ring indoor": 394,
+    "yard": 395,
+    "youth hostel": 396
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-sun397-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet18-sun397-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-sun397-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-sun397-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/README.md b/resnet18-sun397-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..20edde2444e951b4f42a46372b344768ae552a16
--- /dev/null
+++ b/resnet18-sun397-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset sun397.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: sun397
+    pretrained: true
+test_datasets: null
+train_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: train
+type: transformers
+val_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: test
+```
+
diff --git a/resnet18-sun397-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/config.json b/resnet18-sun397-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..886da3497a7114ff31c2408ec559a773285de738
--- /dev/null
+++ b/resnet18-sun397-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,837 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "abbey",
+    "1": "airplane cabin",
+    "2": "airport terminal",
+    "3": "alley",
+    "4": "amphitheater",
+    "5": "amusement arcade",
+    "6": "amusement park",
+    "7": "anechoic chamber",
+    "8": "apartment building outdoor",
+    "9": "apse indoor",
+    "10": "aquarium",
+    "11": "aqueduct",
+    "12": "arch",
+    "13": "archive",
+    "14": "arrival gate outdoor",
+    "15": "art gallery",
+    "16": "art school",
+    "17": "art studio",
+    "18": "assembly line",
+    "19": "athletic field outdoor",
+    "20": "atrium public",
+    "21": "attic",
+    "22": "auditorium",
+    "23": "auto factory",
+    "24": "badlands",
+    "25": "badminton court indoor",
+    "26": "baggage claim",
+    "27": "bakery shop",
+    "28": "balcony exterior",
+    "29": "balcony interior",
+    "30": "ball pit",
+    "31": "ballroom",
+    "32": "bamboo forest",
+    "33": "banquet hall",
+    "34": "bar",
+    "35": "barn",
+    "36": "barndoor",
+    "37": "baseball field",
+    "38": "basement",
+    "39": "basilica",
+    "40": "basketball court outdoor",
+    "41": "bathroom",
+    "42": "batters box",
+    "43": "bayou",
+    "44": "bazaar indoor",
+    "45": "bazaar outdoor",
+    "46": "beach",
+    "47": "beauty salon",
+    "48": "bedroom",
+    "49": "berth",
+    "50": "biology laboratory",
+    "51": "bistro indoor",
+    "52": "boardwalk",
+    "53": "boat deck",
+    "54": "boathouse",
+    "55": "bookstore",
+    "56": "booth indoor",
+    "57": "botanical garden",
+    "58": "bow window indoor",
+    "59": "bow window outdoor",
+    "60": "bowling alley",
+    "61": "boxing ring",
+    "62": "brewery indoor",
+    "63": "bridge",
+    "64": "building facade",
+    "65": "bullring",
+    "66": "burial chamber",
+    "67": "bus interior",
+    "68": "butchers shop",
+    "69": "butte",
+    "70": "cabin outdoor",
+    "71": "cafeteria",
+    "72": "campsite",
+    "73": "campus",
+    "74": "canal natural",
+    "75": "canal urban",
+    "76": "candy store",
+    "77": "canyon",
+    "78": "car interior backseat",
+    "79": "car interior frontseat",
+    "80": "carrousel",
+    "81": "casino indoor",
+    "82": "castle",
+    "83": "catacomb",
+    "84": "cathedral indoor",
+    "85": "cathedral outdoor",
+    "86": "cavern indoor",
+    "87": "cemetery",
+    "88": "chalet",
+    "89": "cheese factory",
+    "90": "chemistry lab",
+    "91": "chicken coop indoor",
+    "92": "chicken coop outdoor",
+    "93": "childs room",
+    "94": "church indoor",
+    "95": "church outdoor",
+    "96": "classroom",
+    "97": "clean room",
+    "98": "cliff",
+    "99": "cloister indoor",
+    "100": "closet",
+    "101": "clothing store",
+    "102": "coast",
+    "103": "cockpit",
+    "104": "coffee shop",
+    "105": "computer room",
+    "106": "conference center",
+    "107": "conference room",
+    "108": "construction site",
+    "109": "control room",
+    "110": "control tower outdoor",
+    "111": "corn field",
+    "112": "corral",
+    "113": "corridor",
+    "114": "cottage garden",
+    "115": "courthouse",
+    "116": "courtroom",
+    "117": "courtyard",
+    "118": "covered bridge exterior",
+    "119": "creek",
+    "120": "crevasse",
+    "121": "crosswalk",
+    "122": "cubicle office",
+    "123": "dam",
+    "124": "delicatessen",
+    "125": "dentists office",
+    "126": "desert sand",
+    "127": "desert vegetation",
+    "128": "diner indoor",
+    "129": "diner outdoor",
+    "130": "dinette home",
+    "131": "dinette vehicle",
+    "132": "dining car",
+    "133": "dining room",
+    "134": "discotheque",
+    "135": "dock",
+    "136": "doorway outdoor",
+    "137": "dorm room",
+    "138": "driveway",
+    "139": "driving range outdoor",
+    "140": "drugstore",
+    "141": "electrical substation",
+    "142": "elevator door",
+    "143": "elevator interior",
+    "144": "elevator shaft",
+    "145": "engine room",
+    "146": "escalator indoor",
+    "147": "excavation",
+    "148": "factory indoor",
+    "149": "fairway",
+    "150": "fastfood restaurant",
+    "151": "field cultivated",
+    "152": "field wild",
+    "153": "fire escape",
+    "154": "fire station",
+    "155": "firing range indoor",
+    "156": "fishpond",
+    "157": "florist shop indoor",
+    "158": "food court",
+    "159": "forest broadleaf",
+    "160": "forest needleleaf",
+    "161": "forest path",
+    "162": "forest road",
+    "163": "formal garden",
+    "164": "fountain",
+    "165": "galley",
+    "166": "game room",
+    "167": "garage indoor",
+    "168": "garbage dump",
+    "169": "gas station",
+    "170": "gazebo exterior",
+    "171": "general store indoor",
+    "172": "general store outdoor",
+    "173": "gift shop",
+    "174": "golf course",
+    "175": "greenhouse indoor",
+    "176": "greenhouse outdoor",
+    "177": "gymnasium indoor",
+    "178": "hangar indoor",
+    "179": "hangar outdoor",
+    "180": "harbor",
+    "181": "hayfield",
+    "182": "heliport",
+    "183": "herb garden",
+    "184": "highway",
+    "185": "hill",
+    "186": "home office",
+    "187": "hospital",
+    "188": "hospital room",
+    "189": "hot spring",
+    "190": "hot tub outdoor",
+    "191": "hotel outdoor",
+    "192": "hotel room",
+    "193": "house",
+    "194": "hunting lodge outdoor",
+    "195": "ice cream parlor",
+    "196": "ice floe",
+    "197": "ice shelf",
+    "198": "ice skating rink indoor",
+    "199": "ice skating rink outdoor",
+    "200": "iceberg",
+    "201": "igloo",
+    "202": "industrial area",
+    "203": "inn outdoor",
+    "204": "islet",
+    "205": "jacuzzi indoor",
+    "206": "jail cell",
+    "207": "jail indoor",
+    "208": "jewelry shop",
+    "209": "kasbah",
+    "210": "kennel indoor",
+    "211": "kennel outdoor",
+    "212": "kindergarden classroom",
+    "213": "kitchen",
+    "214": "kitchenette",
+    "215": "labyrinth outdoor",
+    "216": "lake natural",
+    "217": "landfill",
+    "218": "landing deck",
+    "219": "laundromat",
+    "220": "lecture room",
+    "221": "library indoor",
+    "222": "library outdoor",
+    "223": "lido deck outdoor",
+    "224": "lift bridge",
+    "225": "lighthouse",
+    "226": "limousine interior",
+    "227": "living room",
+    "228": "lobby",
+    "229": "lock chamber",
+    "230": "locker room",
+    "231": "mansion",
+    "232": "manufactured home",
+    "233": "market indoor",
+    "234": "market outdoor",
+    "235": "marsh",
+    "236": "martial arts gym",
+    "237": "mausoleum",
+    "238": "medina",
+    "239": "moat water",
+    "240": "monastery outdoor",
+    "241": "mosque indoor",
+    "242": "mosque outdoor",
+    "243": "motel",
+    "244": "mountain",
+    "245": "mountain snowy",
+    "246": "movie theater indoor",
+    "247": "museum indoor",
+    "248": "music store",
+    "249": "music studio",
+    "250": "nuclear power plant outdoor",
+    "251": "nursery",
+    "252": "oast house",
+    "253": "observatory outdoor",
+    "254": "ocean",
+    "255": "office",
+    "256": "office building",
+    "257": "oil refinery outdoor",
+    "258": "oilrig",
+    "259": "operating room",
+    "260": "orchard",
+    "261": "outhouse outdoor",
+    "262": "pagoda",
+    "263": "palace",
+    "264": "pantry",
+    "265": "park",
+    "266": "parking garage indoor",
+    "267": "parking garage outdoor",
+    "268": "parking lot",
+    "269": "parlor",
+    "270": "pasture",
+    "271": "patio",
+    "272": "pavilion",
+    "273": "pharmacy",
+    "274": "phone booth",
+    "275": "physics laboratory",
+    "276": "picnic area",
+    "277": "pilothouse indoor",
+    "278": "planetarium outdoor",
+    "279": "playground",
+    "280": "playroom",
+    "281": "plaza",
+    "282": "podium indoor",
+    "283": "podium outdoor",
+    "284": "pond",
+    "285": "poolroom establishment",
+    "286": "poolroom home",
+    "287": "power plant outdoor",
+    "288": "promenade deck",
+    "289": "pub indoor",
+    "290": "pulpit",
+    "291": "putting green",
+    "292": "racecourse",
+    "293": "raceway",
+    "294": "raft",
+    "295": "railroad track",
+    "296": "rainforest",
+    "297": "reception",
+    "298": "recreation room",
+    "299": "residential neighborhood",
+    "300": "restaurant",
+    "301": "restaurant kitchen",
+    "302": "restaurant patio",
+    "303": "rice paddy",
+    "304": "riding arena",
+    "305": "river",
+    "306": "rock arch",
+    "307": "rope bridge",
+    "308": "ruin",
+    "309": "runway",
+    "310": "sandbar",
+    "311": "sandbox",
+    "312": "sauna",
+    "313": "schoolhouse",
+    "314": "sea cliff",
+    "315": "server room",
+    "316": "shed",
+    "317": "shoe shop",
+    "318": "shopfront",
+    "319": "shopping mall indoor",
+    "320": "shower",
+    "321": "skatepark",
+    "322": "ski lodge",
+    "323": "ski resort",
+    "324": "ski slope",
+    "325": "sky",
+    "326": "skyscraper",
+    "327": "slum",
+    "328": "snowfield",
+    "329": "squash court",
+    "330": "stable",
+    "331": "stadium baseball",
+    "332": "stadium football",
+    "333": "stage indoor",
+    "334": "staircase",
+    "335": "street",
+    "336": "subway interior",
+    "337": "subway station platform",
+    "338": "supermarket",
+    "339": "sushi bar",
+    "340": "swamp",
+    "341": "swimming pool indoor",
+    "342": "swimming pool outdoor",
+    "343": "synagogue indoor",
+    "344": "synagogue outdoor",
+    "345": "television studio",
+    "346": "temple east asia",
+    "347": "temple south asia",
+    "348": "tennis court indoor",
+    "349": "tennis court outdoor",
+    "350": "tent outdoor",
+    "351": "theater indoor procenium",
+    "352": "theater indoor seats",
+    "353": "thriftshop",
+    "354": "throne room",
+    "355": "ticket booth",
+    "356": "toll plaza",
+    "357": "topiary garden",
+    "358": "tower",
+    "359": "toyshop",
+    "360": "track outdoor",
+    "361": "train railway",
+    "362": "train station platform",
+    "363": "tree farm",
+    "364": "tree house",
+    "365": "trench",
+    "366": "underwater coral reef",
+    "367": "utility room",
+    "368": "valley",
+    "369": "van interior",
+    "370": "vegetable garden",
+    "371": "veranda",
+    "372": "veterinarians office",
+    "373": "viaduct",
+    "374": "videostore",
+    "375": "village",
+    "376": "vineyard",
+    "377": "volcano",
+    "378": "volleyball court indoor",
+    "379": "volleyball court outdoor",
+    "380": "waiting room",
+    "381": "warehouse indoor",
+    "382": "water tower",
+    "383": "waterfall block",
+    "384": "waterfall fan",
+    "385": "waterfall plunge",
+    "386": "watering hole",
+    "387": "wave",
+    "388": "wet bar",
+    "389": "wheat field",
+    "390": "wind farm",
+    "391": "windmill",
+    "392": "wine cellar barrel storage",
+    "393": "wine cellar bottle storage",
+    "394": "wrestling ring indoor",
+    "395": "yard",
+    "396": "youth hostel"
+  },
+  "label2id": {
+    "abbey": 0,
+    "airplane cabin": 1,
+    "airport terminal": 2,
+    "alley": 3,
+    "amphitheater": 4,
+    "amusement arcade": 5,
+    "amusement park": 6,
+    "anechoic chamber": 7,
+    "apartment building outdoor": 8,
+    "apse indoor": 9,
+    "aquarium": 10,
+    "aqueduct": 11,
+    "arch": 12,
+    "archive": 13,
+    "arrival gate outdoor": 14,
+    "art gallery": 15,
+    "art school": 16,
+    "art studio": 17,
+    "assembly line": 18,
+    "athletic field outdoor": 19,
+    "atrium public": 20,
+    "attic": 21,
+    "auditorium": 22,
+    "auto factory": 23,
+    "badlands": 24,
+    "badminton court indoor": 25,
+    "baggage claim": 26,
+    "bakery shop": 27,
+    "balcony exterior": 28,
+    "balcony interior": 29,
+    "ball pit": 30,
+    "ballroom": 31,
+    "bamboo forest": 32,
+    "banquet hall": 33,
+    "bar": 34,
+    "barn": 35,
+    "barndoor": 36,
+    "baseball field": 37,
+    "basement": 38,
+    "basilica": 39,
+    "basketball court outdoor": 40,
+    "bathroom": 41,
+    "batters box": 42,
+    "bayou": 43,
+    "bazaar indoor": 44,
+    "bazaar outdoor": 45,
+    "beach": 46,
+    "beauty salon": 47,
+    "bedroom": 48,
+    "berth": 49,
+    "biology laboratory": 50,
+    "bistro indoor": 51,
+    "boardwalk": 52,
+    "boat deck": 53,
+    "boathouse": 54,
+    "bookstore": 55,
+    "booth indoor": 56,
+    "botanical garden": 57,
+    "bow window indoor": 58,
+    "bow window outdoor": 59,
+    "bowling alley": 60,
+    "boxing ring": 61,
+    "brewery indoor": 62,
+    "bridge": 63,
+    "building facade": 64,
+    "bullring": 65,
+    "burial chamber": 66,
+    "bus interior": 67,
+    "butchers shop": 68,
+    "butte": 69,
+    "cabin outdoor": 70,
+    "cafeteria": 71,
+    "campsite": 72,
+    "campus": 73,
+    "canal natural": 74,
+    "canal urban": 75,
+    "candy store": 76,
+    "canyon": 77,
+    "car interior backseat": 78,
+    "car interior frontseat": 79,
+    "carrousel": 80,
+    "casino indoor": 81,
+    "castle": 82,
+    "catacomb": 83,
+    "cathedral indoor": 84,
+    "cathedral outdoor": 85,
+    "cavern indoor": 86,
+    "cemetery": 87,
+    "chalet": 88,
+    "cheese factory": 89,
+    "chemistry lab": 90,
+    "chicken coop indoor": 91,
+    "chicken coop outdoor": 92,
+    "childs room": 93,
+    "church indoor": 94,
+    "church outdoor": 95,
+    "classroom": 96,
+    "clean room": 97,
+    "cliff": 98,
+    "cloister indoor": 99,
+    "closet": 100,
+    "clothing store": 101,
+    "coast": 102,
+    "cockpit": 103,
+    "coffee shop": 104,
+    "computer room": 105,
+    "conference center": 106,
+    "conference room": 107,
+    "construction site": 108,
+    "control room": 109,
+    "control tower outdoor": 110,
+    "corn field": 111,
+    "corral": 112,
+    "corridor": 113,
+    "cottage garden": 114,
+    "courthouse": 115,
+    "courtroom": 116,
+    "courtyard": 117,
+    "covered bridge exterior": 118,
+    "creek": 119,
+    "crevasse": 120,
+    "crosswalk": 121,
+    "cubicle office": 122,
+    "dam": 123,
+    "delicatessen": 124,
+    "dentists office": 125,
+    "desert sand": 126,
+    "desert vegetation": 127,
+    "diner indoor": 128,
+    "diner outdoor": 129,
+    "dinette home": 130,
+    "dinette vehicle": 131,
+    "dining car": 132,
+    "dining room": 133,
+    "discotheque": 134,
+    "dock": 135,
+    "doorway outdoor": 136,
+    "dorm room": 137,
+    "driveway": 138,
+    "driving range outdoor": 139,
+    "drugstore": 140,
+    "electrical substation": 141,
+    "elevator door": 142,
+    "elevator interior": 143,
+    "elevator shaft": 144,
+    "engine room": 145,
+    "escalator indoor": 146,
+    "excavation": 147,
+    "factory indoor": 148,
+    "fairway": 149,
+    "fastfood restaurant": 150,
+    "field cultivated": 151,
+    "field wild": 152,
+    "fire escape": 153,
+    "fire station": 154,
+    "firing range indoor": 155,
+    "fishpond": 156,
+    "florist shop indoor": 157,
+    "food court": 158,
+    "forest broadleaf": 159,
+    "forest needleleaf": 160,
+    "forest path": 161,
+    "forest road": 162,
+    "formal garden": 163,
+    "fountain": 164,
+    "galley": 165,
+    "game room": 166,
+    "garage indoor": 167,
+    "garbage dump": 168,
+    "gas station": 169,
+    "gazebo exterior": 170,
+    "general store indoor": 171,
+    "general store outdoor": 172,
+    "gift shop": 173,
+    "golf course": 174,
+    "greenhouse indoor": 175,
+    "greenhouse outdoor": 176,
+    "gymnasium indoor": 177,
+    "hangar indoor": 178,
+    "hangar outdoor": 179,
+    "harbor": 180,
+    "hayfield": 181,
+    "heliport": 182,
+    "herb garden": 183,
+    "highway": 184,
+    "hill": 185,
+    "home office": 186,
+    "hospital": 187,
+    "hospital room": 188,
+    "hot spring": 189,
+    "hot tub outdoor": 190,
+    "hotel outdoor": 191,
+    "hotel room": 192,
+    "house": 193,
+    "hunting lodge outdoor": 194,
+    "ice cream parlor": 195,
+    "ice floe": 196,
+    "ice shelf": 197,
+    "ice skating rink indoor": 198,
+    "ice skating rink outdoor": 199,
+    "iceberg": 200,
+    "igloo": 201,
+    "industrial area": 202,
+    "inn outdoor": 203,
+    "islet": 204,
+    "jacuzzi indoor": 205,
+    "jail cell": 206,
+    "jail indoor": 207,
+    "jewelry shop": 208,
+    "kasbah": 209,
+    "kennel indoor": 210,
+    "kennel outdoor": 211,
+    "kindergarden classroom": 212,
+    "kitchen": 213,
+    "kitchenette": 214,
+    "labyrinth outdoor": 215,
+    "lake natural": 216,
+    "landfill": 217,
+    "landing deck": 218,
+    "laundromat": 219,
+    "lecture room": 220,
+    "library indoor": 221,
+    "library outdoor": 222,
+    "lido deck outdoor": 223,
+    "lift bridge": 224,
+    "lighthouse": 225,
+    "limousine interior": 226,
+    "living room": 227,
+    "lobby": 228,
+    "lock chamber": 229,
+    "locker room": 230,
+    "mansion": 231,
+    "manufactured home": 232,
+    "market indoor": 233,
+    "market outdoor": 234,
+    "marsh": 235,
+    "martial arts gym": 236,
+    "mausoleum": 237,
+    "medina": 238,
+    "moat water": 239,
+    "monastery outdoor": 240,
+    "mosque indoor": 241,
+    "mosque outdoor": 242,
+    "motel": 243,
+    "mountain": 244,
+    "mountain snowy": 245,
+    "movie theater indoor": 246,
+    "museum indoor": 247,
+    "music store": 248,
+    "music studio": 249,
+    "nuclear power plant outdoor": 250,
+    "nursery": 251,
+    "oast house": 252,
+    "observatory outdoor": 253,
+    "ocean": 254,
+    "office": 255,
+    "office building": 256,
+    "oil refinery outdoor": 257,
+    "oilrig": 258,
+    "operating room": 259,
+    "orchard": 260,
+    "outhouse outdoor": 261,
+    "pagoda": 262,
+    "palace": 263,
+    "pantry": 264,
+    "park": 265,
+    "parking garage indoor": 266,
+    "parking garage outdoor": 267,
+    "parking lot": 268,
+    "parlor": 269,
+    "pasture": 270,
+    "patio": 271,
+    "pavilion": 272,
+    "pharmacy": 273,
+    "phone booth": 274,
+    "physics laboratory": 275,
+    "picnic area": 276,
+    "pilothouse indoor": 277,
+    "planetarium outdoor": 278,
+    "playground": 279,
+    "playroom": 280,
+    "plaza": 281,
+    "podium indoor": 282,
+    "podium outdoor": 283,
+    "pond": 284,
+    "poolroom establishment": 285,
+    "poolroom home": 286,
+    "power plant outdoor": 287,
+    "promenade deck": 288,
+    "pub indoor": 289,
+    "pulpit": 290,
+    "putting green": 291,
+    "racecourse": 292,
+    "raceway": 293,
+    "raft": 294,
+    "railroad track": 295,
+    "rainforest": 296,
+    "reception": 297,
+    "recreation room": 298,
+    "residential neighborhood": 299,
+    "restaurant": 300,
+    "restaurant kitchen": 301,
+    "restaurant patio": 302,
+    "rice paddy": 303,
+    "riding arena": 304,
+    "river": 305,
+    "rock arch": 306,
+    "rope bridge": 307,
+    "ruin": 308,
+    "runway": 309,
+    "sandbar": 310,
+    "sandbox": 311,
+    "sauna": 312,
+    "schoolhouse": 313,
+    "sea cliff": 314,
+    "server room": 315,
+    "shed": 316,
+    "shoe shop": 317,
+    "shopfront": 318,
+    "shopping mall indoor": 319,
+    "shower": 320,
+    "skatepark": 321,
+    "ski lodge": 322,
+    "ski resort": 323,
+    "ski slope": 324,
+    "sky": 325,
+    "skyscraper": 326,
+    "slum": 327,
+    "snowfield": 328,
+    "squash court": 329,
+    "stable": 330,
+    "stadium baseball": 331,
+    "stadium football": 332,
+    "stage indoor": 333,
+    "staircase": 334,
+    "street": 335,
+    "subway interior": 336,
+    "subway station platform": 337,
+    "supermarket": 338,
+    "sushi bar": 339,
+    "swamp": 340,
+    "swimming pool indoor": 341,
+    "swimming pool outdoor": 342,
+    "synagogue indoor": 343,
+    "synagogue outdoor": 344,
+    "television studio": 345,
+    "temple east asia": 346,
+    "temple south asia": 347,
+    "tennis court indoor": 348,
+    "tennis court outdoor": 349,
+    "tent outdoor": 350,
+    "theater indoor procenium": 351,
+    "theater indoor seats": 352,
+    "thriftshop": 353,
+    "throne room": 354,
+    "ticket booth": 355,
+    "toll plaza": 356,
+    "topiary garden": 357,
+    "tower": 358,
+    "toyshop": 359,
+    "track outdoor": 360,
+    "train railway": 361,
+    "train station platform": 362,
+    "tree farm": 363,
+    "tree house": 364,
+    "trench": 365,
+    "underwater coral reef": 366,
+    "utility room": 367,
+    "valley": 368,
+    "van interior": 369,
+    "vegetable garden": 370,
+    "veranda": 371,
+    "veterinarians office": 372,
+    "viaduct": 373,
+    "videostore": 374,
+    "village": 375,
+    "vineyard": 376,
+    "volcano": 377,
+    "volleyball court indoor": 378,
+    "volleyball court outdoor": 379,
+    "waiting room": 380,
+    "warehouse indoor": 381,
+    "water tower": 382,
+    "waterfall block": 383,
+    "waterfall fan": 384,
+    "waterfall plunge": 385,
+    "watering hole": 386,
+    "wave": 387,
+    "wet bar": 388,
+    "wheat field": 389,
+    "wind farm": 390,
+    "windmill": 391,
+    "wine cellar barrel storage": 392,
+    "wine cellar bottle storage": 393,
+    "wrestling ring indoor": 394,
+    "yard": 395,
+    "youth hostel": 396
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-sun397-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet18-sun397-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-sun397-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-sun397-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/README.md b/resnet18-sun397-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..a9cb72271b19e1c577a169d581989b0c4cf17bde
--- /dev/null
+++ b/resnet18-sun397-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset sun397.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: sun397
+    pretrained: true
+test_datasets: null
+train_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: train
+type: transformers
+val_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: test
+```
+
diff --git a/resnet18-sun397-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/config.json b/resnet18-sun397-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..886da3497a7114ff31c2408ec559a773285de738
--- /dev/null
+++ b/resnet18-sun397-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,837 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "abbey",
+    "1": "airplane cabin",
+    "2": "airport terminal",
+    "3": "alley",
+    "4": "amphitheater",
+    "5": "amusement arcade",
+    "6": "amusement park",
+    "7": "anechoic chamber",
+    "8": "apartment building outdoor",
+    "9": "apse indoor",
+    "10": "aquarium",
+    "11": "aqueduct",
+    "12": "arch",
+    "13": "archive",
+    "14": "arrival gate outdoor",
+    "15": "art gallery",
+    "16": "art school",
+    "17": "art studio",
+    "18": "assembly line",
+    "19": "athletic field outdoor",
+    "20": "atrium public",
+    "21": "attic",
+    "22": "auditorium",
+    "23": "auto factory",
+    "24": "badlands",
+    "25": "badminton court indoor",
+    "26": "baggage claim",
+    "27": "bakery shop",
+    "28": "balcony exterior",
+    "29": "balcony interior",
+    "30": "ball pit",
+    "31": "ballroom",
+    "32": "bamboo forest",
+    "33": "banquet hall",
+    "34": "bar",
+    "35": "barn",
+    "36": "barndoor",
+    "37": "baseball field",
+    "38": "basement",
+    "39": "basilica",
+    "40": "basketball court outdoor",
+    "41": "bathroom",
+    "42": "batters box",
+    "43": "bayou",
+    "44": "bazaar indoor",
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+    "392": "wine cellar barrel storage",
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+    "394": "wrestling ring indoor",
+    "395": "yard",
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+    "veranda": 371,
+    "veterinarians office": 372,
+    "viaduct": 373,
+    "videostore": 374,
+    "village": 375,
+    "vineyard": 376,
+    "volcano": 377,
+    "volleyball court indoor": 378,
+    "volleyball court outdoor": 379,
+    "waiting room": 380,
+    "warehouse indoor": 381,
+    "water tower": 382,
+    "waterfall block": 383,
+    "waterfall fan": 384,
+    "waterfall plunge": 385,
+    "watering hole": 386,
+    "wave": 387,
+    "wet bar": 388,
+    "wheat field": 389,
+    "wind farm": 390,
+    "windmill": 391,
+    "wine cellar barrel storage": 392,
+    "wine cellar bottle storage": 393,
+    "wrestling ring indoor": 394,
+    "yard": 395,
+    "youth hostel": 396
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-sun397-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet18-sun397-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-sun397-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-sun397-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/README.md b/resnet18-sun397-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e2c64426a71f681d601ee9c4db9cac7a4a07e4a0
--- /dev/null
+++ b/resnet18-sun397-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset sun397.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: sun397
+    pretrained: true
+test_datasets: null
+train_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: train
+type: transformers
+val_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: test
+```
+
diff --git a/resnet18-sun397-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/config.json b/resnet18-sun397-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..886da3497a7114ff31c2408ec559a773285de738
--- /dev/null
+++ b/resnet18-sun397-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/config.json
@@ -0,0 +1,837 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "abbey",
+    "1": "airplane cabin",
+    "2": "airport terminal",
+    "3": "alley",
+    "4": "amphitheater",
+    "5": "amusement arcade",
+    "6": "amusement park",
+    "7": "anechoic chamber",
+    "8": "apartment building outdoor",
+    "9": "apse indoor",
+    "10": "aquarium",
+    "11": "aqueduct",
+    "12": "arch",
+    "13": "archive",
+    "14": "arrival gate outdoor",
+    "15": "art gallery",
+    "16": "art school",
+    "17": "art studio",
+    "18": "assembly line",
+    "19": "athletic field outdoor",
+    "20": "atrium public",
+    "21": "attic",
+    "22": "auditorium",
+    "23": "auto factory",
+    "24": "badlands",
+    "25": "badminton court indoor",
+    "26": "baggage claim",
+    "27": "bakery shop",
+    "28": "balcony exterior",
+    "29": "balcony interior",
+    "30": "ball pit",
+    "31": "ballroom",
+    "32": "bamboo forest",
+    "33": "banquet hall",
+    "34": "bar",
+    "35": "barn",
+    "36": "barndoor",
+    "37": "baseball field",
+    "38": "basement",
+    "39": "basilica",
+    "40": "basketball court outdoor",
+    "41": "bathroom",
+    "42": "batters box",
+    "43": "bayou",
+    "44": "bazaar indoor",
+    "45": "bazaar outdoor",
+    "46": "beach",
+    "47": "beauty salon",
+    "48": "bedroom",
+    "49": "berth",
+    "50": "biology laboratory",
+    "51": "bistro indoor",
+    "52": "boardwalk",
+    "53": "boat deck",
+    "54": "boathouse",
+    "55": "bookstore",
+    "56": "booth indoor",
+    "57": "botanical garden",
+    "58": "bow window indoor",
+    "59": "bow window outdoor",
+    "60": "bowling alley",
+    "61": "boxing ring",
+    "62": "brewery indoor",
+    "63": "bridge",
+    "64": "building facade",
+    "65": "bullring",
+    "66": "burial chamber",
+    "67": "bus interior",
+    "68": "butchers shop",
+    "69": "butte",
+    "70": "cabin outdoor",
+    "71": "cafeteria",
+    "72": "campsite",
+    "73": "campus",
+    "74": "canal natural",
+    "75": "canal urban",
+    "76": "candy store",
+    "77": "canyon",
+    "78": "car interior backseat",
+    "79": "car interior frontseat",
+    "80": "carrousel",
+    "81": "casino indoor",
+    "82": "castle",
+    "83": "catacomb",
+    "84": "cathedral indoor",
+    "85": "cathedral outdoor",
+    "86": "cavern indoor",
+    "87": "cemetery",
+    "88": "chalet",
+    "89": "cheese factory",
+    "90": "chemistry lab",
+    "91": "chicken coop indoor",
+    "92": "chicken coop outdoor",
+    "93": "childs room",
+    "94": "church indoor",
+    "95": "church outdoor",
+    "96": "classroom",
+    "97": "clean room",
+    "98": "cliff",
+    "99": "cloister indoor",
+    "100": "closet",
+    "101": "clothing store",
+    "102": "coast",
+    "103": "cockpit",
+    "104": "coffee shop",
+    "105": "computer room",
+    "106": "conference center",
+    "107": "conference room",
+    "108": "construction site",
+    "109": "control room",
+    "110": "control tower outdoor",
+    "111": "corn field",
+    "112": "corral",
+    "113": "corridor",
+    "114": "cottage garden",
+    "115": "courthouse",
+    "116": "courtroom",
+    "117": "courtyard",
+    "118": "covered bridge exterior",
+    "119": "creek",
+    "120": "crevasse",
+    "121": "crosswalk",
+    "122": "cubicle office",
+    "123": "dam",
+    "124": "delicatessen",
+    "125": "dentists office",
+    "126": "desert sand",
+    "127": "desert vegetation",
+    "128": "diner indoor",
+    "129": "diner outdoor",
+    "130": "dinette home",
+    "131": "dinette vehicle",
+    "132": "dining car",
+    "133": "dining room",
+    "134": "discotheque",
+    "135": "dock",
+    "136": "doorway outdoor",
+    "137": "dorm room",
+    "138": "driveway",
+    "139": "driving range outdoor",
+    "140": "drugstore",
+    "141": "electrical substation",
+    "142": "elevator door",
+    "143": "elevator interior",
+    "144": "elevator shaft",
+    "145": "engine room",
+    "146": "escalator indoor",
+    "147": "excavation",
+    "148": "factory indoor",
+    "149": "fairway",
+    "150": "fastfood restaurant",
+    "151": "field cultivated",
+    "152": "field wild",
+    "153": "fire escape",
+    "154": "fire station",
+    "155": "firing range indoor",
+    "156": "fishpond",
+    "157": "florist shop indoor",
+    "158": "food court",
+    "159": "forest broadleaf",
+    "160": "forest needleleaf",
+    "161": "forest path",
+    "162": "forest road",
+    "163": "formal garden",
+    "164": "fountain",
+    "165": "galley",
+    "166": "game room",
+    "167": "garage indoor",
+    "168": "garbage dump",
+    "169": "gas station",
+    "170": "gazebo exterior",
+    "171": "general store indoor",
+    "172": "general store outdoor",
+    "173": "gift shop",
+    "174": "golf course",
+    "175": "greenhouse indoor",
+    "176": "greenhouse outdoor",
+    "177": "gymnasium indoor",
+    "178": "hangar indoor",
+    "179": "hangar outdoor",
+    "180": "harbor",
+    "181": "hayfield",
+    "182": "heliport",
+    "183": "herb garden",
+    "184": "highway",
+    "185": "hill",
+    "186": "home office",
+    "187": "hospital",
+    "188": "hospital room",
+    "189": "hot spring",
+    "190": "hot tub outdoor",
+    "191": "hotel outdoor",
+    "192": "hotel room",
+    "193": "house",
+    "194": "hunting lodge outdoor",
+    "195": "ice cream parlor",
+    "196": "ice floe",
+    "197": "ice shelf",
+    "198": "ice skating rink indoor",
+    "199": "ice skating rink outdoor",
+    "200": "iceberg",
+    "201": "igloo",
+    "202": "industrial area",
+    "203": "inn outdoor",
+    "204": "islet",
+    "205": "jacuzzi indoor",
+    "206": "jail cell",
+    "207": "jail indoor",
+    "208": "jewelry shop",
+    "209": "kasbah",
+    "210": "kennel indoor",
+    "211": "kennel outdoor",
+    "212": "kindergarden classroom",
+    "213": "kitchen",
+    "214": "kitchenette",
+    "215": "labyrinth outdoor",
+    "216": "lake natural",
+    "217": "landfill",
+    "218": "landing deck",
+    "219": "laundromat",
+    "220": "lecture room",
+    "221": "library indoor",
+    "222": "library outdoor",
+    "223": "lido deck outdoor",
+    "224": "lift bridge",
+    "225": "lighthouse",
+    "226": "limousine interior",
+    "227": "living room",
+    "228": "lobby",
+    "229": "lock chamber",
+    "230": "locker room",
+    "231": "mansion",
+    "232": "manufactured home",
+    "233": "market indoor",
+    "234": "market outdoor",
+    "235": "marsh",
+    "236": "martial arts gym",
+    "237": "mausoleum",
+    "238": "medina",
+    "239": "moat water",
+    "240": "monastery outdoor",
+    "241": "mosque indoor",
+    "242": "mosque outdoor",
+    "243": "motel",
+    "244": "mountain",
+    "245": "mountain snowy",
+    "246": "movie theater indoor",
+    "247": "museum indoor",
+    "248": "music store",
+    "249": "music studio",
+    "250": "nuclear power plant outdoor",
+    "251": "nursery",
+    "252": "oast house",
+    "253": "observatory outdoor",
+    "254": "ocean",
+    "255": "office",
+    "256": "office building",
+    "257": "oil refinery outdoor",
+    "258": "oilrig",
+    "259": "operating room",
+    "260": "orchard",
+    "261": "outhouse outdoor",
+    "262": "pagoda",
+    "263": "palace",
+    "264": "pantry",
+    "265": "park",
+    "266": "parking garage indoor",
+    "267": "parking garage outdoor",
+    "268": "parking lot",
+    "269": "parlor",
+    "270": "pasture",
+    "271": "patio",
+    "272": "pavilion",
+    "273": "pharmacy",
+    "274": "phone booth",
+    "275": "physics laboratory",
+    "276": "picnic area",
+    "277": "pilothouse indoor",
+    "278": "planetarium outdoor",
+    "279": "playground",
+    "280": "playroom",
+    "281": "plaza",
+    "282": "podium indoor",
+    "283": "podium outdoor",
+    "284": "pond",
+    "285": "poolroom establishment",
+    "286": "poolroom home",
+    "287": "power plant outdoor",
+    "288": "promenade deck",
+    "289": "pub indoor",
+    "290": "pulpit",
+    "291": "putting green",
+    "292": "racecourse",
+    "293": "raceway",
+    "294": "raft",
+    "295": "railroad track",
+    "296": "rainforest",
+    "297": "reception",
+    "298": "recreation room",
+    "299": "residential neighborhood",
+    "300": "restaurant",
+    "301": "restaurant kitchen",
+    "302": "restaurant patio",
+    "303": "rice paddy",
+    "304": "riding arena",
+    "305": "river",
+    "306": "rock arch",
+    "307": "rope bridge",
+    "308": "ruin",
+    "309": "runway",
+    "310": "sandbar",
+    "311": "sandbox",
+    "312": "sauna",
+    "313": "schoolhouse",
+    "314": "sea cliff",
+    "315": "server room",
+    "316": "shed",
+    "317": "shoe shop",
+    "318": "shopfront",
+    "319": "shopping mall indoor",
+    "320": "shower",
+    "321": "skatepark",
+    "322": "ski lodge",
+    "323": "ski resort",
+    "324": "ski slope",
+    "325": "sky",
+    "326": "skyscraper",
+    "327": "slum",
+    "328": "snowfield",
+    "329": "squash court",
+    "330": "stable",
+    "331": "stadium baseball",
+    "332": "stadium football",
+    "333": "stage indoor",
+    "334": "staircase",
+    "335": "street",
+    "336": "subway interior",
+    "337": "subway station platform",
+    "338": "supermarket",
+    "339": "sushi bar",
+    "340": "swamp",
+    "341": "swimming pool indoor",
+    "342": "swimming pool outdoor",
+    "343": "synagogue indoor",
+    "344": "synagogue outdoor",
+    "345": "television studio",
+    "346": "temple east asia",
+    "347": "temple south asia",
+    "348": "tennis court indoor",
+    "349": "tennis court outdoor",
+    "350": "tent outdoor",
+    "351": "theater indoor procenium",
+    "352": "theater indoor seats",
+    "353": "thriftshop",
+    "354": "throne room",
+    "355": "ticket booth",
+    "356": "toll plaza",
+    "357": "topiary garden",
+    "358": "tower",
+    "359": "toyshop",
+    "360": "track outdoor",
+    "361": "train railway",
+    "362": "train station platform",
+    "363": "tree farm",
+    "364": "tree house",
+    "365": "trench",
+    "366": "underwater coral reef",
+    "367": "utility room",
+    "368": "valley",
+    "369": "van interior",
+    "370": "vegetable garden",
+    "371": "veranda",
+    "372": "veterinarians office",
+    "373": "viaduct",
+    "374": "videostore",
+    "375": "village",
+    "376": "vineyard",
+    "377": "volcano",
+    "378": "volleyball court indoor",
+    "379": "volleyball court outdoor",
+    "380": "waiting room",
+    "381": "warehouse indoor",
+    "382": "water tower",
+    "383": "waterfall block",
+    "384": "waterfall fan",
+    "385": "waterfall plunge",
+    "386": "watering hole",
+    "387": "wave",
+    "388": "wet bar",
+    "389": "wheat field",
+    "390": "wind farm",
+    "391": "windmill",
+    "392": "wine cellar barrel storage",
+    "393": "wine cellar bottle storage",
+    "394": "wrestling ring indoor",
+    "395": "yard",
+    "396": "youth hostel"
+  },
+  "label2id": {
+    "abbey": 0,
+    "airplane cabin": 1,
+    "airport terminal": 2,
+    "alley": 3,
+    "amphitheater": 4,
+    "amusement arcade": 5,
+    "amusement park": 6,
+    "anechoic chamber": 7,
+    "apartment building outdoor": 8,
+    "apse indoor": 9,
+    "aquarium": 10,
+    "aqueduct": 11,
+    "arch": 12,
+    "archive": 13,
+    "arrival gate outdoor": 14,
+    "art gallery": 15,
+    "art school": 16,
+    "art studio": 17,
+    "assembly line": 18,
+    "athletic field outdoor": 19,
+    "atrium public": 20,
+    "attic": 21,
+    "auditorium": 22,
+    "auto factory": 23,
+    "badlands": 24,
+    "badminton court indoor": 25,
+    "baggage claim": 26,
+    "bakery shop": 27,
+    "balcony exterior": 28,
+    "balcony interior": 29,
+    "ball pit": 30,
+    "ballroom": 31,
+    "bamboo forest": 32,
+    "banquet hall": 33,
+    "bar": 34,
+    "barn": 35,
+    "barndoor": 36,
+    "baseball field": 37,
+    "basement": 38,
+    "basilica": 39,
+    "basketball court outdoor": 40,
+    "bathroom": 41,
+    "batters box": 42,
+    "bayou": 43,
+    "bazaar indoor": 44,
+    "bazaar outdoor": 45,
+    "beach": 46,
+    "beauty salon": 47,
+    "bedroom": 48,
+    "berth": 49,
+    "biology laboratory": 50,
+    "bistro indoor": 51,
+    "boardwalk": 52,
+    "boat deck": 53,
+    "boathouse": 54,
+    "bookstore": 55,
+    "booth indoor": 56,
+    "botanical garden": 57,
+    "bow window indoor": 58,
+    "bow window outdoor": 59,
+    "bowling alley": 60,
+    "boxing ring": 61,
+    "brewery indoor": 62,
+    "bridge": 63,
+    "building facade": 64,
+    "bullring": 65,
+    "burial chamber": 66,
+    "bus interior": 67,
+    "butchers shop": 68,
+    "butte": 69,
+    "cabin outdoor": 70,
+    "cafeteria": 71,
+    "campsite": 72,
+    "campus": 73,
+    "canal natural": 74,
+    "canal urban": 75,
+    "candy store": 76,
+    "canyon": 77,
+    "car interior backseat": 78,
+    "car interior frontseat": 79,
+    "carrousel": 80,
+    "casino indoor": 81,
+    "castle": 82,
+    "catacomb": 83,
+    "cathedral indoor": 84,
+    "cathedral outdoor": 85,
+    "cavern indoor": 86,
+    "cemetery": 87,
+    "chalet": 88,
+    "cheese factory": 89,
+    "chemistry lab": 90,
+    "chicken coop indoor": 91,
+    "chicken coop outdoor": 92,
+    "childs room": 93,
+    "church indoor": 94,
+    "church outdoor": 95,
+    "classroom": 96,
+    "clean room": 97,
+    "cliff": 98,
+    "cloister indoor": 99,
+    "closet": 100,
+    "clothing store": 101,
+    "coast": 102,
+    "cockpit": 103,
+    "coffee shop": 104,
+    "computer room": 105,
+    "conference center": 106,
+    "conference room": 107,
+    "construction site": 108,
+    "control room": 109,
+    "control tower outdoor": 110,
+    "corn field": 111,
+    "corral": 112,
+    "corridor": 113,
+    "cottage garden": 114,
+    "courthouse": 115,
+    "courtroom": 116,
+    "courtyard": 117,
+    "covered bridge exterior": 118,
+    "creek": 119,
+    "crevasse": 120,
+    "crosswalk": 121,
+    "cubicle office": 122,
+    "dam": 123,
+    "delicatessen": 124,
+    "dentists office": 125,
+    "desert sand": 126,
+    "desert vegetation": 127,
+    "diner indoor": 128,
+    "diner outdoor": 129,
+    "dinette home": 130,
+    "dinette vehicle": 131,
+    "dining car": 132,
+    "dining room": 133,
+    "discotheque": 134,
+    "dock": 135,
+    "doorway outdoor": 136,
+    "dorm room": 137,
+    "driveway": 138,
+    "driving range outdoor": 139,
+    "drugstore": 140,
+    "electrical substation": 141,
+    "elevator door": 142,
+    "elevator interior": 143,
+    "elevator shaft": 144,
+    "engine room": 145,
+    "escalator indoor": 146,
+    "excavation": 147,
+    "factory indoor": 148,
+    "fairway": 149,
+    "fastfood restaurant": 150,
+    "field cultivated": 151,
+    "field wild": 152,
+    "fire escape": 153,
+    "fire station": 154,
+    "firing range indoor": 155,
+    "fishpond": 156,
+    "florist shop indoor": 157,
+    "food court": 158,
+    "forest broadleaf": 159,
+    "forest needleleaf": 160,
+    "forest path": 161,
+    "forest road": 162,
+    "formal garden": 163,
+    "fountain": 164,
+    "galley": 165,
+    "game room": 166,
+    "garage indoor": 167,
+    "garbage dump": 168,
+    "gas station": 169,
+    "gazebo exterior": 170,
+    "general store indoor": 171,
+    "general store outdoor": 172,
+    "gift shop": 173,
+    "golf course": 174,
+    "greenhouse indoor": 175,
+    "greenhouse outdoor": 176,
+    "gymnasium indoor": 177,
+    "hangar indoor": 178,
+    "hangar outdoor": 179,
+    "harbor": 180,
+    "hayfield": 181,
+    "heliport": 182,
+    "herb garden": 183,
+    "highway": 184,
+    "hill": 185,
+    "home office": 186,
+    "hospital": 187,
+    "hospital room": 188,
+    "hot spring": 189,
+    "hot tub outdoor": 190,
+    "hotel outdoor": 191,
+    "hotel room": 192,
+    "house": 193,
+    "hunting lodge outdoor": 194,
+    "ice cream parlor": 195,
+    "ice floe": 196,
+    "ice shelf": 197,
+    "ice skating rink indoor": 198,
+    "ice skating rink outdoor": 199,
+    "iceberg": 200,
+    "igloo": 201,
+    "industrial area": 202,
+    "inn outdoor": 203,
+    "islet": 204,
+    "jacuzzi indoor": 205,
+    "jail cell": 206,
+    "jail indoor": 207,
+    "jewelry shop": 208,
+    "kasbah": 209,
+    "kennel indoor": 210,
+    "kennel outdoor": 211,
+    "kindergarden classroom": 212,
+    "kitchen": 213,
+    "kitchenette": 214,
+    "labyrinth outdoor": 215,
+    "lake natural": 216,
+    "landfill": 217,
+    "landing deck": 218,
+    "laundromat": 219,
+    "lecture room": 220,
+    "library indoor": 221,
+    "library outdoor": 222,
+    "lido deck outdoor": 223,
+    "lift bridge": 224,
+    "lighthouse": 225,
+    "limousine interior": 226,
+    "living room": 227,
+    "lobby": 228,
+    "lock chamber": 229,
+    "locker room": 230,
+    "mansion": 231,
+    "manufactured home": 232,
+    "market indoor": 233,
+    "market outdoor": 234,
+    "marsh": 235,
+    "martial arts gym": 236,
+    "mausoleum": 237,
+    "medina": 238,
+    "moat water": 239,
+    "monastery outdoor": 240,
+    "mosque indoor": 241,
+    "mosque outdoor": 242,
+    "motel": 243,
+    "mountain": 244,
+    "mountain snowy": 245,
+    "movie theater indoor": 246,
+    "museum indoor": 247,
+    "music store": 248,
+    "music studio": 249,
+    "nuclear power plant outdoor": 250,
+    "nursery": 251,
+    "oast house": 252,
+    "observatory outdoor": 253,
+    "ocean": 254,
+    "office": 255,
+    "office building": 256,
+    "oil refinery outdoor": 257,
+    "oilrig": 258,
+    "operating room": 259,
+    "orchard": 260,
+    "outhouse outdoor": 261,
+    "pagoda": 262,
+    "palace": 263,
+    "pantry": 264,
+    "park": 265,
+    "parking garage indoor": 266,
+    "parking garage outdoor": 267,
+    "parking lot": 268,
+    "parlor": 269,
+    "pasture": 270,
+    "patio": 271,
+    "pavilion": 272,
+    "pharmacy": 273,
+    "phone booth": 274,
+    "physics laboratory": 275,
+    "picnic area": 276,
+    "pilothouse indoor": 277,
+    "planetarium outdoor": 278,
+    "playground": 279,
+    "playroom": 280,
+    "plaza": 281,
+    "podium indoor": 282,
+    "podium outdoor": 283,
+    "pond": 284,
+    "poolroom establishment": 285,
+    "poolroom home": 286,
+    "power plant outdoor": 287,
+    "promenade deck": 288,
+    "pub indoor": 289,
+    "pulpit": 290,
+    "putting green": 291,
+    "racecourse": 292,
+    "raceway": 293,
+    "raft": 294,
+    "railroad track": 295,
+    "rainforest": 296,
+    "reception": 297,
+    "recreation room": 298,
+    "residential neighborhood": 299,
+    "restaurant": 300,
+    "restaurant kitchen": 301,
+    "restaurant patio": 302,
+    "rice paddy": 303,
+    "riding arena": 304,
+    "river": 305,
+    "rock arch": 306,
+    "rope bridge": 307,
+    "ruin": 308,
+    "runway": 309,
+    "sandbar": 310,
+    "sandbox": 311,
+    "sauna": 312,
+    "schoolhouse": 313,
+    "sea cliff": 314,
+    "server room": 315,
+    "shed": 316,
+    "shoe shop": 317,
+    "shopfront": 318,
+    "shopping mall indoor": 319,
+    "shower": 320,
+    "skatepark": 321,
+    "ski lodge": 322,
+    "ski resort": 323,
+    "ski slope": 324,
+    "sky": 325,
+    "skyscraper": 326,
+    "slum": 327,
+    "snowfield": 328,
+    "squash court": 329,
+    "stable": 330,
+    "stadium baseball": 331,
+    "stadium football": 332,
+    "stage indoor": 333,
+    "staircase": 334,
+    "street": 335,
+    "subway interior": 336,
+    "subway station platform": 337,
+    "supermarket": 338,
+    "sushi bar": 339,
+    "swamp": 340,
+    "swimming pool indoor": 341,
+    "swimming pool outdoor": 342,
+    "synagogue indoor": 343,
+    "synagogue outdoor": 344,
+    "television studio": 345,
+    "temple east asia": 346,
+    "temple south asia": 347,
+    "tennis court indoor": 348,
+    "tennis court outdoor": 349,
+    "tent outdoor": 350,
+    "theater indoor procenium": 351,
+    "theater indoor seats": 352,
+    "thriftshop": 353,
+    "throne room": 354,
+    "ticket booth": 355,
+    "toll plaza": 356,
+    "topiary garden": 357,
+    "tower": 358,
+    "toyshop": 359,
+    "track outdoor": 360,
+    "train railway": 361,
+    "train station platform": 362,
+    "tree farm": 363,
+    "tree house": 364,
+    "trench": 365,
+    "underwater coral reef": 366,
+    "utility room": 367,
+    "valley": 368,
+    "van interior": 369,
+    "vegetable garden": 370,
+    "veranda": 371,
+    "veterinarians office": 372,
+    "viaduct": 373,
+    "videostore": 374,
+    "village": 375,
+    "vineyard": 376,
+    "volcano": 377,
+    "volleyball court indoor": 378,
+    "volleyball court outdoor": 379,
+    "waiting room": 380,
+    "warehouse indoor": 381,
+    "water tower": 382,
+    "waterfall block": 383,
+    "waterfall fan": 384,
+    "waterfall plunge": 385,
+    "watering hole": 386,
+    "wave": 387,
+    "wet bar": 388,
+    "wheat field": 389,
+    "wind farm": 390,
+    "windmill": 391,
+    "wine cellar barrel storage": 392,
+    "wine cellar bottle storage": 393,
+    "wrestling ring indoor": 394,
+    "yard": 395,
+    "youth hostel": 396
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-sun397-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet18-sun397-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-sun397-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-sun397-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/README.md b/resnet18-sun397-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..18ca9d057842f12b72328b3a58f0c60d40e9e12e
--- /dev/null
+++ b/resnet18-sun397-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset sun397.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: sun397
+    pretrained: true
+test_datasets: null
+train_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: train
+type: transformers
+val_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: test
+```
+
diff --git a/resnet18-sun397-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/config.json b/resnet18-sun397-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..886da3497a7114ff31c2408ec559a773285de738
--- /dev/null
+++ b/resnet18-sun397-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,837 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "abbey",
+    "1": "airplane cabin",
+    "2": "airport terminal",
+    "3": "alley",
+    "4": "amphitheater",
+    "5": "amusement arcade",
+    "6": "amusement park",
+    "7": "anechoic chamber",
+    "8": "apartment building outdoor",
+    "9": "apse indoor",
+    "10": "aquarium",
+    "11": "aqueduct",
+    "12": "arch",
+    "13": "archive",
+    "14": "arrival gate outdoor",
+    "15": "art gallery",
+    "16": "art school",
+    "17": "art studio",
+    "18": "assembly line",
+    "19": "athletic field outdoor",
+    "20": "atrium public",
+    "21": "attic",
+    "22": "auditorium",
+    "23": "auto factory",
+    "24": "badlands",
+    "25": "badminton court indoor",
+    "26": "baggage claim",
+    "27": "bakery shop",
+    "28": "balcony exterior",
+    "29": "balcony interior",
+    "30": "ball pit",
+    "31": "ballroom",
+    "32": "bamboo forest",
+    "33": "banquet hall",
+    "34": "bar",
+    "35": "barn",
+    "36": "barndoor",
+    "37": "baseball field",
+    "38": "basement",
+    "39": "basilica",
+    "40": "basketball court outdoor",
+    "41": "bathroom",
+    "42": "batters box",
+    "43": "bayou",
+    "44": "bazaar indoor",
+    "45": "bazaar outdoor",
+    "46": "beach",
+    "47": "beauty salon",
+    "48": "bedroom",
+    "49": "berth",
+    "50": "biology laboratory",
+    "51": "bistro indoor",
+    "52": "boardwalk",
+    "53": "boat deck",
+    "54": "boathouse",
+    "55": "bookstore",
+    "56": "booth indoor",
+    "57": "botanical garden",
+    "58": "bow window indoor",
+    "59": "bow window outdoor",
+    "60": "bowling alley",
+    "61": "boxing ring",
+    "62": "brewery indoor",
+    "63": "bridge",
+    "64": "building facade",
+    "65": "bullring",
+    "66": "burial chamber",
+    "67": "bus interior",
+    "68": "butchers shop",
+    "69": "butte",
+    "70": "cabin outdoor",
+    "71": "cafeteria",
+    "72": "campsite",
+    "73": "campus",
+    "74": "canal natural",
+    "75": "canal urban",
+    "76": "candy store",
+    "77": "canyon",
+    "78": "car interior backseat",
+    "79": "car interior frontseat",
+    "80": "carrousel",
+    "81": "casino indoor",
+    "82": "castle",
+    "83": "catacomb",
+    "84": "cathedral indoor",
+    "85": "cathedral outdoor",
+    "86": "cavern indoor",
+    "87": "cemetery",
+    "88": "chalet",
+    "89": "cheese factory",
+    "90": "chemistry lab",
+    "91": "chicken coop indoor",
+    "92": "chicken coop outdoor",
+    "93": "childs room",
+    "94": "church indoor",
+    "95": "church outdoor",
+    "96": "classroom",
+    "97": "clean room",
+    "98": "cliff",
+    "99": "cloister indoor",
+    "100": "closet",
+    "101": "clothing store",
+    "102": "coast",
+    "103": "cockpit",
+    "104": "coffee shop",
+    "105": "computer room",
+    "106": "conference center",
+    "107": "conference room",
+    "108": "construction site",
+    "109": "control room",
+    "110": "control tower outdoor",
+    "111": "corn field",
+    "112": "corral",
+    "113": "corridor",
+    "114": "cottage garden",
+    "115": "courthouse",
+    "116": "courtroom",
+    "117": "courtyard",
+    "118": "covered bridge exterior",
+    "119": "creek",
+    "120": "crevasse",
+    "121": "crosswalk",
+    "122": "cubicle office",
+    "123": "dam",
+    "124": "delicatessen",
+    "125": "dentists office",
+    "126": "desert sand",
+    "127": "desert vegetation",
+    "128": "diner indoor",
+    "129": "diner outdoor",
+    "130": "dinette home",
+    "131": "dinette vehicle",
+    "132": "dining car",
+    "133": "dining room",
+    "134": "discotheque",
+    "135": "dock",
+    "136": "doorway outdoor",
+    "137": "dorm room",
+    "138": "driveway",
+    "139": "driving range outdoor",
+    "140": "drugstore",
+    "141": "electrical substation",
+    "142": "elevator door",
+    "143": "elevator interior",
+    "144": "elevator shaft",
+    "145": "engine room",
+    "146": "escalator indoor",
+    "147": "excavation",
+    "148": "factory indoor",
+    "149": "fairway",
+    "150": "fastfood restaurant",
+    "151": "field cultivated",
+    "152": "field wild",
+    "153": "fire escape",
+    "154": "fire station",
+    "155": "firing range indoor",
+    "156": "fishpond",
+    "157": "florist shop indoor",
+    "158": "food court",
+    "159": "forest broadleaf",
+    "160": "forest needleleaf",
+    "161": "forest path",
+    "162": "forest road",
+    "163": "formal garden",
+    "164": "fountain",
+    "165": "galley",
+    "166": "game room",
+    "167": "garage indoor",
+    "168": "garbage dump",
+    "169": "gas station",
+    "170": "gazebo exterior",
+    "171": "general store indoor",
+    "172": "general store outdoor",
+    "173": "gift shop",
+    "174": "golf course",
+    "175": "greenhouse indoor",
+    "176": "greenhouse outdoor",
+    "177": "gymnasium indoor",
+    "178": "hangar indoor",
+    "179": "hangar outdoor",
+    "180": "harbor",
+    "181": "hayfield",
+    "182": "heliport",
+    "183": "herb garden",
+    "184": "highway",
+    "185": "hill",
+    "186": "home office",
+    "187": "hospital",
+    "188": "hospital room",
+    "189": "hot spring",
+    "190": "hot tub outdoor",
+    "191": "hotel outdoor",
+    "192": "hotel room",
+    "193": "house",
+    "194": "hunting lodge outdoor",
+    "195": "ice cream parlor",
+    "196": "ice floe",
+    "197": "ice shelf",
+    "198": "ice skating rink indoor",
+    "199": "ice skating rink outdoor",
+    "200": "iceberg",
+    "201": "igloo",
+    "202": "industrial area",
+    "203": "inn outdoor",
+    "204": "islet",
+    "205": "jacuzzi indoor",
+    "206": "jail cell",
+    "207": "jail indoor",
+    "208": "jewelry shop",
+    "209": "kasbah",
+    "210": "kennel indoor",
+    "211": "kennel outdoor",
+    "212": "kindergarden classroom",
+    "213": "kitchen",
+    "214": "kitchenette",
+    "215": "labyrinth outdoor",
+    "216": "lake natural",
+    "217": "landfill",
+    "218": "landing deck",
+    "219": "laundromat",
+    "220": "lecture room",
+    "221": "library indoor",
+    "222": "library outdoor",
+    "223": "lido deck outdoor",
+    "224": "lift bridge",
+    "225": "lighthouse",
+    "226": "limousine interior",
+    "227": "living room",
+    "228": "lobby",
+    "229": "lock chamber",
+    "230": "locker room",
+    "231": "mansion",
+    "232": "manufactured home",
+    "233": "market indoor",
+    "234": "market outdoor",
+    "235": "marsh",
+    "236": "martial arts gym",
+    "237": "mausoleum",
+    "238": "medina",
+    "239": "moat water",
+    "240": "monastery outdoor",
+    "241": "mosque indoor",
+    "242": "mosque outdoor",
+    "243": "motel",
+    "244": "mountain",
+    "245": "mountain snowy",
+    "246": "movie theater indoor",
+    "247": "museum indoor",
+    "248": "music store",
+    "249": "music studio",
+    "250": "nuclear power plant outdoor",
+    "251": "nursery",
+    "252": "oast house",
+    "253": "observatory outdoor",
+    "254": "ocean",
+    "255": "office",
+    "256": "office building",
+    "257": "oil refinery outdoor",
+    "258": "oilrig",
+    "259": "operating room",
+    "260": "orchard",
+    "261": "outhouse outdoor",
+    "262": "pagoda",
+    "263": "palace",
+    "264": "pantry",
+    "265": "park",
+    "266": "parking garage indoor",
+    "267": "parking garage outdoor",
+    "268": "parking lot",
+    "269": "parlor",
+    "270": "pasture",
+    "271": "patio",
+    "272": "pavilion",
+    "273": "pharmacy",
+    "274": "phone booth",
+    "275": "physics laboratory",
+    "276": "picnic area",
+    "277": "pilothouse indoor",
+    "278": "planetarium outdoor",
+    "279": "playground",
+    "280": "playroom",
+    "281": "plaza",
+    "282": "podium indoor",
+    "283": "podium outdoor",
+    "284": "pond",
+    "285": "poolroom establishment",
+    "286": "poolroom home",
+    "287": "power plant outdoor",
+    "288": "promenade deck",
+    "289": "pub indoor",
+    "290": "pulpit",
+    "291": "putting green",
+    "292": "racecourse",
+    "293": "raceway",
+    "294": "raft",
+    "295": "railroad track",
+    "296": "rainforest",
+    "297": "reception",
+    "298": "recreation room",
+    "299": "residential neighborhood",
+    "300": "restaurant",
+    "301": "restaurant kitchen",
+    "302": "restaurant patio",
+    "303": "rice paddy",
+    "304": "riding arena",
+    "305": "river",
+    "306": "rock arch",
+    "307": "rope bridge",
+    "308": "ruin",
+    "309": "runway",
+    "310": "sandbar",
+    "311": "sandbox",
+    "312": "sauna",
+    "313": "schoolhouse",
+    "314": "sea cliff",
+    "315": "server room",
+    "316": "shed",
+    "317": "shoe shop",
+    "318": "shopfront",
+    "319": "shopping mall indoor",
+    "320": "shower",
+    "321": "skatepark",
+    "322": "ski lodge",
+    "323": "ski resort",
+    "324": "ski slope",
+    "325": "sky",
+    "326": "skyscraper",
+    "327": "slum",
+    "328": "snowfield",
+    "329": "squash court",
+    "330": "stable",
+    "331": "stadium baseball",
+    "332": "stadium football",
+    "333": "stage indoor",
+    "334": "staircase",
+    "335": "street",
+    "336": "subway interior",
+    "337": "subway station platform",
+    "338": "supermarket",
+    "339": "sushi bar",
+    "340": "swamp",
+    "341": "swimming pool indoor",
+    "342": "swimming pool outdoor",
+    "343": "synagogue indoor",
+    "344": "synagogue outdoor",
+    "345": "television studio",
+    "346": "temple east asia",
+    "347": "temple south asia",
+    "348": "tennis court indoor",
+    "349": "tennis court outdoor",
+    "350": "tent outdoor",
+    "351": "theater indoor procenium",
+    "352": "theater indoor seats",
+    "353": "thriftshop",
+    "354": "throne room",
+    "355": "ticket booth",
+    "356": "toll plaza",
+    "357": "topiary garden",
+    "358": "tower",
+    "359": "toyshop",
+    "360": "track outdoor",
+    "361": "train railway",
+    "362": "train station platform",
+    "363": "tree farm",
+    "364": "tree house",
+    "365": "trench",
+    "366": "underwater coral reef",
+    "367": "utility room",
+    "368": "valley",
+    "369": "van interior",
+    "370": "vegetable garden",
+    "371": "veranda",
+    "372": "veterinarians office",
+    "373": "viaduct",
+    "374": "videostore",
+    "375": "village",
+    "376": "vineyard",
+    "377": "volcano",
+    "378": "volleyball court indoor",
+    "379": "volleyball court outdoor",
+    "380": "waiting room",
+    "381": "warehouse indoor",
+    "382": "water tower",
+    "383": "waterfall block",
+    "384": "waterfall fan",
+    "385": "waterfall plunge",
+    "386": "watering hole",
+    "387": "wave",
+    "388": "wet bar",
+    "389": "wheat field",
+    "390": "wind farm",
+    "391": "windmill",
+    "392": "wine cellar barrel storage",
+    "393": "wine cellar bottle storage",
+    "394": "wrestling ring indoor",
+    "395": "yard",
+    "396": "youth hostel"
+  },
+  "label2id": {
+    "abbey": 0,
+    "airplane cabin": 1,
+    "airport terminal": 2,
+    "alley": 3,
+    "amphitheater": 4,
+    "amusement arcade": 5,
+    "amusement park": 6,
+    "anechoic chamber": 7,
+    "apartment building outdoor": 8,
+    "apse indoor": 9,
+    "aquarium": 10,
+    "aqueduct": 11,
+    "arch": 12,
+    "archive": 13,
+    "arrival gate outdoor": 14,
+    "art gallery": 15,
+    "art school": 16,
+    "art studio": 17,
+    "assembly line": 18,
+    "athletic field outdoor": 19,
+    "atrium public": 20,
+    "attic": 21,
+    "auditorium": 22,
+    "auto factory": 23,
+    "badlands": 24,
+    "badminton court indoor": 25,
+    "baggage claim": 26,
+    "bakery shop": 27,
+    "balcony exterior": 28,
+    "balcony interior": 29,
+    "ball pit": 30,
+    "ballroom": 31,
+    "bamboo forest": 32,
+    "banquet hall": 33,
+    "bar": 34,
+    "barn": 35,
+    "barndoor": 36,
+    "baseball field": 37,
+    "basement": 38,
+    "basilica": 39,
+    "basketball court outdoor": 40,
+    "bathroom": 41,
+    "batters box": 42,
+    "bayou": 43,
+    "bazaar indoor": 44,
+    "bazaar outdoor": 45,
+    "beach": 46,
+    "beauty salon": 47,
+    "bedroom": 48,
+    "berth": 49,
+    "biology laboratory": 50,
+    "bistro indoor": 51,
+    "boardwalk": 52,
+    "boat deck": 53,
+    "boathouse": 54,
+    "bookstore": 55,
+    "booth indoor": 56,
+    "botanical garden": 57,
+    "bow window indoor": 58,
+    "bow window outdoor": 59,
+    "bowling alley": 60,
+    "boxing ring": 61,
+    "brewery indoor": 62,
+    "bridge": 63,
+    "building facade": 64,
+    "bullring": 65,
+    "burial chamber": 66,
+    "bus interior": 67,
+    "butchers shop": 68,
+    "butte": 69,
+    "cabin outdoor": 70,
+    "cafeteria": 71,
+    "campsite": 72,
+    "campus": 73,
+    "canal natural": 74,
+    "canal urban": 75,
+    "candy store": 76,
+    "canyon": 77,
+    "car interior backseat": 78,
+    "car interior frontseat": 79,
+    "carrousel": 80,
+    "casino indoor": 81,
+    "castle": 82,
+    "catacomb": 83,
+    "cathedral indoor": 84,
+    "cathedral outdoor": 85,
+    "cavern indoor": 86,
+    "cemetery": 87,
+    "chalet": 88,
+    "cheese factory": 89,
+    "chemistry lab": 90,
+    "chicken coop indoor": 91,
+    "chicken coop outdoor": 92,
+    "childs room": 93,
+    "church indoor": 94,
+    "church outdoor": 95,
+    "classroom": 96,
+    "clean room": 97,
+    "cliff": 98,
+    "cloister indoor": 99,
+    "closet": 100,
+    "clothing store": 101,
+    "coast": 102,
+    "cockpit": 103,
+    "coffee shop": 104,
+    "computer room": 105,
+    "conference center": 106,
+    "conference room": 107,
+    "construction site": 108,
+    "control room": 109,
+    "control tower outdoor": 110,
+    "corn field": 111,
+    "corral": 112,
+    "corridor": 113,
+    "cottage garden": 114,
+    "courthouse": 115,
+    "courtroom": 116,
+    "courtyard": 117,
+    "covered bridge exterior": 118,
+    "creek": 119,
+    "crevasse": 120,
+    "crosswalk": 121,
+    "cubicle office": 122,
+    "dam": 123,
+    "delicatessen": 124,
+    "dentists office": 125,
+    "desert sand": 126,
+    "desert vegetation": 127,
+    "diner indoor": 128,
+    "diner outdoor": 129,
+    "dinette home": 130,
+    "dinette vehicle": 131,
+    "dining car": 132,
+    "dining room": 133,
+    "discotheque": 134,
+    "dock": 135,
+    "doorway outdoor": 136,
+    "dorm room": 137,
+    "driveway": 138,
+    "driving range outdoor": 139,
+    "drugstore": 140,
+    "electrical substation": 141,
+    "elevator door": 142,
+    "elevator interior": 143,
+    "elevator shaft": 144,
+    "engine room": 145,
+    "escalator indoor": 146,
+    "excavation": 147,
+    "factory indoor": 148,
+    "fairway": 149,
+    "fastfood restaurant": 150,
+    "field cultivated": 151,
+    "field wild": 152,
+    "fire escape": 153,
+    "fire station": 154,
+    "firing range indoor": 155,
+    "fishpond": 156,
+    "florist shop indoor": 157,
+    "food court": 158,
+    "forest broadleaf": 159,
+    "forest needleleaf": 160,
+    "forest path": 161,
+    "forest road": 162,
+    "formal garden": 163,
+    "fountain": 164,
+    "galley": 165,
+    "game room": 166,
+    "garage indoor": 167,
+    "garbage dump": 168,
+    "gas station": 169,
+    "gazebo exterior": 170,
+    "general store indoor": 171,
+    "general store outdoor": 172,
+    "gift shop": 173,
+    "golf course": 174,
+    "greenhouse indoor": 175,
+    "greenhouse outdoor": 176,
+    "gymnasium indoor": 177,
+    "hangar indoor": 178,
+    "hangar outdoor": 179,
+    "harbor": 180,
+    "hayfield": 181,
+    "heliport": 182,
+    "herb garden": 183,
+    "highway": 184,
+    "hill": 185,
+    "home office": 186,
+    "hospital": 187,
+    "hospital room": 188,
+    "hot spring": 189,
+    "hot tub outdoor": 190,
+    "hotel outdoor": 191,
+    "hotel room": 192,
+    "house": 193,
+    "hunting lodge outdoor": 194,
+    "ice cream parlor": 195,
+    "ice floe": 196,
+    "ice shelf": 197,
+    "ice skating rink indoor": 198,
+    "ice skating rink outdoor": 199,
+    "iceberg": 200,
+    "igloo": 201,
+    "industrial area": 202,
+    "inn outdoor": 203,
+    "islet": 204,
+    "jacuzzi indoor": 205,
+    "jail cell": 206,
+    "jail indoor": 207,
+    "jewelry shop": 208,
+    "kasbah": 209,
+    "kennel indoor": 210,
+    "kennel outdoor": 211,
+    "kindergarden classroom": 212,
+    "kitchen": 213,
+    "kitchenette": 214,
+    "labyrinth outdoor": 215,
+    "lake natural": 216,
+    "landfill": 217,
+    "landing deck": 218,
+    "laundromat": 219,
+    "lecture room": 220,
+    "library indoor": 221,
+    "library outdoor": 222,
+    "lido deck outdoor": 223,
+    "lift bridge": 224,
+    "lighthouse": 225,
+    "limousine interior": 226,
+    "living room": 227,
+    "lobby": 228,
+    "lock chamber": 229,
+    "locker room": 230,
+    "mansion": 231,
+    "manufactured home": 232,
+    "market indoor": 233,
+    "market outdoor": 234,
+    "marsh": 235,
+    "martial arts gym": 236,
+    "mausoleum": 237,
+    "medina": 238,
+    "moat water": 239,
+    "monastery outdoor": 240,
+    "mosque indoor": 241,
+    "mosque outdoor": 242,
+    "motel": 243,
+    "mountain": 244,
+    "mountain snowy": 245,
+    "movie theater indoor": 246,
+    "museum indoor": 247,
+    "music store": 248,
+    "music studio": 249,
+    "nuclear power plant outdoor": 250,
+    "nursery": 251,
+    "oast house": 252,
+    "observatory outdoor": 253,
+    "ocean": 254,
+    "office": 255,
+    "office building": 256,
+    "oil refinery outdoor": 257,
+    "oilrig": 258,
+    "operating room": 259,
+    "orchard": 260,
+    "outhouse outdoor": 261,
+    "pagoda": 262,
+    "palace": 263,
+    "pantry": 264,
+    "park": 265,
+    "parking garage indoor": 266,
+    "parking garage outdoor": 267,
+    "parking lot": 268,
+    "parlor": 269,
+    "pasture": 270,
+    "patio": 271,
+    "pavilion": 272,
+    "pharmacy": 273,
+    "phone booth": 274,
+    "physics laboratory": 275,
+    "picnic area": 276,
+    "pilothouse indoor": 277,
+    "planetarium outdoor": 278,
+    "playground": 279,
+    "playroom": 280,
+    "plaza": 281,
+    "podium indoor": 282,
+    "podium outdoor": 283,
+    "pond": 284,
+    "poolroom establishment": 285,
+    "poolroom home": 286,
+    "power plant outdoor": 287,
+    "promenade deck": 288,
+    "pub indoor": 289,
+    "pulpit": 290,
+    "putting green": 291,
+    "racecourse": 292,
+    "raceway": 293,
+    "raft": 294,
+    "railroad track": 295,
+    "rainforest": 296,
+    "reception": 297,
+    "recreation room": 298,
+    "residential neighborhood": 299,
+    "restaurant": 300,
+    "restaurant kitchen": 301,
+    "restaurant patio": 302,
+    "rice paddy": 303,
+    "riding arena": 304,
+    "river": 305,
+    "rock arch": 306,
+    "rope bridge": 307,
+    "ruin": 308,
+    "runway": 309,
+    "sandbar": 310,
+    "sandbox": 311,
+    "sauna": 312,
+    "schoolhouse": 313,
+    "sea cliff": 314,
+    "server room": 315,
+    "shed": 316,
+    "shoe shop": 317,
+    "shopfront": 318,
+    "shopping mall indoor": 319,
+    "shower": 320,
+    "skatepark": 321,
+    "ski lodge": 322,
+    "ski resort": 323,
+    "ski slope": 324,
+    "sky": 325,
+    "skyscraper": 326,
+    "slum": 327,
+    "snowfield": 328,
+    "squash court": 329,
+    "stable": 330,
+    "stadium baseball": 331,
+    "stadium football": 332,
+    "stage indoor": 333,
+    "staircase": 334,
+    "street": 335,
+    "subway interior": 336,
+    "subway station platform": 337,
+    "supermarket": 338,
+    "sushi bar": 339,
+    "swamp": 340,
+    "swimming pool indoor": 341,
+    "swimming pool outdoor": 342,
+    "synagogue indoor": 343,
+    "synagogue outdoor": 344,
+    "television studio": 345,
+    "temple east asia": 346,
+    "temple south asia": 347,
+    "tennis court indoor": 348,
+    "tennis court outdoor": 349,
+    "tent outdoor": 350,
+    "theater indoor procenium": 351,
+    "theater indoor seats": 352,
+    "thriftshop": 353,
+    "throne room": 354,
+    "ticket booth": 355,
+    "toll plaza": 356,
+    "topiary garden": 357,
+    "tower": 358,
+    "toyshop": 359,
+    "track outdoor": 360,
+    "train railway": 361,
+    "train station platform": 362,
+    "tree farm": 363,
+    "tree house": 364,
+    "trench": 365,
+    "underwater coral reef": 366,
+    "utility room": 367,
+    "valley": 368,
+    "van interior": 369,
+    "vegetable garden": 370,
+    "veranda": 371,
+    "veterinarians office": 372,
+    "viaduct": 373,
+    "videostore": 374,
+    "village": 375,
+    "vineyard": 376,
+    "volcano": 377,
+    "volleyball court indoor": 378,
+    "volleyball court outdoor": 379,
+    "waiting room": 380,
+    "warehouse indoor": 381,
+    "water tower": 382,
+    "waterfall block": 383,
+    "waterfall fan": 384,
+    "waterfall plunge": 385,
+    "watering hole": 386,
+    "wave": 387,
+    "wet bar": 388,
+    "wheat field": 389,
+    "wind farm": 390,
+    "windmill": 391,
+    "wine cellar barrel storage": 392,
+    "wine cellar bottle storage": 393,
+    "wrestling ring indoor": 394,
+    "yard": 395,
+    "youth hostel": 396
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-sun397-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet18-sun397-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-sun397-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-2000/README.md b/resnet18-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..59f2b1ef6e869917954ab70e99b757e8490e1487
--- /dev/null
+++ b/resnet18-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset sun397.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: sun397
+    pretrained: true
+test_datasets: null
+train_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: train
+type: transformers
+val_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: test
+```
+
diff --git a/resnet18-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-2000/config.json b/resnet18-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..886da3497a7114ff31c2408ec559a773285de738
--- /dev/null
+++ b/resnet18-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,837 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "abbey",
+    "1": "airplane cabin",
+    "2": "airport terminal",
+    "3": "alley",
+    "4": "amphitheater",
+    "5": "amusement arcade",
+    "6": "amusement park",
+    "7": "anechoic chamber",
+    "8": "apartment building outdoor",
+    "9": "apse indoor",
+    "10": "aquarium",
+    "11": "aqueduct",
+    "12": "arch",
+    "13": "archive",
+    "14": "arrival gate outdoor",
+    "15": "art gallery",
+    "16": "art school",
+    "17": "art studio",
+    "18": "assembly line",
+    "19": "athletic field outdoor",
+    "20": "atrium public",
+    "21": "attic",
+    "22": "auditorium",
+    "23": "auto factory",
+    "24": "badlands",
+    "25": "badminton court indoor",
+    "26": "baggage claim",
+    "27": "bakery shop",
+    "28": "balcony exterior",
+    "29": "balcony interior",
+    "30": "ball pit",
+    "31": "ballroom",
+    "32": "bamboo forest",
+    "33": "banquet hall",
+    "34": "bar",
+    "35": "barn",
+    "36": "barndoor",
+    "37": "baseball field",
+    "38": "basement",
+    "39": "basilica",
+    "40": "basketball court outdoor",
+    "41": "bathroom",
+    "42": "batters box",
+    "43": "bayou",
+    "44": "bazaar indoor",
+    "45": "bazaar outdoor",
+    "46": "beach",
+    "47": "beauty salon",
+    "48": "bedroom",
+    "49": "berth",
+    "50": "biology laboratory",
+    "51": "bistro indoor",
+    "52": "boardwalk",
+    "53": "boat deck",
+    "54": "boathouse",
+    "55": "bookstore",
+    "56": "booth indoor",
+    "57": "botanical garden",
+    "58": "bow window indoor",
+    "59": "bow window outdoor",
+    "60": "bowling alley",
+    "61": "boxing ring",
+    "62": "brewery indoor",
+    "63": "bridge",
+    "64": "building facade",
+    "65": "bullring",
+    "66": "burial chamber",
+    "67": "bus interior",
+    "68": "butchers shop",
+    "69": "butte",
+    "70": "cabin outdoor",
+    "71": "cafeteria",
+    "72": "campsite",
+    "73": "campus",
+    "74": "canal natural",
+    "75": "canal urban",
+    "76": "candy store",
+    "77": "canyon",
+    "78": "car interior backseat",
+    "79": "car interior frontseat",
+    "80": "carrousel",
+    "81": "casino indoor",
+    "82": "castle",
+    "83": "catacomb",
+    "84": "cathedral indoor",
+    "85": "cathedral outdoor",
+    "86": "cavern indoor",
+    "87": "cemetery",
+    "88": "chalet",
+    "89": "cheese factory",
+    "90": "chemistry lab",
+    "91": "chicken coop indoor",
+    "92": "chicken coop outdoor",
+    "93": "childs room",
+    "94": "church indoor",
+    "95": "church outdoor",
+    "96": "classroom",
+    "97": "clean room",
+    "98": "cliff",
+    "99": "cloister indoor",
+    "100": "closet",
+    "101": "clothing store",
+    "102": "coast",
+    "103": "cockpit",
+    "104": "coffee shop",
+    "105": "computer room",
+    "106": "conference center",
+    "107": "conference room",
+    "108": "construction site",
+    "109": "control room",
+    "110": "control tower outdoor",
+    "111": "corn field",
+    "112": "corral",
+    "113": "corridor",
+    "114": "cottage garden",
+    "115": "courthouse",
+    "116": "courtroom",
+    "117": "courtyard",
+    "118": "covered bridge exterior",
+    "119": "creek",
+    "120": "crevasse",
+    "121": "crosswalk",
+    "122": "cubicle office",
+    "123": "dam",
+    "124": "delicatessen",
+    "125": "dentists office",
+    "126": "desert sand",
+    "127": "desert vegetation",
+    "128": "diner indoor",
+    "129": "diner outdoor",
+    "130": "dinette home",
+    "131": "dinette vehicle",
+    "132": "dining car",
+    "133": "dining room",
+    "134": "discotheque",
+    "135": "dock",
+    "136": "doorway outdoor",
+    "137": "dorm room",
+    "138": "driveway",
+    "139": "driving range outdoor",
+    "140": "drugstore",
+    "141": "electrical substation",
+    "142": "elevator door",
+    "143": "elevator interior",
+    "144": "elevator shaft",
+    "145": "engine room",
+    "146": "escalator indoor",
+    "147": "excavation",
+    "148": "factory indoor",
+    "149": "fairway",
+    "150": "fastfood restaurant",
+    "151": "field cultivated",
+    "152": "field wild",
+    "153": "fire escape",
+    "154": "fire station",
+    "155": "firing range indoor",
+    "156": "fishpond",
+    "157": "florist shop indoor",
+    "158": "food court",
+    "159": "forest broadleaf",
+    "160": "forest needleleaf",
+    "161": "forest path",
+    "162": "forest road",
+    "163": "formal garden",
+    "164": "fountain",
+    "165": "galley",
+    "166": "game room",
+    "167": "garage indoor",
+    "168": "garbage dump",
+    "169": "gas station",
+    "170": "gazebo exterior",
+    "171": "general store indoor",
+    "172": "general store outdoor",
+    "173": "gift shop",
+    "174": "golf course",
+    "175": "greenhouse indoor",
+    "176": "greenhouse outdoor",
+    "177": "gymnasium indoor",
+    "178": "hangar indoor",
+    "179": "hangar outdoor",
+    "180": "harbor",
+    "181": "hayfield",
+    "182": "heliport",
+    "183": "herb garden",
+    "184": "highway",
+    "185": "hill",
+    "186": "home office",
+    "187": "hospital",
+    "188": "hospital room",
+    "189": "hot spring",
+    "190": "hot tub outdoor",
+    "191": "hotel outdoor",
+    "192": "hotel room",
+    "193": "house",
+    "194": "hunting lodge outdoor",
+    "195": "ice cream parlor",
+    "196": "ice floe",
+    "197": "ice shelf",
+    "198": "ice skating rink indoor",
+    "199": "ice skating rink outdoor",
+    "200": "iceberg",
+    "201": "igloo",
+    "202": "industrial area",
+    "203": "inn outdoor",
+    "204": "islet",
+    "205": "jacuzzi indoor",
+    "206": "jail cell",
+    "207": "jail indoor",
+    "208": "jewelry shop",
+    "209": "kasbah",
+    "210": "kennel indoor",
+    "211": "kennel outdoor",
+    "212": "kindergarden classroom",
+    "213": "kitchen",
+    "214": "kitchenette",
+    "215": "labyrinth outdoor",
+    "216": "lake natural",
+    "217": "landfill",
+    "218": "landing deck",
+    "219": "laundromat",
+    "220": "lecture room",
+    "221": "library indoor",
+    "222": "library outdoor",
+    "223": "lido deck outdoor",
+    "224": "lift bridge",
+    "225": "lighthouse",
+    "226": "limousine interior",
+    "227": "living room",
+    "228": "lobby",
+    "229": "lock chamber",
+    "230": "locker room",
+    "231": "mansion",
+    "232": "manufactured home",
+    "233": "market indoor",
+    "234": "market outdoor",
+    "235": "marsh",
+    "236": "martial arts gym",
+    "237": "mausoleum",
+    "238": "medina",
+    "239": "moat water",
+    "240": "monastery outdoor",
+    "241": "mosque indoor",
+    "242": "mosque outdoor",
+    "243": "motel",
+    "244": "mountain",
+    "245": "mountain snowy",
+    "246": "movie theater indoor",
+    "247": "museum indoor",
+    "248": "music store",
+    "249": "music studio",
+    "250": "nuclear power plant outdoor",
+    "251": "nursery",
+    "252": "oast house",
+    "253": "observatory outdoor",
+    "254": "ocean",
+    "255": "office",
+    "256": "office building",
+    "257": "oil refinery outdoor",
+    "258": "oilrig",
+    "259": "operating room",
+    "260": "orchard",
+    "261": "outhouse outdoor",
+    "262": "pagoda",
+    "263": "palace",
+    "264": "pantry",
+    "265": "park",
+    "266": "parking garage indoor",
+    "267": "parking garage outdoor",
+    "268": "parking lot",
+    "269": "parlor",
+    "270": "pasture",
+    "271": "patio",
+    "272": "pavilion",
+    "273": "pharmacy",
+    "274": "phone booth",
+    "275": "physics laboratory",
+    "276": "picnic area",
+    "277": "pilothouse indoor",
+    "278": "planetarium outdoor",
+    "279": "playground",
+    "280": "playroom",
+    "281": "plaza",
+    "282": "podium indoor",
+    "283": "podium outdoor",
+    "284": "pond",
+    "285": "poolroom establishment",
+    "286": "poolroom home",
+    "287": "power plant outdoor",
+    "288": "promenade deck",
+    "289": "pub indoor",
+    "290": "pulpit",
+    "291": "putting green",
+    "292": "racecourse",
+    "293": "raceway",
+    "294": "raft",
+    "295": "railroad track",
+    "296": "rainforest",
+    "297": "reception",
+    "298": "recreation room",
+    "299": "residential neighborhood",
+    "300": "restaurant",
+    "301": "restaurant kitchen",
+    "302": "restaurant patio",
+    "303": "rice paddy",
+    "304": "riding arena",
+    "305": "river",
+    "306": "rock arch",
+    "307": "rope bridge",
+    "308": "ruin",
+    "309": "runway",
+    "310": "sandbar",
+    "311": "sandbox",
+    "312": "sauna",
+    "313": "schoolhouse",
+    "314": "sea cliff",
+    "315": "server room",
+    "316": "shed",
+    "317": "shoe shop",
+    "318": "shopfront",
+    "319": "shopping mall indoor",
+    "320": "shower",
+    "321": "skatepark",
+    "322": "ski lodge",
+    "323": "ski resort",
+    "324": "ski slope",
+    "325": "sky",
+    "326": "skyscraper",
+    "327": "slum",
+    "328": "snowfield",
+    "329": "squash court",
+    "330": "stable",
+    "331": "stadium baseball",
+    "332": "stadium football",
+    "333": "stage indoor",
+    "334": "staircase",
+    "335": "street",
+    "336": "subway interior",
+    "337": "subway station platform",
+    "338": "supermarket",
+    "339": "sushi bar",
+    "340": "swamp",
+    "341": "swimming pool indoor",
+    "342": "swimming pool outdoor",
+    "343": "synagogue indoor",
+    "344": "synagogue outdoor",
+    "345": "television studio",
+    "346": "temple east asia",
+    "347": "temple south asia",
+    "348": "tennis court indoor",
+    "349": "tennis court outdoor",
+    "350": "tent outdoor",
+    "351": "theater indoor procenium",
+    "352": "theater indoor seats",
+    "353": "thriftshop",
+    "354": "throne room",
+    "355": "ticket booth",
+    "356": "toll plaza",
+    "357": "topiary garden",
+    "358": "tower",
+    "359": "toyshop",
+    "360": "track outdoor",
+    "361": "train railway",
+    "362": "train station platform",
+    "363": "tree farm",
+    "364": "tree house",
+    "365": "trench",
+    "366": "underwater coral reef",
+    "367": "utility room",
+    "368": "valley",
+    "369": "van interior",
+    "370": "vegetable garden",
+    "371": "veranda",
+    "372": "veterinarians office",
+    "373": "viaduct",
+    "374": "videostore",
+    "375": "village",
+    "376": "vineyard",
+    "377": "volcano",
+    "378": "volleyball court indoor",
+    "379": "volleyball court outdoor",
+    "380": "waiting room",
+    "381": "warehouse indoor",
+    "382": "water tower",
+    "383": "waterfall block",
+    "384": "waterfall fan",
+    "385": "waterfall plunge",
+    "386": "watering hole",
+    "387": "wave",
+    "388": "wet bar",
+    "389": "wheat field",
+    "390": "wind farm",
+    "391": "windmill",
+    "392": "wine cellar barrel storage",
+    "393": "wine cellar bottle storage",
+    "394": "wrestling ring indoor",
+    "395": "yard",
+    "396": "youth hostel"
+  },
+  "label2id": {
+    "abbey": 0,
+    "airplane cabin": 1,
+    "airport terminal": 2,
+    "alley": 3,
+    "amphitheater": 4,
+    "amusement arcade": 5,
+    "amusement park": 6,
+    "anechoic chamber": 7,
+    "apartment building outdoor": 8,
+    "apse indoor": 9,
+    "aquarium": 10,
+    "aqueduct": 11,
+    "arch": 12,
+    "archive": 13,
+    "arrival gate outdoor": 14,
+    "art gallery": 15,
+    "art school": 16,
+    "art studio": 17,
+    "assembly line": 18,
+    "athletic field outdoor": 19,
+    "atrium public": 20,
+    "attic": 21,
+    "auditorium": 22,
+    "auto factory": 23,
+    "badlands": 24,
+    "badminton court indoor": 25,
+    "baggage claim": 26,
+    "bakery shop": 27,
+    "balcony exterior": 28,
+    "balcony interior": 29,
+    "ball pit": 30,
+    "ballroom": 31,
+    "bamboo forest": 32,
+    "banquet hall": 33,
+    "bar": 34,
+    "barn": 35,
+    "barndoor": 36,
+    "baseball field": 37,
+    "basement": 38,
+    "basilica": 39,
+    "basketball court outdoor": 40,
+    "bathroom": 41,
+    "batters box": 42,
+    "bayou": 43,
+    "bazaar indoor": 44,
+    "bazaar outdoor": 45,
+    "beach": 46,
+    "beauty salon": 47,
+    "bedroom": 48,
+    "berth": 49,
+    "biology laboratory": 50,
+    "bistro indoor": 51,
+    "boardwalk": 52,
+    "boat deck": 53,
+    "boathouse": 54,
+    "bookstore": 55,
+    "booth indoor": 56,
+    "botanical garden": 57,
+    "bow window indoor": 58,
+    "bow window outdoor": 59,
+    "bowling alley": 60,
+    "boxing ring": 61,
+    "brewery indoor": 62,
+    "bridge": 63,
+    "building facade": 64,
+    "bullring": 65,
+    "burial chamber": 66,
+    "bus interior": 67,
+    "butchers shop": 68,
+    "butte": 69,
+    "cabin outdoor": 70,
+    "cafeteria": 71,
+    "campsite": 72,
+    "campus": 73,
+    "canal natural": 74,
+    "canal urban": 75,
+    "candy store": 76,
+    "canyon": 77,
+    "car interior backseat": 78,
+    "car interior frontseat": 79,
+    "carrousel": 80,
+    "casino indoor": 81,
+    "castle": 82,
+    "catacomb": 83,
+    "cathedral indoor": 84,
+    "cathedral outdoor": 85,
+    "cavern indoor": 86,
+    "cemetery": 87,
+    "chalet": 88,
+    "cheese factory": 89,
+    "chemistry lab": 90,
+    "chicken coop indoor": 91,
+    "chicken coop outdoor": 92,
+    "childs room": 93,
+    "church indoor": 94,
+    "church outdoor": 95,
+    "classroom": 96,
+    "clean room": 97,
+    "cliff": 98,
+    "cloister indoor": 99,
+    "closet": 100,
+    "clothing store": 101,
+    "coast": 102,
+    "cockpit": 103,
+    "coffee shop": 104,
+    "computer room": 105,
+    "conference center": 106,
+    "conference room": 107,
+    "construction site": 108,
+    "control room": 109,
+    "control tower outdoor": 110,
+    "corn field": 111,
+    "corral": 112,
+    "corridor": 113,
+    "cottage garden": 114,
+    "courthouse": 115,
+    "courtroom": 116,
+    "courtyard": 117,
+    "covered bridge exterior": 118,
+    "creek": 119,
+    "crevasse": 120,
+    "crosswalk": 121,
+    "cubicle office": 122,
+    "dam": 123,
+    "delicatessen": 124,
+    "dentists office": 125,
+    "desert sand": 126,
+    "desert vegetation": 127,
+    "diner indoor": 128,
+    "diner outdoor": 129,
+    "dinette home": 130,
+    "dinette vehicle": 131,
+    "dining car": 132,
+    "dining room": 133,
+    "discotheque": 134,
+    "dock": 135,
+    "doorway outdoor": 136,
+    "dorm room": 137,
+    "driveway": 138,
+    "driving range outdoor": 139,
+    "drugstore": 140,
+    "electrical substation": 141,
+    "elevator door": 142,
+    "elevator interior": 143,
+    "elevator shaft": 144,
+    "engine room": 145,
+    "escalator indoor": 146,
+    "excavation": 147,
+    "factory indoor": 148,
+    "fairway": 149,
+    "fastfood restaurant": 150,
+    "field cultivated": 151,
+    "field wild": 152,
+    "fire escape": 153,
+    "fire station": 154,
+    "firing range indoor": 155,
+    "fishpond": 156,
+    "florist shop indoor": 157,
+    "food court": 158,
+    "forest broadleaf": 159,
+    "forest needleleaf": 160,
+    "forest path": 161,
+    "forest road": 162,
+    "formal garden": 163,
+    "fountain": 164,
+    "galley": 165,
+    "game room": 166,
+    "garage indoor": 167,
+    "garbage dump": 168,
+    "gas station": 169,
+    "gazebo exterior": 170,
+    "general store indoor": 171,
+    "general store outdoor": 172,
+    "gift shop": 173,
+    "golf course": 174,
+    "greenhouse indoor": 175,
+    "greenhouse outdoor": 176,
+    "gymnasium indoor": 177,
+    "hangar indoor": 178,
+    "hangar outdoor": 179,
+    "harbor": 180,
+    "hayfield": 181,
+    "heliport": 182,
+    "herb garden": 183,
+    "highway": 184,
+    "hill": 185,
+    "home office": 186,
+    "hospital": 187,
+    "hospital room": 188,
+    "hot spring": 189,
+    "hot tub outdoor": 190,
+    "hotel outdoor": 191,
+    "hotel room": 192,
+    "house": 193,
+    "hunting lodge outdoor": 194,
+    "ice cream parlor": 195,
+    "ice floe": 196,
+    "ice shelf": 197,
+    "ice skating rink indoor": 198,
+    "ice skating rink outdoor": 199,
+    "iceberg": 200,
+    "igloo": 201,
+    "industrial area": 202,
+    "inn outdoor": 203,
+    "islet": 204,
+    "jacuzzi indoor": 205,
+    "jail cell": 206,
+    "jail indoor": 207,
+    "jewelry shop": 208,
+    "kasbah": 209,
+    "kennel indoor": 210,
+    "kennel outdoor": 211,
+    "kindergarden classroom": 212,
+    "kitchen": 213,
+    "kitchenette": 214,
+    "labyrinth outdoor": 215,
+    "lake natural": 216,
+    "landfill": 217,
+    "landing deck": 218,
+    "laundromat": 219,
+    "lecture room": 220,
+    "library indoor": 221,
+    "library outdoor": 222,
+    "lido deck outdoor": 223,
+    "lift bridge": 224,
+    "lighthouse": 225,
+    "limousine interior": 226,
+    "living room": 227,
+    "lobby": 228,
+    "lock chamber": 229,
+    "locker room": 230,
+    "mansion": 231,
+    "manufactured home": 232,
+    "market indoor": 233,
+    "market outdoor": 234,
+    "marsh": 235,
+    "martial arts gym": 236,
+    "mausoleum": 237,
+    "medina": 238,
+    "moat water": 239,
+    "monastery outdoor": 240,
+    "mosque indoor": 241,
+    "mosque outdoor": 242,
+    "motel": 243,
+    "mountain": 244,
+    "mountain snowy": 245,
+    "movie theater indoor": 246,
+    "museum indoor": 247,
+    "music store": 248,
+    "music studio": 249,
+    "nuclear power plant outdoor": 250,
+    "nursery": 251,
+    "oast house": 252,
+    "observatory outdoor": 253,
+    "ocean": 254,
+    "office": 255,
+    "office building": 256,
+    "oil refinery outdoor": 257,
+    "oilrig": 258,
+    "operating room": 259,
+    "orchard": 260,
+    "outhouse outdoor": 261,
+    "pagoda": 262,
+    "palace": 263,
+    "pantry": 264,
+    "park": 265,
+    "parking garage indoor": 266,
+    "parking garage outdoor": 267,
+    "parking lot": 268,
+    "parlor": 269,
+    "pasture": 270,
+    "patio": 271,
+    "pavilion": 272,
+    "pharmacy": 273,
+    "phone booth": 274,
+    "physics laboratory": 275,
+    "picnic area": 276,
+    "pilothouse indoor": 277,
+    "planetarium outdoor": 278,
+    "playground": 279,
+    "playroom": 280,
+    "plaza": 281,
+    "podium indoor": 282,
+    "podium outdoor": 283,
+    "pond": 284,
+    "poolroom establishment": 285,
+    "poolroom home": 286,
+    "power plant outdoor": 287,
+    "promenade deck": 288,
+    "pub indoor": 289,
+    "pulpit": 290,
+    "putting green": 291,
+    "racecourse": 292,
+    "raceway": 293,
+    "raft": 294,
+    "railroad track": 295,
+    "rainforest": 296,
+    "reception": 297,
+    "recreation room": 298,
+    "residential neighborhood": 299,
+    "restaurant": 300,
+    "restaurant kitchen": 301,
+    "restaurant patio": 302,
+    "rice paddy": 303,
+    "riding arena": 304,
+    "river": 305,
+    "rock arch": 306,
+    "rope bridge": 307,
+    "ruin": 308,
+    "runway": 309,
+    "sandbar": 310,
+    "sandbox": 311,
+    "sauna": 312,
+    "schoolhouse": 313,
+    "sea cliff": 314,
+    "server room": 315,
+    "shed": 316,
+    "shoe shop": 317,
+    "shopfront": 318,
+    "shopping mall indoor": 319,
+    "shower": 320,
+    "skatepark": 321,
+    "ski lodge": 322,
+    "ski resort": 323,
+    "ski slope": 324,
+    "sky": 325,
+    "skyscraper": 326,
+    "slum": 327,
+    "snowfield": 328,
+    "squash court": 329,
+    "stable": 330,
+    "stadium baseball": 331,
+    "stadium football": 332,
+    "stage indoor": 333,
+    "staircase": 334,
+    "street": 335,
+    "subway interior": 336,
+    "subway station platform": 337,
+    "supermarket": 338,
+    "sushi bar": 339,
+    "swamp": 340,
+    "swimming pool indoor": 341,
+    "swimming pool outdoor": 342,
+    "synagogue indoor": 343,
+    "synagogue outdoor": 344,
+    "television studio": 345,
+    "temple east asia": 346,
+    "temple south asia": 347,
+    "tennis court indoor": 348,
+    "tennis court outdoor": 349,
+    "tent outdoor": 350,
+    "theater indoor procenium": 351,
+    "theater indoor seats": 352,
+    "thriftshop": 353,
+    "throne room": 354,
+    "ticket booth": 355,
+    "toll plaza": 356,
+    "topiary garden": 357,
+    "tower": 358,
+    "toyshop": 359,
+    "track outdoor": 360,
+    "train railway": 361,
+    "train station platform": 362,
+    "tree farm": 363,
+    "tree house": 364,
+    "trench": 365,
+    "underwater coral reef": 366,
+    "utility room": 367,
+    "valley": 368,
+    "van interior": 369,
+    "vegetable garden": 370,
+    "veranda": 371,
+    "veterinarians office": 372,
+    "viaduct": 373,
+    "videostore": 374,
+    "village": 375,
+    "vineyard": 376,
+    "volcano": 377,
+    "volleyball court indoor": 378,
+    "volleyball court outdoor": 379,
+    "waiting room": 380,
+    "warehouse indoor": 381,
+    "water tower": 382,
+    "waterfall block": 383,
+    "waterfall fan": 384,
+    "waterfall plunge": 385,
+    "watering hole": 386,
+    "wave": 387,
+    "wet bar": 388,
+    "wheat field": 389,
+    "wind farm": 390,
+    "windmill": 391,
+    "wine cellar barrel storage": 392,
+    "wine cellar bottle storage": 393,
+    "wrestling ring indoor": 394,
+    "yard": 395,
+    "youth hostel": 396
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet18-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/README.md b/resnet18-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..59f2b1ef6e869917954ab70e99b757e8490e1487
--- /dev/null
+++ b/resnet18-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset sun397.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: sun397
+    pretrained: true
+test_datasets: null
+train_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: train
+type: transformers
+val_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: test
+```
+
diff --git a/resnet18-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/config.json b/resnet18-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..886da3497a7114ff31c2408ec559a773285de738
--- /dev/null
+++ b/resnet18-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,837 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "abbey",
+    "1": "airplane cabin",
+    "2": "airport terminal",
+    "3": "alley",
+    "4": "amphitheater",
+    "5": "amusement arcade",
+    "6": "amusement park",
+    "7": "anechoic chamber",
+    "8": "apartment building outdoor",
+    "9": "apse indoor",
+    "10": "aquarium",
+    "11": "aqueduct",
+    "12": "arch",
+    "13": "archive",
+    "14": "arrival gate outdoor",
+    "15": "art gallery",
+    "16": "art school",
+    "17": "art studio",
+    "18": "assembly line",
+    "19": "athletic field outdoor",
+    "20": "atrium public",
+    "21": "attic",
+    "22": "auditorium",
+    "23": "auto factory",
+    "24": "badlands",
+    "25": "badminton court indoor",
+    "26": "baggage claim",
+    "27": "bakery shop",
+    "28": "balcony exterior",
+    "29": "balcony interior",
+    "30": "ball pit",
+    "31": "ballroom",
+    "32": "bamboo forest",
+    "33": "banquet hall",
+    "34": "bar",
+    "35": "barn",
+    "36": "barndoor",
+    "37": "baseball field",
+    "38": "basement",
+    "39": "basilica",
+    "40": "basketball court outdoor",
+    "41": "bathroom",
+    "42": "batters box",
+    "43": "bayou",
+    "44": "bazaar indoor",
+    "45": "bazaar outdoor",
+    "46": "beach",
+    "47": "beauty salon",
+    "48": "bedroom",
+    "49": "berth",
+    "50": "biology laboratory",
+    "51": "bistro indoor",
+    "52": "boardwalk",
+    "53": "boat deck",
+    "54": "boathouse",
+    "55": "bookstore",
+    "56": "booth indoor",
+    "57": "botanical garden",
+    "58": "bow window indoor",
+    "59": "bow window outdoor",
+    "60": "bowling alley",
+    "61": "boxing ring",
+    "62": "brewery indoor",
+    "63": "bridge",
+    "64": "building facade",
+    "65": "bullring",
+    "66": "burial chamber",
+    "67": "bus interior",
+    "68": "butchers shop",
+    "69": "butte",
+    "70": "cabin outdoor",
+    "71": "cafeteria",
+    "72": "campsite",
+    "73": "campus",
+    "74": "canal natural",
+    "75": "canal urban",
+    "76": "candy store",
+    "77": "canyon",
+    "78": "car interior backseat",
+    "79": "car interior frontseat",
+    "80": "carrousel",
+    "81": "casino indoor",
+    "82": "castle",
+    "83": "catacomb",
+    "84": "cathedral indoor",
+    "85": "cathedral outdoor",
+    "86": "cavern indoor",
+    "87": "cemetery",
+    "88": "chalet",
+    "89": "cheese factory",
+    "90": "chemistry lab",
+    "91": "chicken coop indoor",
+    "92": "chicken coop outdoor",
+    "93": "childs room",
+    "94": "church indoor",
+    "95": "church outdoor",
+    "96": "classroom",
+    "97": "clean room",
+    "98": "cliff",
+    "99": "cloister indoor",
+    "100": "closet",
+    "101": "clothing store",
+    "102": "coast",
+    "103": "cockpit",
+    "104": "coffee shop",
+    "105": "computer room",
+    "106": "conference center",
+    "107": "conference room",
+    "108": "construction site",
+    "109": "control room",
+    "110": "control tower outdoor",
+    "111": "corn field",
+    "112": "corral",
+    "113": "corridor",
+    "114": "cottage garden",
+    "115": "courthouse",
+    "116": "courtroom",
+    "117": "courtyard",
+    "118": "covered bridge exterior",
+    "119": "creek",
+    "120": "crevasse",
+    "121": "crosswalk",
+    "122": "cubicle office",
+    "123": "dam",
+    "124": "delicatessen",
+    "125": "dentists office",
+    "126": "desert sand",
+    "127": "desert vegetation",
+    "128": "diner indoor",
+    "129": "diner outdoor",
+    "130": "dinette home",
+    "131": "dinette vehicle",
+    "132": "dining car",
+    "133": "dining room",
+    "134": "discotheque",
+    "135": "dock",
+    "136": "doorway outdoor",
+    "137": "dorm room",
+    "138": "driveway",
+    "139": "driving range outdoor",
+    "140": "drugstore",
+    "141": "electrical substation",
+    "142": "elevator door",
+    "143": "elevator interior",
+    "144": "elevator shaft",
+    "145": "engine room",
+    "146": "escalator indoor",
+    "147": "excavation",
+    "148": "factory indoor",
+    "149": "fairway",
+    "150": "fastfood restaurant",
+    "151": "field cultivated",
+    "152": "field wild",
+    "153": "fire escape",
+    "154": "fire station",
+    "155": "firing range indoor",
+    "156": "fishpond",
+    "157": "florist shop indoor",
+    "158": "food court",
+    "159": "forest broadleaf",
+    "160": "forest needleleaf",
+    "161": "forest path",
+    "162": "forest road",
+    "163": "formal garden",
+    "164": "fountain",
+    "165": "galley",
+    "166": "game room",
+    "167": "garage indoor",
+    "168": "garbage dump",
+    "169": "gas station",
+    "170": "gazebo exterior",
+    "171": "general store indoor",
+    "172": "general store outdoor",
+    "173": "gift shop",
+    "174": "golf course",
+    "175": "greenhouse indoor",
+    "176": "greenhouse outdoor",
+    "177": "gymnasium indoor",
+    "178": "hangar indoor",
+    "179": "hangar outdoor",
+    "180": "harbor",
+    "181": "hayfield",
+    "182": "heliport",
+    "183": "herb garden",
+    "184": "highway",
+    "185": "hill",
+    "186": "home office",
+    "187": "hospital",
+    "188": "hospital room",
+    "189": "hot spring",
+    "190": "hot tub outdoor",
+    "191": "hotel outdoor",
+    "192": "hotel room",
+    "193": "house",
+    "194": "hunting lodge outdoor",
+    "195": "ice cream parlor",
+    "196": "ice floe",
+    "197": "ice shelf",
+    "198": "ice skating rink indoor",
+    "199": "ice skating rink outdoor",
+    "200": "iceberg",
+    "201": "igloo",
+    "202": "industrial area",
+    "203": "inn outdoor",
+    "204": "islet",
+    "205": "jacuzzi indoor",
+    "206": "jail cell",
+    "207": "jail indoor",
+    "208": "jewelry shop",
+    "209": "kasbah",
+    "210": "kennel indoor",
+    "211": "kennel outdoor",
+    "212": "kindergarden classroom",
+    "213": "kitchen",
+    "214": "kitchenette",
+    "215": "labyrinth outdoor",
+    "216": "lake natural",
+    "217": "landfill",
+    "218": "landing deck",
+    "219": "laundromat",
+    "220": "lecture room",
+    "221": "library indoor",
+    "222": "library outdoor",
+    "223": "lido deck outdoor",
+    "224": "lift bridge",
+    "225": "lighthouse",
+    "226": "limousine interior",
+    "227": "living room",
+    "228": "lobby",
+    "229": "lock chamber",
+    "230": "locker room",
+    "231": "mansion",
+    "232": "manufactured home",
+    "233": "market indoor",
+    "234": "market outdoor",
+    "235": "marsh",
+    "236": "martial arts gym",
+    "237": "mausoleum",
+    "238": "medina",
+    "239": "moat water",
+    "240": "monastery outdoor",
+    "241": "mosque indoor",
+    "242": "mosque outdoor",
+    "243": "motel",
+    "244": "mountain",
+    "245": "mountain snowy",
+    "246": "movie theater indoor",
+    "247": "museum indoor",
+    "248": "music store",
+    "249": "music studio",
+    "250": "nuclear power plant outdoor",
+    "251": "nursery",
+    "252": "oast house",
+    "253": "observatory outdoor",
+    "254": "ocean",
+    "255": "office",
+    "256": "office building",
+    "257": "oil refinery outdoor",
+    "258": "oilrig",
+    "259": "operating room",
+    "260": "orchard",
+    "261": "outhouse outdoor",
+    "262": "pagoda",
+    "263": "palace",
+    "264": "pantry",
+    "265": "park",
+    "266": "parking garage indoor",
+    "267": "parking garage outdoor",
+    "268": "parking lot",
+    "269": "parlor",
+    "270": "pasture",
+    "271": "patio",
+    "272": "pavilion",
+    "273": "pharmacy",
+    "274": "phone booth",
+    "275": "physics laboratory",
+    "276": "picnic area",
+    "277": "pilothouse indoor",
+    "278": "planetarium outdoor",
+    "279": "playground",
+    "280": "playroom",
+    "281": "plaza",
+    "282": "podium indoor",
+    "283": "podium outdoor",
+    "284": "pond",
+    "285": "poolroom establishment",
+    "286": "poolroom home",
+    "287": "power plant outdoor",
+    "288": "promenade deck",
+    "289": "pub indoor",
+    "290": "pulpit",
+    "291": "putting green",
+    "292": "racecourse",
+    "293": "raceway",
+    "294": "raft",
+    "295": "railroad track",
+    "296": "rainforest",
+    "297": "reception",
+    "298": "recreation room",
+    "299": "residential neighborhood",
+    "300": "restaurant",
+    "301": "restaurant kitchen",
+    "302": "restaurant patio",
+    "303": "rice paddy",
+    "304": "riding arena",
+    "305": "river",
+    "306": "rock arch",
+    "307": "rope bridge",
+    "308": "ruin",
+    "309": "runway",
+    "310": "sandbar",
+    "311": "sandbox",
+    "312": "sauna",
+    "313": "schoolhouse",
+    "314": "sea cliff",
+    "315": "server room",
+    "316": "shed",
+    "317": "shoe shop",
+    "318": "shopfront",
+    "319": "shopping mall indoor",
+    "320": "shower",
+    "321": "skatepark",
+    "322": "ski lodge",
+    "323": "ski resort",
+    "324": "ski slope",
+    "325": "sky",
+    "326": "skyscraper",
+    "327": "slum",
+    "328": "snowfield",
+    "329": "squash court",
+    "330": "stable",
+    "331": "stadium baseball",
+    "332": "stadium football",
+    "333": "stage indoor",
+    "334": "staircase",
+    "335": "street",
+    "336": "subway interior",
+    "337": "subway station platform",
+    "338": "supermarket",
+    "339": "sushi bar",
+    "340": "swamp",
+    "341": "swimming pool indoor",
+    "342": "swimming pool outdoor",
+    "343": "synagogue indoor",
+    "344": "synagogue outdoor",
+    "345": "television studio",
+    "346": "temple east asia",
+    "347": "temple south asia",
+    "348": "tennis court indoor",
+    "349": "tennis court outdoor",
+    "350": "tent outdoor",
+    "351": "theater indoor procenium",
+    "352": "theater indoor seats",
+    "353": "thriftshop",
+    "354": "throne room",
+    "355": "ticket booth",
+    "356": "toll plaza",
+    "357": "topiary garden",
+    "358": "tower",
+    "359": "toyshop",
+    "360": "track outdoor",
+    "361": "train railway",
+    "362": "train station platform",
+    "363": "tree farm",
+    "364": "tree house",
+    "365": "trench",
+    "366": "underwater coral reef",
+    "367": "utility room",
+    "368": "valley",
+    "369": "van interior",
+    "370": "vegetable garden",
+    "371": "veranda",
+    "372": "veterinarians office",
+    "373": "viaduct",
+    "374": "videostore",
+    "375": "village",
+    "376": "vineyard",
+    "377": "volcano",
+    "378": "volleyball court indoor",
+    "379": "volleyball court outdoor",
+    "380": "waiting room",
+    "381": "warehouse indoor",
+    "382": "water tower",
+    "383": "waterfall block",
+    "384": "waterfall fan",
+    "385": "waterfall plunge",
+    "386": "watering hole",
+    "387": "wave",
+    "388": "wet bar",
+    "389": "wheat field",
+    "390": "wind farm",
+    "391": "windmill",
+    "392": "wine cellar barrel storage",
+    "393": "wine cellar bottle storage",
+    "394": "wrestling ring indoor",
+    "395": "yard",
+    "396": "youth hostel"
+  },
+  "label2id": {
+    "abbey": 0,
+    "airplane cabin": 1,
+    "airport terminal": 2,
+    "alley": 3,
+    "amphitheater": 4,
+    "amusement arcade": 5,
+    "amusement park": 6,
+    "anechoic chamber": 7,
+    "apartment building outdoor": 8,
+    "apse indoor": 9,
+    "aquarium": 10,
+    "aqueduct": 11,
+    "arch": 12,
+    "archive": 13,
+    "arrival gate outdoor": 14,
+    "art gallery": 15,
+    "art school": 16,
+    "art studio": 17,
+    "assembly line": 18,
+    "athletic field outdoor": 19,
+    "atrium public": 20,
+    "attic": 21,
+    "auditorium": 22,
+    "auto factory": 23,
+    "badlands": 24,
+    "badminton court indoor": 25,
+    "baggage claim": 26,
+    "bakery shop": 27,
+    "balcony exterior": 28,
+    "balcony interior": 29,
+    "ball pit": 30,
+    "ballroom": 31,
+    "bamboo forest": 32,
+    "banquet hall": 33,
+    "bar": 34,
+    "barn": 35,
+    "barndoor": 36,
+    "baseball field": 37,
+    "basement": 38,
+    "basilica": 39,
+    "basketball court outdoor": 40,
+    "bathroom": 41,
+    "batters box": 42,
+    "bayou": 43,
+    "bazaar indoor": 44,
+    "bazaar outdoor": 45,
+    "beach": 46,
+    "beauty salon": 47,
+    "bedroom": 48,
+    "berth": 49,
+    "biology laboratory": 50,
+    "bistro indoor": 51,
+    "boardwalk": 52,
+    "boat deck": 53,
+    "boathouse": 54,
+    "bookstore": 55,
+    "booth indoor": 56,
+    "botanical garden": 57,
+    "bow window indoor": 58,
+    "bow window outdoor": 59,
+    "bowling alley": 60,
+    "boxing ring": 61,
+    "brewery indoor": 62,
+    "bridge": 63,
+    "building facade": 64,
+    "bullring": 65,
+    "burial chamber": 66,
+    "bus interior": 67,
+    "butchers shop": 68,
+    "butte": 69,
+    "cabin outdoor": 70,
+    "cafeteria": 71,
+    "campsite": 72,
+    "campus": 73,
+    "canal natural": 74,
+    "canal urban": 75,
+    "candy store": 76,
+    "canyon": 77,
+    "car interior backseat": 78,
+    "car interior frontseat": 79,
+    "carrousel": 80,
+    "casino indoor": 81,
+    "castle": 82,
+    "catacomb": 83,
+    "cathedral indoor": 84,
+    "cathedral outdoor": 85,
+    "cavern indoor": 86,
+    "cemetery": 87,
+    "chalet": 88,
+    "cheese factory": 89,
+    "chemistry lab": 90,
+    "chicken coop indoor": 91,
+    "chicken coop outdoor": 92,
+    "childs room": 93,
+    "church indoor": 94,
+    "church outdoor": 95,
+    "classroom": 96,
+    "clean room": 97,
+    "cliff": 98,
+    "cloister indoor": 99,
+    "closet": 100,
+    "clothing store": 101,
+    "coast": 102,
+    "cockpit": 103,
+    "coffee shop": 104,
+    "computer room": 105,
+    "conference center": 106,
+    "conference room": 107,
+    "construction site": 108,
+    "control room": 109,
+    "control tower outdoor": 110,
+    "corn field": 111,
+    "corral": 112,
+    "corridor": 113,
+    "cottage garden": 114,
+    "courthouse": 115,
+    "courtroom": 116,
+    "courtyard": 117,
+    "covered bridge exterior": 118,
+    "creek": 119,
+    "crevasse": 120,
+    "crosswalk": 121,
+    "cubicle office": 122,
+    "dam": 123,
+    "delicatessen": 124,
+    "dentists office": 125,
+    "desert sand": 126,
+    "desert vegetation": 127,
+    "diner indoor": 128,
+    "diner outdoor": 129,
+    "dinette home": 130,
+    "dinette vehicle": 131,
+    "dining car": 132,
+    "dining room": 133,
+    "discotheque": 134,
+    "dock": 135,
+    "doorway outdoor": 136,
+    "dorm room": 137,
+    "driveway": 138,
+    "driving range outdoor": 139,
+    "drugstore": 140,
+    "electrical substation": 141,
+    "elevator door": 142,
+    "elevator interior": 143,
+    "elevator shaft": 144,
+    "engine room": 145,
+    "escalator indoor": 146,
+    "excavation": 147,
+    "factory indoor": 148,
+    "fairway": 149,
+    "fastfood restaurant": 150,
+    "field cultivated": 151,
+    "field wild": 152,
+    "fire escape": 153,
+    "fire station": 154,
+    "firing range indoor": 155,
+    "fishpond": 156,
+    "florist shop indoor": 157,
+    "food court": 158,
+    "forest broadleaf": 159,
+    "forest needleleaf": 160,
+    "forest path": 161,
+    "forest road": 162,
+    "formal garden": 163,
+    "fountain": 164,
+    "galley": 165,
+    "game room": 166,
+    "garage indoor": 167,
+    "garbage dump": 168,
+    "gas station": 169,
+    "gazebo exterior": 170,
+    "general store indoor": 171,
+    "general store outdoor": 172,
+    "gift shop": 173,
+    "golf course": 174,
+    "greenhouse indoor": 175,
+    "greenhouse outdoor": 176,
+    "gymnasium indoor": 177,
+    "hangar indoor": 178,
+    "hangar outdoor": 179,
+    "harbor": 180,
+    "hayfield": 181,
+    "heliport": 182,
+    "herb garden": 183,
+    "highway": 184,
+    "hill": 185,
+    "home office": 186,
+    "hospital": 187,
+    "hospital room": 188,
+    "hot spring": 189,
+    "hot tub outdoor": 190,
+    "hotel outdoor": 191,
+    "hotel room": 192,
+    "house": 193,
+    "hunting lodge outdoor": 194,
+    "ice cream parlor": 195,
+    "ice floe": 196,
+    "ice shelf": 197,
+    "ice skating rink indoor": 198,
+    "ice skating rink outdoor": 199,
+    "iceberg": 200,
+    "igloo": 201,
+    "industrial area": 202,
+    "inn outdoor": 203,
+    "islet": 204,
+    "jacuzzi indoor": 205,
+    "jail cell": 206,
+    "jail indoor": 207,
+    "jewelry shop": 208,
+    "kasbah": 209,
+    "kennel indoor": 210,
+    "kennel outdoor": 211,
+    "kindergarden classroom": 212,
+    "kitchen": 213,
+    "kitchenette": 214,
+    "labyrinth outdoor": 215,
+    "lake natural": 216,
+    "landfill": 217,
+    "landing deck": 218,
+    "laundromat": 219,
+    "lecture room": 220,
+    "library indoor": 221,
+    "library outdoor": 222,
+    "lido deck outdoor": 223,
+    "lift bridge": 224,
+    "lighthouse": 225,
+    "limousine interior": 226,
+    "living room": 227,
+    "lobby": 228,
+    "lock chamber": 229,
+    "locker room": 230,
+    "mansion": 231,
+    "manufactured home": 232,
+    "market indoor": 233,
+    "market outdoor": 234,
+    "marsh": 235,
+    "martial arts gym": 236,
+    "mausoleum": 237,
+    "medina": 238,
+    "moat water": 239,
+    "monastery outdoor": 240,
+    "mosque indoor": 241,
+    "mosque outdoor": 242,
+    "motel": 243,
+    "mountain": 244,
+    "mountain snowy": 245,
+    "movie theater indoor": 246,
+    "museum indoor": 247,
+    "music store": 248,
+    "music studio": 249,
+    "nuclear power plant outdoor": 250,
+    "nursery": 251,
+    "oast house": 252,
+    "observatory outdoor": 253,
+    "ocean": 254,
+    "office": 255,
+    "office building": 256,
+    "oil refinery outdoor": 257,
+    "oilrig": 258,
+    "operating room": 259,
+    "orchard": 260,
+    "outhouse outdoor": 261,
+    "pagoda": 262,
+    "palace": 263,
+    "pantry": 264,
+    "park": 265,
+    "parking garage indoor": 266,
+    "parking garage outdoor": 267,
+    "parking lot": 268,
+    "parlor": 269,
+    "pasture": 270,
+    "patio": 271,
+    "pavilion": 272,
+    "pharmacy": 273,
+    "phone booth": 274,
+    "physics laboratory": 275,
+    "picnic area": 276,
+    "pilothouse indoor": 277,
+    "planetarium outdoor": 278,
+    "playground": 279,
+    "playroom": 280,
+    "plaza": 281,
+    "podium indoor": 282,
+    "podium outdoor": 283,
+    "pond": 284,
+    "poolroom establishment": 285,
+    "poolroom home": 286,
+    "power plant outdoor": 287,
+    "promenade deck": 288,
+    "pub indoor": 289,
+    "pulpit": 290,
+    "putting green": 291,
+    "racecourse": 292,
+    "raceway": 293,
+    "raft": 294,
+    "railroad track": 295,
+    "rainforest": 296,
+    "reception": 297,
+    "recreation room": 298,
+    "residential neighborhood": 299,
+    "restaurant": 300,
+    "restaurant kitchen": 301,
+    "restaurant patio": 302,
+    "rice paddy": 303,
+    "riding arena": 304,
+    "river": 305,
+    "rock arch": 306,
+    "rope bridge": 307,
+    "ruin": 308,
+    "runway": 309,
+    "sandbar": 310,
+    "sandbox": 311,
+    "sauna": 312,
+    "schoolhouse": 313,
+    "sea cliff": 314,
+    "server room": 315,
+    "shed": 316,
+    "shoe shop": 317,
+    "shopfront": 318,
+    "shopping mall indoor": 319,
+    "shower": 320,
+    "skatepark": 321,
+    "ski lodge": 322,
+    "ski resort": 323,
+    "ski slope": 324,
+    "sky": 325,
+    "skyscraper": 326,
+    "slum": 327,
+    "snowfield": 328,
+    "squash court": 329,
+    "stable": 330,
+    "stadium baseball": 331,
+    "stadium football": 332,
+    "stage indoor": 333,
+    "staircase": 334,
+    "street": 335,
+    "subway interior": 336,
+    "subway station platform": 337,
+    "supermarket": 338,
+    "sushi bar": 339,
+    "swamp": 340,
+    "swimming pool indoor": 341,
+    "swimming pool outdoor": 342,
+    "synagogue indoor": 343,
+    "synagogue outdoor": 344,
+    "television studio": 345,
+    "temple east asia": 346,
+    "temple south asia": 347,
+    "tennis court indoor": 348,
+    "tennis court outdoor": 349,
+    "tent outdoor": 350,
+    "theater indoor procenium": 351,
+    "theater indoor seats": 352,
+    "thriftshop": 353,
+    "throne room": 354,
+    "ticket booth": 355,
+    "toll plaza": 356,
+    "topiary garden": 357,
+    "tower": 358,
+    "toyshop": 359,
+    "track outdoor": 360,
+    "train railway": 361,
+    "train station platform": 362,
+    "tree farm": 363,
+    "tree house": 364,
+    "trench": 365,
+    "underwater coral reef": 366,
+    "utility room": 367,
+    "valley": 368,
+    "van interior": 369,
+    "vegetable garden": 370,
+    "veranda": 371,
+    "veterinarians office": 372,
+    "viaduct": 373,
+    "videostore": 374,
+    "village": 375,
+    "vineyard": 376,
+    "volcano": 377,
+    "volleyball court indoor": 378,
+    "volleyball court outdoor": 379,
+    "waiting room": 380,
+    "warehouse indoor": 381,
+    "water tower": 382,
+    "waterfall block": 383,
+    "waterfall fan": 384,
+    "waterfall plunge": 385,
+    "watering hole": 386,
+    "wave": 387,
+    "wet bar": 388,
+    "wheat field": 389,
+    "wind farm": 390,
+    "windmill": 391,
+    "wine cellar barrel storage": 392,
+    "wine cellar bottle storage": 393,
+    "wrestling ring indoor": 394,
+    "yard": 395,
+    "youth hostel": 396
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet18-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-svhn-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/README.md b/resnet18-svhn-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..bdcdf40a2c4378ff1b8e69f8b6ca88dccf509128
--- /dev/null
+++ b/resnet18-svhn-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,80 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset svhn.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: svhn
+    pretrained: true
+test_datasets: null
+train_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: train
+type: transformers
+val_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: test
+```
+
diff --git a/resnet18-svhn-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/config.json b/resnet18-svhn-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..018e7d4d1ef4a7995d309411e18d7bc5d8d5f4a9
--- /dev/null
+++ b/resnet18-svhn-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-svhn-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet18-svhn-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-svhn-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-svhn-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/README.md b/resnet18-svhn-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..78ce727903477364e2604c88e790b4798c21d61f
--- /dev/null
+++ b/resnet18-svhn-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,80 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset svhn.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: svhn
+    pretrained: true
+test_datasets: null
+train_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: train
+type: transformers
+val_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: test
+```
+
diff --git a/resnet18-svhn-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/config.json b/resnet18-svhn-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..018e7d4d1ef4a7995d309411e18d7bc5d8d5f4a9
--- /dev/null
+++ b/resnet18-svhn-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-svhn-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet18-svhn-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-svhn-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-svhn-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/README.md b/resnet18-svhn-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..189b827d117502d04fcb69e200cec9f3de76d84d
--- /dev/null
+++ b/resnet18-svhn-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,80 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset svhn.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: svhn
+    pretrained: true
+test_datasets: null
+train_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: train
+type: transformers
+val_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: test
+```
+
diff --git a/resnet18-svhn-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/config.json b/resnet18-svhn-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..018e7d4d1ef4a7995d309411e18d7bc5d8d5f4a9
--- /dev/null
+++ b/resnet18-svhn-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-svhn-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet18-svhn-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-svhn-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet18-svhn-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/README.md b/resnet18-svhn-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..43405458698bcea7284298cab4b37c641d1af0d5
--- /dev/null
+++ b/resnet18-svhn-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,80 @@
+---
+base_model: microsoft/resnet-18
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset svhn.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-18
+    dataset_name: svhn
+    pretrained: true
+test_datasets: null
+train_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: train
+type: transformers
+val_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: test
+```
+
diff --git a/resnet18-svhn-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/config.json b/resnet18-svhn-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..018e7d4d1ef4a7995d309411e18d7bc5d8d5f4a9
--- /dev/null
+++ b/resnet18-svhn-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet18-svhn-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet18-svhn-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet18-svhn-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-cifar10-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/README.md b/resnet50-cifar10-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..6bc59cccc2f0fd0283c5d607540750402854914a
--- /dev/null
+++ b/resnet50-cifar10-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: cifar10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: train
+type: transformers
+val_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: test
+```
+
diff --git a/resnet50-cifar10-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/config.json b/resnet50-cifar10-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..3c885e0d0eac58ee224a40f544b024413974088f
--- /dev/null
+++ b/resnet50-cifar10-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "automobile",
+    "2": "bird",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "frog",
+    "7": "horse",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "automobile": 1,
+    "bird": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "frog": 6,
+    "horse": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-cifar10-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet50-cifar10-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-cifar10-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-cifar10-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/README.md b/resnet50-cifar10-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..1ff9b42153446695881aa454c47f61b2f1841aed
--- /dev/null
+++ b/resnet50-cifar10-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: cifar10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: train
+type: transformers
+val_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: test
+```
+
diff --git a/resnet50-cifar10-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/config.json b/resnet50-cifar10-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..3c885e0d0eac58ee224a40f544b024413974088f
--- /dev/null
+++ b/resnet50-cifar10-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "automobile",
+    "2": "bird",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "frog",
+    "7": "horse",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "automobile": 1,
+    "bird": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "frog": 6,
+    "horse": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-cifar10-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet50-cifar10-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-cifar10-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-cifar10-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/README.md b/resnet50-cifar10-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e98ff4fba8c1e58555a6a05d5356de93859621ee
--- /dev/null
+++ b/resnet50-cifar10-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: cifar10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: train
+type: transformers
+val_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: test
+```
+
diff --git a/resnet50-cifar10-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/config.json b/resnet50-cifar10-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..3c885e0d0eac58ee224a40f544b024413974088f
--- /dev/null
+++ b/resnet50-cifar10-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "automobile",
+    "2": "bird",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "frog",
+    "7": "horse",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "automobile": 1,
+    "bird": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "frog": 6,
+    "horse": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-cifar10-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet50-cifar10-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-cifar10-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-cifar10-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/README.md b/resnet50-cifar10-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..305e6dadd068ce46d65b0a4cc929c96d6105d8f1
--- /dev/null
+++ b/resnet50-cifar10-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: cifar10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: train
+type: transformers
+val_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: test
+```
+
diff --git a/resnet50-cifar10-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/config.json b/resnet50-cifar10-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..3c885e0d0eac58ee224a40f544b024413974088f
--- /dev/null
+++ b/resnet50-cifar10-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "automobile",
+    "2": "bird",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "frog",
+    "7": "horse",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "automobile": 1,
+    "bird": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "frog": 6,
+    "horse": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-cifar10-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet50-cifar10-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-cifar10-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-cifar10-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/README.md b/resnet50-cifar10-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..c8585d60f4020b9f4136b21748b0bc4e07798a8a
--- /dev/null
+++ b/resnet50-cifar10-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: cifar10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: train
+type: transformers
+val_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: test
+```
+
diff --git a/resnet50-cifar10-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/config.json b/resnet50-cifar10-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..3c885e0d0eac58ee224a40f544b024413974088f
--- /dev/null
+++ b/resnet50-cifar10-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "automobile",
+    "2": "bird",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "frog",
+    "7": "horse",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "automobile": 1,
+    "bird": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "frog": 6,
+    "horse": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-cifar10-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet50-cifar10-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-cifar10-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-cifar10-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/README.md b/resnet50-cifar10-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..efc79f0fc70bbc4fd82a77666ef14be7a5eecea0
--- /dev/null
+++ b/resnet50-cifar10-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: cifar10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: train
+type: transformers
+val_datasets:
+  cifar10:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar10
+    split: test
+```
+
diff --git a/resnet50-cifar10-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/config.json b/resnet50-cifar10-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..3c885e0d0eac58ee224a40f544b024413974088f
--- /dev/null
+++ b/resnet50-cifar10-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "automobile",
+    "2": "bird",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "frog",
+    "7": "horse",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "automobile": 1,
+    "bird": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "frog": 6,
+    "horse": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-cifar10-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet50-cifar10-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-cifar10-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-cifar100-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/README.md b/resnet50-cifar100-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..0311a90a558ac029f8282297668ea90a597f7331
--- /dev/null
+++ b/resnet50-cifar100-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar100.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: cifar100
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: train
+type: transformers
+val_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: test
+```
+
diff --git a/resnet50-cifar100-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/config.json b/resnet50-cifar100-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..4eba7ae9631d2b0e864ded80157f76e37582afd4
--- /dev/null
+++ b/resnet50-cifar100-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,243 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "apple",
+    "1": "aquarium_fish",
+    "2": "baby",
+    "3": "bear",
+    "4": "beaver",
+    "5": "bed",
+    "6": "bee",
+    "7": "beetle",
+    "8": "bicycle",
+    "9": "bottle",
+    "10": "bowl",
+    "11": "boy",
+    "12": "bridge",
+    "13": "bus",
+    "14": "butterfly",
+    "15": "camel",
+    "16": "can",
+    "17": "castle",
+    "18": "caterpillar",
+    "19": "cattle",
+    "20": "chair",
+    "21": "chimpanzee",
+    "22": "clock",
+    "23": "cloud",
+    "24": "cockroach",
+    "25": "couch",
+    "26": "cra",
+    "27": "crocodile",
+    "28": "cup",
+    "29": "dinosaur",
+    "30": "dolphin",
+    "31": "elephant",
+    "32": "flatfish",
+    "33": "forest",
+    "34": "fox",
+    "35": "girl",
+    "36": "hamster",
+    "37": "house",
+    "38": "kangaroo",
+    "39": "keyboard",
+    "40": "lamp",
+    "41": "lawn_mower",
+    "42": "leopard",
+    "43": "lion",
+    "44": "lizard",
+    "45": "lobster",
+    "46": "man",
+    "47": "maple_tree",
+    "48": "motorcycle",
+    "49": "mountain",
+    "50": "mouse",
+    "51": "mushroom",
+    "52": "oak_tree",
+    "53": "orange",
+    "54": "orchid",
+    "55": "otter",
+    "56": "palm_tree",
+    "57": "pear",
+    "58": "pickup_truck",
+    "59": "pine_tree",
+    "60": "plain",
+    "61": "plate",
+    "62": "poppy",
+    "63": "porcupine",
+    "64": "possum",
+    "65": "rabbit",
+    "66": "raccoon",
+    "67": "ray",
+    "68": "road",
+    "69": "rocket",
+    "70": "rose",
+    "71": "sea",
+    "72": "seal",
+    "73": "shark",
+    "74": "shrew",
+    "75": "skunk",
+    "76": "skyscraper",
+    "77": "snail",
+    "78": "snake",
+    "79": "spider",
+    "80": "squirrel",
+    "81": "streetcar",
+    "82": "sunflower",
+    "83": "sweet_pepper",
+    "84": "table",
+    "85": "tank",
+    "86": "telephone",
+    "87": "television",
+    "88": "tiger",
+    "89": "tractor",
+    "90": "train",
+    "91": "trout",
+    "92": "tulip",
+    "93": "turtle",
+    "94": "wardrobe",
+    "95": "whale",
+    "96": "willow_tree",
+    "97": "wolf",
+    "98": "woman",
+    "99": "worm"
+  },
+  "label2id": {
+    "apple": 0,
+    "aquarium_fish": 1,
+    "baby": 2,
+    "bear": 3,
+    "beaver": 4,
+    "bed": 5,
+    "bee": 6,
+    "beetle": 7,
+    "bicycle": 8,
+    "bottle": 9,
+    "bowl": 10,
+    "boy": 11,
+    "bridge": 12,
+    "bus": 13,
+    "butterfly": 14,
+    "camel": 15,
+    "can": 16,
+    "castle": 17,
+    "caterpillar": 18,
+    "cattle": 19,
+    "chair": 20,
+    "chimpanzee": 21,
+    "clock": 22,
+    "cloud": 23,
+    "cockroach": 24,
+    "couch": 25,
+    "cra": 26,
+    "crocodile": 27,
+    "cup": 28,
+    "dinosaur": 29,
+    "dolphin": 30,
+    "elephant": 31,
+    "flatfish": 32,
+    "forest": 33,
+    "fox": 34,
+    "girl": 35,
+    "hamster": 36,
+    "house": 37,
+    "kangaroo": 38,
+    "keyboard": 39,
+    "lamp": 40,
+    "lawn_mower": 41,
+    "leopard": 42,
+    "lion": 43,
+    "lizard": 44,
+    "lobster": 45,
+    "man": 46,
+    "maple_tree": 47,
+    "motorcycle": 48,
+    "mountain": 49,
+    "mouse": 50,
+    "mushroom": 51,
+    "oak_tree": 52,
+    "orange": 53,
+    "orchid": 54,
+    "otter": 55,
+    "palm_tree": 56,
+    "pear": 57,
+    "pickup_truck": 58,
+    "pine_tree": 59,
+    "plain": 60,
+    "plate": 61,
+    "poppy": 62,
+    "porcupine": 63,
+    "possum": 64,
+    "rabbit": 65,
+    "raccoon": 66,
+    "ray": 67,
+    "road": 68,
+    "rocket": 69,
+    "rose": 70,
+    "sea": 71,
+    "seal": 72,
+    "shark": 73,
+    "shrew": 74,
+    "skunk": 75,
+    "skyscraper": 76,
+    "snail": 77,
+    "snake": 78,
+    "spider": 79,
+    "squirrel": 80,
+    "streetcar": 81,
+    "sunflower": 82,
+    "sweet_pepper": 83,
+    "table": 84,
+    "tank": 85,
+    "telephone": 86,
+    "television": 87,
+    "tiger": 88,
+    "tractor": 89,
+    "train": 90,
+    "trout": 91,
+    "tulip": 92,
+    "turtle": 93,
+    "wardrobe": 94,
+    "whale": 95,
+    "willow_tree": 96,
+    "wolf": 97,
+    "woman": 98,
+    "worm": 99
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-cifar100-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet50-cifar100-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-cifar100-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/README.md b/resnet50-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..2d5e91fced2de21bb38d544bb637911312dc6cf9
--- /dev/null
+++ b/resnet50-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar100.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: cifar100
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: train
+type: transformers
+val_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: test
+```
+
diff --git a/resnet50-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/config.json b/resnet50-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..4eba7ae9631d2b0e864ded80157f76e37582afd4
--- /dev/null
+++ b/resnet50-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,243 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "apple",
+    "1": "aquarium_fish",
+    "2": "baby",
+    "3": "bear",
+    "4": "beaver",
+    "5": "bed",
+    "6": "bee",
+    "7": "beetle",
+    "8": "bicycle",
+    "9": "bottle",
+    "10": "bowl",
+    "11": "boy",
+    "12": "bridge",
+    "13": "bus",
+    "14": "butterfly",
+    "15": "camel",
+    "16": "can",
+    "17": "castle",
+    "18": "caterpillar",
+    "19": "cattle",
+    "20": "chair",
+    "21": "chimpanzee",
+    "22": "clock",
+    "23": "cloud",
+    "24": "cockroach",
+    "25": "couch",
+    "26": "cra",
+    "27": "crocodile",
+    "28": "cup",
+    "29": "dinosaur",
+    "30": "dolphin",
+    "31": "elephant",
+    "32": "flatfish",
+    "33": "forest",
+    "34": "fox",
+    "35": "girl",
+    "36": "hamster",
+    "37": "house",
+    "38": "kangaroo",
+    "39": "keyboard",
+    "40": "lamp",
+    "41": "lawn_mower",
+    "42": "leopard",
+    "43": "lion",
+    "44": "lizard",
+    "45": "lobster",
+    "46": "man",
+    "47": "maple_tree",
+    "48": "motorcycle",
+    "49": "mountain",
+    "50": "mouse",
+    "51": "mushroom",
+    "52": "oak_tree",
+    "53": "orange",
+    "54": "orchid",
+    "55": "otter",
+    "56": "palm_tree",
+    "57": "pear",
+    "58": "pickup_truck",
+    "59": "pine_tree",
+    "60": "plain",
+    "61": "plate",
+    "62": "poppy",
+    "63": "porcupine",
+    "64": "possum",
+    "65": "rabbit",
+    "66": "raccoon",
+    "67": "ray",
+    "68": "road",
+    "69": "rocket",
+    "70": "rose",
+    "71": "sea",
+    "72": "seal",
+    "73": "shark",
+    "74": "shrew",
+    "75": "skunk",
+    "76": "skyscraper",
+    "77": "snail",
+    "78": "snake",
+    "79": "spider",
+    "80": "squirrel",
+    "81": "streetcar",
+    "82": "sunflower",
+    "83": "sweet_pepper",
+    "84": "table",
+    "85": "tank",
+    "86": "telephone",
+    "87": "television",
+    "88": "tiger",
+    "89": "tractor",
+    "90": "train",
+    "91": "trout",
+    "92": "tulip",
+    "93": "turtle",
+    "94": "wardrobe",
+    "95": "whale",
+    "96": "willow_tree",
+    "97": "wolf",
+    "98": "woman",
+    "99": "worm"
+  },
+  "label2id": {
+    "apple": 0,
+    "aquarium_fish": 1,
+    "baby": 2,
+    "bear": 3,
+    "beaver": 4,
+    "bed": 5,
+    "bee": 6,
+    "beetle": 7,
+    "bicycle": 8,
+    "bottle": 9,
+    "bowl": 10,
+    "boy": 11,
+    "bridge": 12,
+    "bus": 13,
+    "butterfly": 14,
+    "camel": 15,
+    "can": 16,
+    "castle": 17,
+    "caterpillar": 18,
+    "cattle": 19,
+    "chair": 20,
+    "chimpanzee": 21,
+    "clock": 22,
+    "cloud": 23,
+    "cockroach": 24,
+    "couch": 25,
+    "cra": 26,
+    "crocodile": 27,
+    "cup": 28,
+    "dinosaur": 29,
+    "dolphin": 30,
+    "elephant": 31,
+    "flatfish": 32,
+    "forest": 33,
+    "fox": 34,
+    "girl": 35,
+    "hamster": 36,
+    "house": 37,
+    "kangaroo": 38,
+    "keyboard": 39,
+    "lamp": 40,
+    "lawn_mower": 41,
+    "leopard": 42,
+    "lion": 43,
+    "lizard": 44,
+    "lobster": 45,
+    "man": 46,
+    "maple_tree": 47,
+    "motorcycle": 48,
+    "mountain": 49,
+    "mouse": 50,
+    "mushroom": 51,
+    "oak_tree": 52,
+    "orange": 53,
+    "orchid": 54,
+    "otter": 55,
+    "palm_tree": 56,
+    "pear": 57,
+    "pickup_truck": 58,
+    "pine_tree": 59,
+    "plain": 60,
+    "plate": 61,
+    "poppy": 62,
+    "porcupine": 63,
+    "possum": 64,
+    "rabbit": 65,
+    "raccoon": 66,
+    "ray": 67,
+    "road": 68,
+    "rocket": 69,
+    "rose": 70,
+    "sea": 71,
+    "seal": 72,
+    "shark": 73,
+    "shrew": 74,
+    "skunk": 75,
+    "skyscraper": 76,
+    "snail": 77,
+    "snake": 78,
+    "spider": 79,
+    "squirrel": 80,
+    "streetcar": 81,
+    "sunflower": 82,
+    "sweet_pepper": 83,
+    "table": 84,
+    "tank": 85,
+    "telephone": 86,
+    "television": 87,
+    "tiger": 88,
+    "tractor": 89,
+    "train": 90,
+    "trout": 91,
+    "tulip": 92,
+    "turtle": 93,
+    "wardrobe": 94,
+    "whale": 95,
+    "willow_tree": 96,
+    "wolf": 97,
+    "woman": 98,
+    "worm": 99
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet50-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/README.md b/resnet50-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..2d5e91fced2de21bb38d544bb637911312dc6cf9
--- /dev/null
+++ b/resnet50-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar100.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: cifar100
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: train
+type: transformers
+val_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: test
+```
+
diff --git a/resnet50-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/config.json b/resnet50-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..4eba7ae9631d2b0e864ded80157f76e37582afd4
--- /dev/null
+++ b/resnet50-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,243 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "apple",
+    "1": "aquarium_fish",
+    "2": "baby",
+    "3": "bear",
+    "4": "beaver",
+    "5": "bed",
+    "6": "bee",
+    "7": "beetle",
+    "8": "bicycle",
+    "9": "bottle",
+    "10": "bowl",
+    "11": "boy",
+    "12": "bridge",
+    "13": "bus",
+    "14": "butterfly",
+    "15": "camel",
+    "16": "can",
+    "17": "castle",
+    "18": "caterpillar",
+    "19": "cattle",
+    "20": "chair",
+    "21": "chimpanzee",
+    "22": "clock",
+    "23": "cloud",
+    "24": "cockroach",
+    "25": "couch",
+    "26": "cra",
+    "27": "crocodile",
+    "28": "cup",
+    "29": "dinosaur",
+    "30": "dolphin",
+    "31": "elephant",
+    "32": "flatfish",
+    "33": "forest",
+    "34": "fox",
+    "35": "girl",
+    "36": "hamster",
+    "37": "house",
+    "38": "kangaroo",
+    "39": "keyboard",
+    "40": "lamp",
+    "41": "lawn_mower",
+    "42": "leopard",
+    "43": "lion",
+    "44": "lizard",
+    "45": "lobster",
+    "46": "man",
+    "47": "maple_tree",
+    "48": "motorcycle",
+    "49": "mountain",
+    "50": "mouse",
+    "51": "mushroom",
+    "52": "oak_tree",
+    "53": "orange",
+    "54": "orchid",
+    "55": "otter",
+    "56": "palm_tree",
+    "57": "pear",
+    "58": "pickup_truck",
+    "59": "pine_tree",
+    "60": "plain",
+    "61": "plate",
+    "62": "poppy",
+    "63": "porcupine",
+    "64": "possum",
+    "65": "rabbit",
+    "66": "raccoon",
+    "67": "ray",
+    "68": "road",
+    "69": "rocket",
+    "70": "rose",
+    "71": "sea",
+    "72": "seal",
+    "73": "shark",
+    "74": "shrew",
+    "75": "skunk",
+    "76": "skyscraper",
+    "77": "snail",
+    "78": "snake",
+    "79": "spider",
+    "80": "squirrel",
+    "81": "streetcar",
+    "82": "sunflower",
+    "83": "sweet_pepper",
+    "84": "table",
+    "85": "tank",
+    "86": "telephone",
+    "87": "television",
+    "88": "tiger",
+    "89": "tractor",
+    "90": "train",
+    "91": "trout",
+    "92": "tulip",
+    "93": "turtle",
+    "94": "wardrobe",
+    "95": "whale",
+    "96": "willow_tree",
+    "97": "wolf",
+    "98": "woman",
+    "99": "worm"
+  },
+  "label2id": {
+    "apple": 0,
+    "aquarium_fish": 1,
+    "baby": 2,
+    "bear": 3,
+    "beaver": 4,
+    "bed": 5,
+    "bee": 6,
+    "beetle": 7,
+    "bicycle": 8,
+    "bottle": 9,
+    "bowl": 10,
+    "boy": 11,
+    "bridge": 12,
+    "bus": 13,
+    "butterfly": 14,
+    "camel": 15,
+    "can": 16,
+    "castle": 17,
+    "caterpillar": 18,
+    "cattle": 19,
+    "chair": 20,
+    "chimpanzee": 21,
+    "clock": 22,
+    "cloud": 23,
+    "cockroach": 24,
+    "couch": 25,
+    "cra": 26,
+    "crocodile": 27,
+    "cup": 28,
+    "dinosaur": 29,
+    "dolphin": 30,
+    "elephant": 31,
+    "flatfish": 32,
+    "forest": 33,
+    "fox": 34,
+    "girl": 35,
+    "hamster": 36,
+    "house": 37,
+    "kangaroo": 38,
+    "keyboard": 39,
+    "lamp": 40,
+    "lawn_mower": 41,
+    "leopard": 42,
+    "lion": 43,
+    "lizard": 44,
+    "lobster": 45,
+    "man": 46,
+    "maple_tree": 47,
+    "motorcycle": 48,
+    "mountain": 49,
+    "mouse": 50,
+    "mushroom": 51,
+    "oak_tree": 52,
+    "orange": 53,
+    "orchid": 54,
+    "otter": 55,
+    "palm_tree": 56,
+    "pear": 57,
+    "pickup_truck": 58,
+    "pine_tree": 59,
+    "plain": 60,
+    "plate": 61,
+    "poppy": 62,
+    "porcupine": 63,
+    "possum": 64,
+    "rabbit": 65,
+    "raccoon": 66,
+    "ray": 67,
+    "road": 68,
+    "rocket": 69,
+    "rose": 70,
+    "sea": 71,
+    "seal": 72,
+    "shark": 73,
+    "shrew": 74,
+    "skunk": 75,
+    "skyscraper": 76,
+    "snail": 77,
+    "snake": 78,
+    "spider": 79,
+    "squirrel": 80,
+    "streetcar": 81,
+    "sunflower": 82,
+    "sweet_pepper": 83,
+    "table": 84,
+    "tank": 85,
+    "telephone": 86,
+    "television": 87,
+    "tiger": 88,
+    "tractor": 89,
+    "train": 90,
+    "trout": 91,
+    "tulip": 92,
+    "turtle": 93,
+    "wardrobe": 94,
+    "whale": 95,
+    "willow_tree": 96,
+    "wolf": 97,
+    "woman": 98,
+    "worm": 99
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet50-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-cifar100-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/README.md b/resnet50-cifar100-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..c6a2d591686c65f3d5da4e052fa0eb5db1cb9baa
--- /dev/null
+++ b/resnet50-cifar100-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset cifar100.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: cifar100
+    pretrained: true
+test_datasets: null
+train_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: train
+type: transformers
+val_datasets:
+  cifar100:
+    _target_: datasets.load_dataset
+    path: tanganke/cifar100
+    split: test
+```
+
diff --git a/resnet50-cifar100-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/config.json b/resnet50-cifar100-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..4eba7ae9631d2b0e864ded80157f76e37582afd4
--- /dev/null
+++ b/resnet50-cifar100-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/config.json
@@ -0,0 +1,243 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "apple",
+    "1": "aquarium_fish",
+    "2": "baby",
+    "3": "bear",
+    "4": "beaver",
+    "5": "bed",
+    "6": "bee",
+    "7": "beetle",
+    "8": "bicycle",
+    "9": "bottle",
+    "10": "bowl",
+    "11": "boy",
+    "12": "bridge",
+    "13": "bus",
+    "14": "butterfly",
+    "15": "camel",
+    "16": "can",
+    "17": "castle",
+    "18": "caterpillar",
+    "19": "cattle",
+    "20": "chair",
+    "21": "chimpanzee",
+    "22": "clock",
+    "23": "cloud",
+    "24": "cockroach",
+    "25": "couch",
+    "26": "cra",
+    "27": "crocodile",
+    "28": "cup",
+    "29": "dinosaur",
+    "30": "dolphin",
+    "31": "elephant",
+    "32": "flatfish",
+    "33": "forest",
+    "34": "fox",
+    "35": "girl",
+    "36": "hamster",
+    "37": "house",
+    "38": "kangaroo",
+    "39": "keyboard",
+    "40": "lamp",
+    "41": "lawn_mower",
+    "42": "leopard",
+    "43": "lion",
+    "44": "lizard",
+    "45": "lobster",
+    "46": "man",
+    "47": "maple_tree",
+    "48": "motorcycle",
+    "49": "mountain",
+    "50": "mouse",
+    "51": "mushroom",
+    "52": "oak_tree",
+    "53": "orange",
+    "54": "orchid",
+    "55": "otter",
+    "56": "palm_tree",
+    "57": "pear",
+    "58": "pickup_truck",
+    "59": "pine_tree",
+    "60": "plain",
+    "61": "plate",
+    "62": "poppy",
+    "63": "porcupine",
+    "64": "possum",
+    "65": "rabbit",
+    "66": "raccoon",
+    "67": "ray",
+    "68": "road",
+    "69": "rocket",
+    "70": "rose",
+    "71": "sea",
+    "72": "seal",
+    "73": "shark",
+    "74": "shrew",
+    "75": "skunk",
+    "76": "skyscraper",
+    "77": "snail",
+    "78": "snake",
+    "79": "spider",
+    "80": "squirrel",
+    "81": "streetcar",
+    "82": "sunflower",
+    "83": "sweet_pepper",
+    "84": "table",
+    "85": "tank",
+    "86": "telephone",
+    "87": "television",
+    "88": "tiger",
+    "89": "tractor",
+    "90": "train",
+    "91": "trout",
+    "92": "tulip",
+    "93": "turtle",
+    "94": "wardrobe",
+    "95": "whale",
+    "96": "willow_tree",
+    "97": "wolf",
+    "98": "woman",
+    "99": "worm"
+  },
+  "label2id": {
+    "apple": 0,
+    "aquarium_fish": 1,
+    "baby": 2,
+    "bear": 3,
+    "beaver": 4,
+    "bed": 5,
+    "bee": 6,
+    "beetle": 7,
+    "bicycle": 8,
+    "bottle": 9,
+    "bowl": 10,
+    "boy": 11,
+    "bridge": 12,
+    "bus": 13,
+    "butterfly": 14,
+    "camel": 15,
+    "can": 16,
+    "castle": 17,
+    "caterpillar": 18,
+    "cattle": 19,
+    "chair": 20,
+    "chimpanzee": 21,
+    "clock": 22,
+    "cloud": 23,
+    "cockroach": 24,
+    "couch": 25,
+    "cra": 26,
+    "crocodile": 27,
+    "cup": 28,
+    "dinosaur": 29,
+    "dolphin": 30,
+    "elephant": 31,
+    "flatfish": 32,
+    "forest": 33,
+    "fox": 34,
+    "girl": 35,
+    "hamster": 36,
+    "house": 37,
+    "kangaroo": 38,
+    "keyboard": 39,
+    "lamp": 40,
+    "lawn_mower": 41,
+    "leopard": 42,
+    "lion": 43,
+    "lizard": 44,
+    "lobster": 45,
+    "man": 46,
+    "maple_tree": 47,
+    "motorcycle": 48,
+    "mountain": 49,
+    "mouse": 50,
+    "mushroom": 51,
+    "oak_tree": 52,
+    "orange": 53,
+    "orchid": 54,
+    "otter": 55,
+    "palm_tree": 56,
+    "pear": 57,
+    "pickup_truck": 58,
+    "pine_tree": 59,
+    "plain": 60,
+    "plate": 61,
+    "poppy": 62,
+    "porcupine": 63,
+    "possum": 64,
+    "rabbit": 65,
+    "raccoon": 66,
+    "ray": 67,
+    "road": 68,
+    "rocket": 69,
+    "rose": 70,
+    "sea": 71,
+    "seal": 72,
+    "shark": 73,
+    "shrew": 74,
+    "skunk": 75,
+    "skyscraper": 76,
+    "snail": 77,
+    "snake": 78,
+    "spider": 79,
+    "squirrel": 80,
+    "streetcar": 81,
+    "sunflower": 82,
+    "sweet_pepper": 83,
+    "table": 84,
+    "tank": 85,
+    "telephone": 86,
+    "television": 87,
+    "tiger": 88,
+    "tractor": 89,
+    "train": 90,
+    "trout": 91,
+    "tulip": 92,
+    "turtle": 93,
+    "wardrobe": 94,
+    "whale": 95,
+    "willow_tree": 96,
+    "wolf": 97,
+    "woman": 98,
+    "worm": 99
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-cifar100-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet50-cifar100-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-cifar100-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-dtd-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/README.md b/resnet50-dtd-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..38daa8da4d5852dc146ab68a5ee2e9faf911f3ae
--- /dev/null
+++ b/resnet50-dtd-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset dtd.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: dtd
+    pretrained: true
+test_datasets: null
+train_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: train
+type: transformers
+val_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: test
+```
+
diff --git a/resnet50-dtd-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/config.json b/resnet50-dtd-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..9be9d43cf554cd4001bc241de10a3998fe29da7d
--- /dev/null
+++ b/resnet50-dtd-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,137 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "banded",
+    "1": "blotchy",
+    "2": "braided",
+    "3": "bubbly",
+    "4": "bumpy",
+    "5": "chequered",
+    "6": "cobwebbed",
+    "7": "cracked",
+    "8": "crosshatched",
+    "9": "crystalline",
+    "10": "dotted",
+    "11": "fibrous",
+    "12": "flecked",
+    "13": "freckled",
+    "14": "frilly",
+    "15": "gauzy",
+    "16": "grid",
+    "17": "grooved",
+    "18": "honeycombed",
+    "19": "interlaced",
+    "20": "knitted",
+    "21": "lacelike",
+    "22": "lined",
+    "23": "marbled",
+    "24": "matted",
+    "25": "meshed",
+    "26": "paisley",
+    "27": "perforated",
+    "28": "pitted",
+    "29": "pleated",
+    "30": "polka-dotted",
+    "31": "porous",
+    "32": "potholed",
+    "33": "scaly",
+    "34": "smeared",
+    "35": "spiralled",
+    "36": "sprinkled",
+    "37": "stained",
+    "38": "stratified",
+    "39": "striped",
+    "40": "studded",
+    "41": "swirly",
+    "42": "veined",
+    "43": "waffled",
+    "44": "woven",
+    "45": "wrinkled",
+    "46": "zigzagged"
+  },
+  "label2id": {
+    "banded": 0,
+    "blotchy": 1,
+    "braided": 2,
+    "bubbly": 3,
+    "bumpy": 4,
+    "chequered": 5,
+    "cobwebbed": 6,
+    "cracked": 7,
+    "crosshatched": 8,
+    "crystalline": 9,
+    "dotted": 10,
+    "fibrous": 11,
+    "flecked": 12,
+    "freckled": 13,
+    "frilly": 14,
+    "gauzy": 15,
+    "grid": 16,
+    "grooved": 17,
+    "honeycombed": 18,
+    "interlaced": 19,
+    "knitted": 20,
+    "lacelike": 21,
+    "lined": 22,
+    "marbled": 23,
+    "matted": 24,
+    "meshed": 25,
+    "paisley": 26,
+    "perforated": 27,
+    "pitted": 28,
+    "pleated": 29,
+    "polka-dotted": 30,
+    "porous": 31,
+    "potholed": 32,
+    "scaly": 33,
+    "smeared": 34,
+    "spiralled": 35,
+    "sprinkled": 36,
+    "stained": 37,
+    "stratified": 38,
+    "striped": 39,
+    "studded": 40,
+    "swirly": 41,
+    "veined": 42,
+    "waffled": 43,
+    "woven": 44,
+    "wrinkled": 45,
+    "zigzagged": 46
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-dtd-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet50-dtd-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-dtd-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-dtd-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/README.md b/resnet50-dtd-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..a0c677850fe621e673fb23a541a252f9c46ec821
--- /dev/null
+++ b/resnet50-dtd-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset dtd.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: dtd
+    pretrained: true
+test_datasets: null
+train_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: train
+type: transformers
+val_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: test
+```
+
diff --git a/resnet50-dtd-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/config.json b/resnet50-dtd-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..9be9d43cf554cd4001bc241de10a3998fe29da7d
--- /dev/null
+++ b/resnet50-dtd-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,137 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "banded",
+    "1": "blotchy",
+    "2": "braided",
+    "3": "bubbly",
+    "4": "bumpy",
+    "5": "chequered",
+    "6": "cobwebbed",
+    "7": "cracked",
+    "8": "crosshatched",
+    "9": "crystalline",
+    "10": "dotted",
+    "11": "fibrous",
+    "12": "flecked",
+    "13": "freckled",
+    "14": "frilly",
+    "15": "gauzy",
+    "16": "grid",
+    "17": "grooved",
+    "18": "honeycombed",
+    "19": "interlaced",
+    "20": "knitted",
+    "21": "lacelike",
+    "22": "lined",
+    "23": "marbled",
+    "24": "matted",
+    "25": "meshed",
+    "26": "paisley",
+    "27": "perforated",
+    "28": "pitted",
+    "29": "pleated",
+    "30": "polka-dotted",
+    "31": "porous",
+    "32": "potholed",
+    "33": "scaly",
+    "34": "smeared",
+    "35": "spiralled",
+    "36": "sprinkled",
+    "37": "stained",
+    "38": "stratified",
+    "39": "striped",
+    "40": "studded",
+    "41": "swirly",
+    "42": "veined",
+    "43": "waffled",
+    "44": "woven",
+    "45": "wrinkled",
+    "46": "zigzagged"
+  },
+  "label2id": {
+    "banded": 0,
+    "blotchy": 1,
+    "braided": 2,
+    "bubbly": 3,
+    "bumpy": 4,
+    "chequered": 5,
+    "cobwebbed": 6,
+    "cracked": 7,
+    "crosshatched": 8,
+    "crystalline": 9,
+    "dotted": 10,
+    "fibrous": 11,
+    "flecked": 12,
+    "freckled": 13,
+    "frilly": 14,
+    "gauzy": 15,
+    "grid": 16,
+    "grooved": 17,
+    "honeycombed": 18,
+    "interlaced": 19,
+    "knitted": 20,
+    "lacelike": 21,
+    "lined": 22,
+    "marbled": 23,
+    "matted": 24,
+    "meshed": 25,
+    "paisley": 26,
+    "perforated": 27,
+    "pitted": 28,
+    "pleated": 29,
+    "polka-dotted": 30,
+    "porous": 31,
+    "potholed": 32,
+    "scaly": 33,
+    "smeared": 34,
+    "spiralled": 35,
+    "sprinkled": 36,
+    "stained": 37,
+    "stratified": 38,
+    "striped": 39,
+    "studded": 40,
+    "swirly": 41,
+    "veined": 42,
+    "waffled": 43,
+    "woven": 44,
+    "wrinkled": 45,
+    "zigzagged": 46
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-dtd-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet50-dtd-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-dtd-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-dtd-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/README.md b/resnet50-dtd-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..85a75292c420cec6e4f2561a41a7c650572d012f
--- /dev/null
+++ b/resnet50-dtd-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset dtd.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: dtd
+    pretrained: true
+test_datasets: null
+train_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: train
+type: transformers
+val_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: test
+```
+
diff --git a/resnet50-dtd-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/config.json b/resnet50-dtd-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..9be9d43cf554cd4001bc241de10a3998fe29da7d
--- /dev/null
+++ b/resnet50-dtd-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,137 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "banded",
+    "1": "blotchy",
+    "2": "braided",
+    "3": "bubbly",
+    "4": "bumpy",
+    "5": "chequered",
+    "6": "cobwebbed",
+    "7": "cracked",
+    "8": "crosshatched",
+    "9": "crystalline",
+    "10": "dotted",
+    "11": "fibrous",
+    "12": "flecked",
+    "13": "freckled",
+    "14": "frilly",
+    "15": "gauzy",
+    "16": "grid",
+    "17": "grooved",
+    "18": "honeycombed",
+    "19": "interlaced",
+    "20": "knitted",
+    "21": "lacelike",
+    "22": "lined",
+    "23": "marbled",
+    "24": "matted",
+    "25": "meshed",
+    "26": "paisley",
+    "27": "perforated",
+    "28": "pitted",
+    "29": "pleated",
+    "30": "polka-dotted",
+    "31": "porous",
+    "32": "potholed",
+    "33": "scaly",
+    "34": "smeared",
+    "35": "spiralled",
+    "36": "sprinkled",
+    "37": "stained",
+    "38": "stratified",
+    "39": "striped",
+    "40": "studded",
+    "41": "swirly",
+    "42": "veined",
+    "43": "waffled",
+    "44": "woven",
+    "45": "wrinkled",
+    "46": "zigzagged"
+  },
+  "label2id": {
+    "banded": 0,
+    "blotchy": 1,
+    "braided": 2,
+    "bubbly": 3,
+    "bumpy": 4,
+    "chequered": 5,
+    "cobwebbed": 6,
+    "cracked": 7,
+    "crosshatched": 8,
+    "crystalline": 9,
+    "dotted": 10,
+    "fibrous": 11,
+    "flecked": 12,
+    "freckled": 13,
+    "frilly": 14,
+    "gauzy": 15,
+    "grid": 16,
+    "grooved": 17,
+    "honeycombed": 18,
+    "interlaced": 19,
+    "knitted": 20,
+    "lacelike": 21,
+    "lined": 22,
+    "marbled": 23,
+    "matted": 24,
+    "meshed": 25,
+    "paisley": 26,
+    "perforated": 27,
+    "pitted": 28,
+    "pleated": 29,
+    "polka-dotted": 30,
+    "porous": 31,
+    "potholed": 32,
+    "scaly": 33,
+    "smeared": 34,
+    "spiralled": 35,
+    "sprinkled": 36,
+    "stained": 37,
+    "stratified": 38,
+    "striped": 39,
+    "studded": 40,
+    "swirly": 41,
+    "veined": 42,
+    "waffled": 43,
+    "woven": 44,
+    "wrinkled": 45,
+    "zigzagged": 46
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-dtd-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet50-dtd-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-dtd-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-dtd-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/README.md b/resnet50-dtd-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..8b8521a2a2b989e38acff054a503491adab35391
--- /dev/null
+++ b/resnet50-dtd-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset dtd.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: dtd
+    pretrained: true
+test_datasets: null
+train_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: train
+type: transformers
+val_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: test
+```
+
diff --git a/resnet50-dtd-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/config.json b/resnet50-dtd-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..9be9d43cf554cd4001bc241de10a3998fe29da7d
--- /dev/null
+++ b/resnet50-dtd-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,137 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "banded",
+    "1": "blotchy",
+    "2": "braided",
+    "3": "bubbly",
+    "4": "bumpy",
+    "5": "chequered",
+    "6": "cobwebbed",
+    "7": "cracked",
+    "8": "crosshatched",
+    "9": "crystalline",
+    "10": "dotted",
+    "11": "fibrous",
+    "12": "flecked",
+    "13": "freckled",
+    "14": "frilly",
+    "15": "gauzy",
+    "16": "grid",
+    "17": "grooved",
+    "18": "honeycombed",
+    "19": "interlaced",
+    "20": "knitted",
+    "21": "lacelike",
+    "22": "lined",
+    "23": "marbled",
+    "24": "matted",
+    "25": "meshed",
+    "26": "paisley",
+    "27": "perforated",
+    "28": "pitted",
+    "29": "pleated",
+    "30": "polka-dotted",
+    "31": "porous",
+    "32": "potholed",
+    "33": "scaly",
+    "34": "smeared",
+    "35": "spiralled",
+    "36": "sprinkled",
+    "37": "stained",
+    "38": "stratified",
+    "39": "striped",
+    "40": "studded",
+    "41": "swirly",
+    "42": "veined",
+    "43": "waffled",
+    "44": "woven",
+    "45": "wrinkled",
+    "46": "zigzagged"
+  },
+  "label2id": {
+    "banded": 0,
+    "blotchy": 1,
+    "braided": 2,
+    "bubbly": 3,
+    "bumpy": 4,
+    "chequered": 5,
+    "cobwebbed": 6,
+    "cracked": 7,
+    "crosshatched": 8,
+    "crystalline": 9,
+    "dotted": 10,
+    "fibrous": 11,
+    "flecked": 12,
+    "freckled": 13,
+    "frilly": 14,
+    "gauzy": 15,
+    "grid": 16,
+    "grooved": 17,
+    "honeycombed": 18,
+    "interlaced": 19,
+    "knitted": 20,
+    "lacelike": 21,
+    "lined": 22,
+    "marbled": 23,
+    "matted": 24,
+    "meshed": 25,
+    "paisley": 26,
+    "perforated": 27,
+    "pitted": 28,
+    "pleated": 29,
+    "polka-dotted": 30,
+    "porous": 31,
+    "potholed": 32,
+    "scaly": 33,
+    "smeared": 34,
+    "spiralled": 35,
+    "sprinkled": 36,
+    "stained": 37,
+    "stratified": 38,
+    "striped": 39,
+    "studded": 40,
+    "swirly": 41,
+    "veined": 42,
+    "waffled": 43,
+    "woven": 44,
+    "wrinkled": 45,
+    "zigzagged": 46
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-dtd-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet50-dtd-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-dtd-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-dtd-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/README.md b/resnet50-dtd-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..2d9aa2cc8593737512cf150d0b966f25b8a12dd2
--- /dev/null
+++ b/resnet50-dtd-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset dtd.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: dtd
+    pretrained: true
+test_datasets: null
+train_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: train
+type: transformers
+val_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: test
+```
+
diff --git a/resnet50-dtd-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/config.json b/resnet50-dtd-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..9be9d43cf554cd4001bc241de10a3998fe29da7d
--- /dev/null
+++ b/resnet50-dtd-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,137 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "banded",
+    "1": "blotchy",
+    "2": "braided",
+    "3": "bubbly",
+    "4": "bumpy",
+    "5": "chequered",
+    "6": "cobwebbed",
+    "7": "cracked",
+    "8": "crosshatched",
+    "9": "crystalline",
+    "10": "dotted",
+    "11": "fibrous",
+    "12": "flecked",
+    "13": "freckled",
+    "14": "frilly",
+    "15": "gauzy",
+    "16": "grid",
+    "17": "grooved",
+    "18": "honeycombed",
+    "19": "interlaced",
+    "20": "knitted",
+    "21": "lacelike",
+    "22": "lined",
+    "23": "marbled",
+    "24": "matted",
+    "25": "meshed",
+    "26": "paisley",
+    "27": "perforated",
+    "28": "pitted",
+    "29": "pleated",
+    "30": "polka-dotted",
+    "31": "porous",
+    "32": "potholed",
+    "33": "scaly",
+    "34": "smeared",
+    "35": "spiralled",
+    "36": "sprinkled",
+    "37": "stained",
+    "38": "stratified",
+    "39": "striped",
+    "40": "studded",
+    "41": "swirly",
+    "42": "veined",
+    "43": "waffled",
+    "44": "woven",
+    "45": "wrinkled",
+    "46": "zigzagged"
+  },
+  "label2id": {
+    "banded": 0,
+    "blotchy": 1,
+    "braided": 2,
+    "bubbly": 3,
+    "bumpy": 4,
+    "chequered": 5,
+    "cobwebbed": 6,
+    "cracked": 7,
+    "crosshatched": 8,
+    "crystalline": 9,
+    "dotted": 10,
+    "fibrous": 11,
+    "flecked": 12,
+    "freckled": 13,
+    "frilly": 14,
+    "gauzy": 15,
+    "grid": 16,
+    "grooved": 17,
+    "honeycombed": 18,
+    "interlaced": 19,
+    "knitted": 20,
+    "lacelike": 21,
+    "lined": 22,
+    "marbled": 23,
+    "matted": 24,
+    "meshed": 25,
+    "paisley": 26,
+    "perforated": 27,
+    "pitted": 28,
+    "pleated": 29,
+    "polka-dotted": 30,
+    "porous": 31,
+    "potholed": 32,
+    "scaly": 33,
+    "smeared": 34,
+    "spiralled": 35,
+    "sprinkled": 36,
+    "stained": 37,
+    "stratified": 38,
+    "striped": 39,
+    "studded": 40,
+    "swirly": 41,
+    "veined": 42,
+    "waffled": 43,
+    "woven": 44,
+    "wrinkled": 45,
+    "zigzagged": 46
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-dtd-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet50-dtd-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-dtd-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-dtd-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/README.md b/resnet50-dtd-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..51f4dc6385799b4b040f69390c9bfa13766223fe
--- /dev/null
+++ b/resnet50-dtd-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset dtd.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: dtd
+    pretrained: true
+test_datasets: null
+train_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: train
+type: transformers
+val_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: test
+```
+
diff --git a/resnet50-dtd-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/config.json b/resnet50-dtd-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..9be9d43cf554cd4001bc241de10a3998fe29da7d
--- /dev/null
+++ b/resnet50-dtd-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,137 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "banded",
+    "1": "blotchy",
+    "2": "braided",
+    "3": "bubbly",
+    "4": "bumpy",
+    "5": "chequered",
+    "6": "cobwebbed",
+    "7": "cracked",
+    "8": "crosshatched",
+    "9": "crystalline",
+    "10": "dotted",
+    "11": "fibrous",
+    "12": "flecked",
+    "13": "freckled",
+    "14": "frilly",
+    "15": "gauzy",
+    "16": "grid",
+    "17": "grooved",
+    "18": "honeycombed",
+    "19": "interlaced",
+    "20": "knitted",
+    "21": "lacelike",
+    "22": "lined",
+    "23": "marbled",
+    "24": "matted",
+    "25": "meshed",
+    "26": "paisley",
+    "27": "perforated",
+    "28": "pitted",
+    "29": "pleated",
+    "30": "polka-dotted",
+    "31": "porous",
+    "32": "potholed",
+    "33": "scaly",
+    "34": "smeared",
+    "35": "spiralled",
+    "36": "sprinkled",
+    "37": "stained",
+    "38": "stratified",
+    "39": "striped",
+    "40": "studded",
+    "41": "swirly",
+    "42": "veined",
+    "43": "waffled",
+    "44": "woven",
+    "45": "wrinkled",
+    "46": "zigzagged"
+  },
+  "label2id": {
+    "banded": 0,
+    "blotchy": 1,
+    "braided": 2,
+    "bubbly": 3,
+    "bumpy": 4,
+    "chequered": 5,
+    "cobwebbed": 6,
+    "cracked": 7,
+    "crosshatched": 8,
+    "crystalline": 9,
+    "dotted": 10,
+    "fibrous": 11,
+    "flecked": 12,
+    "freckled": 13,
+    "frilly": 14,
+    "gauzy": 15,
+    "grid": 16,
+    "grooved": 17,
+    "honeycombed": 18,
+    "interlaced": 19,
+    "knitted": 20,
+    "lacelike": 21,
+    "lined": 22,
+    "marbled": 23,
+    "matted": 24,
+    "meshed": 25,
+    "paisley": 26,
+    "perforated": 27,
+    "pitted": 28,
+    "pleated": 29,
+    "polka-dotted": 30,
+    "porous": 31,
+    "potholed": 32,
+    "scaly": 33,
+    "smeared": 34,
+    "spiralled": 35,
+    "sprinkled": 36,
+    "stained": 37,
+    "stratified": 38,
+    "striped": 39,
+    "studded": 40,
+    "swirly": 41,
+    "veined": 42,
+    "waffled": 43,
+    "woven": 44,
+    "wrinkled": 45,
+    "zigzagged": 46
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-dtd-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet50-dtd-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-dtd-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-dtd-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/README.md b/resnet50-dtd-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..51f4dc6385799b4b040f69390c9bfa13766223fe
--- /dev/null
+++ b/resnet50-dtd-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset dtd.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: dtd
+    pretrained: true
+test_datasets: null
+train_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: train
+type: transformers
+val_datasets:
+  dtd:
+    _target_: datasets.load_dataset
+    path: tanganke/dtd
+    split: test
+```
+
diff --git a/resnet50-dtd-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/config.json b/resnet50-dtd-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..9be9d43cf554cd4001bc241de10a3998fe29da7d
--- /dev/null
+++ b/resnet50-dtd-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/config.json
@@ -0,0 +1,137 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "banded",
+    "1": "blotchy",
+    "2": "braided",
+    "3": "bubbly",
+    "4": "bumpy",
+    "5": "chequered",
+    "6": "cobwebbed",
+    "7": "cracked",
+    "8": "crosshatched",
+    "9": "crystalline",
+    "10": "dotted",
+    "11": "fibrous",
+    "12": "flecked",
+    "13": "freckled",
+    "14": "frilly",
+    "15": "gauzy",
+    "16": "grid",
+    "17": "grooved",
+    "18": "honeycombed",
+    "19": "interlaced",
+    "20": "knitted",
+    "21": "lacelike",
+    "22": "lined",
+    "23": "marbled",
+    "24": "matted",
+    "25": "meshed",
+    "26": "paisley",
+    "27": "perforated",
+    "28": "pitted",
+    "29": "pleated",
+    "30": "polka-dotted",
+    "31": "porous",
+    "32": "potholed",
+    "33": "scaly",
+    "34": "smeared",
+    "35": "spiralled",
+    "36": "sprinkled",
+    "37": "stained",
+    "38": "stratified",
+    "39": "striped",
+    "40": "studded",
+    "41": "swirly",
+    "42": "veined",
+    "43": "waffled",
+    "44": "woven",
+    "45": "wrinkled",
+    "46": "zigzagged"
+  },
+  "label2id": {
+    "banded": 0,
+    "blotchy": 1,
+    "braided": 2,
+    "bubbly": 3,
+    "bumpy": 4,
+    "chequered": 5,
+    "cobwebbed": 6,
+    "cracked": 7,
+    "crosshatched": 8,
+    "crystalline": 9,
+    "dotted": 10,
+    "fibrous": 11,
+    "flecked": 12,
+    "freckled": 13,
+    "frilly": 14,
+    "gauzy": 15,
+    "grid": 16,
+    "grooved": 17,
+    "honeycombed": 18,
+    "interlaced": 19,
+    "knitted": 20,
+    "lacelike": 21,
+    "lined": 22,
+    "marbled": 23,
+    "matted": 24,
+    "meshed": 25,
+    "paisley": 26,
+    "perforated": 27,
+    "pitted": 28,
+    "pleated": 29,
+    "polka-dotted": 30,
+    "porous": 31,
+    "potholed": 32,
+    "scaly": 33,
+    "smeared": 34,
+    "spiralled": 35,
+    "sprinkled": 36,
+    "stained": 37,
+    "stratified": 38,
+    "striped": 39,
+    "studded": 40,
+    "swirly": 41,
+    "veined": 42,
+    "waffled": 43,
+    "woven": 44,
+    "wrinkled": 45,
+    "zigzagged": 46
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-dtd-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet50-dtd-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-dtd-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/README.md b/resnet50-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..8a06bb71a790258a80220772a737829fd3260557
--- /dev/null
+++ b/resnet50-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset emnist_letters.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: emnist_letters
+    pretrained: true
+test_datasets: null
+train_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: train
+type: transformers
+val_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: test
+```
+
diff --git a/resnet50-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/config.json b/resnet50-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..9d1862748747d6d484a29b20c512dd46535c93b1
--- /dev/null
+++ b/resnet50-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,95 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "A",
+    "1": "B",
+    "2": "C",
+    "3": "D",
+    "4": "E",
+    "5": "F",
+    "6": "G",
+    "7": "H",
+    "8": "I",
+    "9": "J",
+    "10": "K",
+    "11": "L",
+    "12": "M",
+    "13": "N",
+    "14": "O",
+    "15": "P",
+    "16": "Q",
+    "17": "R",
+    "18": "S",
+    "19": "T",
+    "20": "U",
+    "21": "V",
+    "22": "W",
+    "23": "X",
+    "24": "Y",
+    "25": "Z"
+  },
+  "label2id": {
+    "A": 0,
+    "B": 1,
+    "C": 2,
+    "D": 3,
+    "E": 4,
+    "F": 5,
+    "G": 6,
+    "H": 7,
+    "I": 8,
+    "J": 9,
+    "K": 10,
+    "L": 11,
+    "M": 12,
+    "N": 13,
+    "O": 14,
+    "P": 15,
+    "Q": 16,
+    "R": 17,
+    "S": 18,
+    "T": 19,
+    "U": 20,
+    "V": 21,
+    "W": 22,
+    "X": 23,
+    "Y": 24,
+    "Z": 25
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet50-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/README.md b/resnet50-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..45b880ed737336688dae542e9e77876550cc8326
--- /dev/null
+++ b/resnet50-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset emnist_letters.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: emnist_letters
+    pretrained: true
+test_datasets: null
+train_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: train
+type: transformers
+val_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: test
+```
+
diff --git a/resnet50-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/config.json b/resnet50-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..9d1862748747d6d484a29b20c512dd46535c93b1
--- /dev/null
+++ b/resnet50-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,95 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "A",
+    "1": "B",
+    "2": "C",
+    "3": "D",
+    "4": "E",
+    "5": "F",
+    "6": "G",
+    "7": "H",
+    "8": "I",
+    "9": "J",
+    "10": "K",
+    "11": "L",
+    "12": "M",
+    "13": "N",
+    "14": "O",
+    "15": "P",
+    "16": "Q",
+    "17": "R",
+    "18": "S",
+    "19": "T",
+    "20": "U",
+    "21": "V",
+    "22": "W",
+    "23": "X",
+    "24": "Y",
+    "25": "Z"
+  },
+  "label2id": {
+    "A": 0,
+    "B": 1,
+    "C": 2,
+    "D": 3,
+    "E": 4,
+    "F": 5,
+    "G": 6,
+    "H": 7,
+    "I": 8,
+    "J": 9,
+    "K": 10,
+    "L": 11,
+    "M": 12,
+    "N": 13,
+    "O": 14,
+    "P": 15,
+    "Q": 16,
+    "R": 17,
+    "S": 18,
+    "T": 19,
+    "U": 20,
+    "V": 21,
+    "W": 22,
+    "X": 23,
+    "Y": 24,
+    "Z": 25
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet50-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-emnist_letters-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/README.md b/resnet50-emnist_letters-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..0af350195995ac0ce7579a1b3c792c61dd90ce6c
--- /dev/null
+++ b/resnet50-emnist_letters-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset emnist_letters.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: emnist_letters
+    pretrained: true
+test_datasets: null
+train_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: train
+type: transformers
+val_datasets:
+  emnist_letters:
+    _target_: datasets.load_dataset
+    path: tanganke/emnist_letters
+    split: test
+```
+
diff --git a/resnet50-emnist_letters-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/config.json b/resnet50-emnist_letters-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..9d1862748747d6d484a29b20c512dd46535c93b1
--- /dev/null
+++ b/resnet50-emnist_letters-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,95 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "A",
+    "1": "B",
+    "2": "C",
+    "3": "D",
+    "4": "E",
+    "5": "F",
+    "6": "G",
+    "7": "H",
+    "8": "I",
+    "9": "J",
+    "10": "K",
+    "11": "L",
+    "12": "M",
+    "13": "N",
+    "14": "O",
+    "15": "P",
+    "16": "Q",
+    "17": "R",
+    "18": "S",
+    "19": "T",
+    "20": "U",
+    "21": "V",
+    "22": "W",
+    "23": "X",
+    "24": "Y",
+    "25": "Z"
+  },
+  "label2id": {
+    "A": 0,
+    "B": 1,
+    "C": 2,
+    "D": 3,
+    "E": 4,
+    "F": 5,
+    "G": 6,
+    "H": 7,
+    "I": 8,
+    "J": 9,
+    "K": 10,
+    "L": 11,
+    "M": 12,
+    "N": 13,
+    "O": 14,
+    "P": 15,
+    "Q": 16,
+    "R": 17,
+    "S": 18,
+    "T": 19,
+    "U": 20,
+    "V": 21,
+    "W": 22,
+    "X": 23,
+    "Y": 24,
+    "Z": 25
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-emnist_letters-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet50-emnist_letters-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-emnist_letters-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/README.md b/resnet50-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..7782f205e8358688ced886fadfbf5471d2b843b7
--- /dev/null
+++ b/resnet50-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset eurosat.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: eurosat
+    pretrained: true
+test_datasets: null
+train_datasets:
+  eurosat:
+    _target_: datasets.load_dataset
+    path: tanganke/eurosat
+    split: train
+type: transformers
+val_datasets:
+  eurosat:
+    _target_: datasets.load_dataset
+    path: tanganke/eurosat
+    split: test
+```
+
diff --git a/resnet50-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/config.json b/resnet50-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..4b8f5a722ee7ec6f4a2d02ac651ae80260967eae
--- /dev/null
+++ b/resnet50-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "annual crop land",
+    "1": "forest",
+    "2": "brushland or shrubland",
+    "3": "highway or road",
+    "4": "industrial buildings or commercial buildings",
+    "5": "pasture land",
+    "6": "permanent crop land",
+    "7": "residential buildings or homes or apartments",
+    "8": "river",
+    "9": "lake or sea"
+  },
+  "label2id": {
+    "annual crop land": 0,
+    "brushland or shrubland": 2,
+    "forest": 1,
+    "highway or road": 3,
+    "industrial buildings or commercial buildings": 4,
+    "lake or sea": 9,
+    "pasture land": 5,
+    "permanent crop land": 6,
+    "residential buildings or homes or apartments": 7,
+    "river": 8
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet50-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/README.md b/resnet50-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..13099bcf0467d99986a093661b30811ba1c44df8
--- /dev/null
+++ b/resnet50-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fashion_mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: fashion_mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: train
+type: transformers
+val_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: test
+```
+
diff --git a/resnet50-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/config.json b/resnet50-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..55bcbf447ad396e78893f8c1d15e0049595b04f9
--- /dev/null
+++ b/resnet50-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "T - shirt / top",
+    "1": "Trouser",
+    "2": "Pullover",
+    "3": "Dress",
+    "4": "Coat",
+    "5": "Sandal",
+    "6": "Shirt",
+    "7": "Sneaker",
+    "8": "Bag",
+    "9": "Ankle boot"
+  },
+  "label2id": {
+    "Ankle boot": 9,
+    "Bag": 8,
+    "Coat": 4,
+    "Dress": 3,
+    "Pullover": 2,
+    "Sandal": 5,
+    "Shirt": 6,
+    "Sneaker": 7,
+    "T - shirt / top": 0,
+    "Trouser": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet50-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-fashion_mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/README.md b/resnet50-fashion_mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..4a6290ca7ee504fa362caf570e823c88ab97a91b
--- /dev/null
+++ b/resnet50-fashion_mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fashion_mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: fashion_mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: train
+type: transformers
+val_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: test
+```
+
diff --git a/resnet50-fashion_mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/config.json b/resnet50-fashion_mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..55bcbf447ad396e78893f8c1d15e0049595b04f9
--- /dev/null
+++ b/resnet50-fashion_mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "T - shirt / top",
+    "1": "Trouser",
+    "2": "Pullover",
+    "3": "Dress",
+    "4": "Coat",
+    "5": "Sandal",
+    "6": "Shirt",
+    "7": "Sneaker",
+    "8": "Bag",
+    "9": "Ankle boot"
+  },
+  "label2id": {
+    "Ankle boot": 9,
+    "Bag": 8,
+    "Coat": 4,
+    "Dress": 3,
+    "Pullover": 2,
+    "Sandal": 5,
+    "Shirt": 6,
+    "Sneaker": 7,
+    "T - shirt / top": 0,
+    "Trouser": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-fashion_mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet50-fashion_mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-fashion_mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-fashion_mnist-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/README.md b/resnet50-fashion_mnist-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..0a83e43d91a81fcac08d97a9df4cdd18fbc35eb3
--- /dev/null
+++ b/resnet50-fashion_mnist-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fashion_mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: fashion_mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: train
+type: transformers
+val_datasets:
+  fashion_mnist:
+    _target_: datasets.load_dataset
+    path: zalando-datasets/fashion_mnist
+    split: test
+```
+
diff --git a/resnet50-fashion_mnist-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/config.json b/resnet50-fashion_mnist-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..55bcbf447ad396e78893f8c1d15e0049595b04f9
--- /dev/null
+++ b/resnet50-fashion_mnist-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "T - shirt / top",
+    "1": "Trouser",
+    "2": "Pullover",
+    "3": "Dress",
+    "4": "Coat",
+    "5": "Sandal",
+    "6": "Shirt",
+    "7": "Sneaker",
+    "8": "Bag",
+    "9": "Ankle boot"
+  },
+  "label2id": {
+    "Ankle boot": 9,
+    "Bag": 8,
+    "Coat": 4,
+    "Dress": 3,
+    "Pullover": 2,
+    "Sandal": 5,
+    "Shirt": 6,
+    "Sneaker": 7,
+    "T - shirt / top": 0,
+    "Trouser": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-fashion_mnist-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet50-fashion_mnist-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-fashion_mnist-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-fer2013-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/README.md b/resnet50-fer2013-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..74ae1e5f2bad116bfaa450d352aa08de2d1c4170
--- /dev/null
+++ b/resnet50-fer2013-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/README.md
@@ -0,0 +1,74 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fer2013.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: fer2013
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: train
+type: transformers
+val_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: test
+```
+
diff --git a/resnet50-fer2013-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/config.json b/resnet50-fer2013-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..f25f031e5d55136af7a32fa76d4d09b952d788fc
--- /dev/null
+++ b/resnet50-fer2013-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/config.json
@@ -0,0 +1,57 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "angry",
+    "1": "disgusted",
+    "2": "fearful",
+    "3": "happy",
+    "4": "neutral",
+    "5": "sad",
+    "6": "surprised"
+  },
+  "label2id": {
+    "angry": 0,
+    "disgusted": 1,
+    "fearful": 2,
+    "happy": 3,
+    "neutral": 4,
+    "sad": 5,
+    "surprised": 6
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-fer2013-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet50-fer2013-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-fer2013-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/README.md b/resnet50-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..8b22f1a47f4fee15d105b690de1a87f7f198f09e
--- /dev/null
+++ b/resnet50-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,74 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fer2013.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: fer2013
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: train
+type: transformers
+val_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: test
+```
+
diff --git a/resnet50-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/config.json b/resnet50-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..f25f031e5d55136af7a32fa76d4d09b952d788fc
--- /dev/null
+++ b/resnet50-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,57 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "angry",
+    "1": "disgusted",
+    "2": "fearful",
+    "3": "happy",
+    "4": "neutral",
+    "5": "sad",
+    "6": "surprised"
+  },
+  "label2id": {
+    "angry": 0,
+    "disgusted": 1,
+    "fearful": 2,
+    "happy": 3,
+    "neutral": 4,
+    "sad": 5,
+    "surprised": 6
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet50-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-fer2013-batch_size_64_lr_0.01_training_data_ratio_0.5-1000/README.md b/resnet50-fer2013-batch_size_64_lr_0.01_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..036013b268f7b9c9bce3d26179bac032f435955d
--- /dev/null
+++ b/resnet50-fer2013-batch_size_64_lr_0.01_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,74 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fer2013.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: fer2013
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: train
+type: transformers
+val_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: test
+```
+
diff --git a/resnet50-fer2013-batch_size_64_lr_0.01_training_data_ratio_0.5-1000/config.json b/resnet50-fer2013-batch_size_64_lr_0.01_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..f25f031e5d55136af7a32fa76d4d09b952d788fc
--- /dev/null
+++ b/resnet50-fer2013-batch_size_64_lr_0.01_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,57 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "angry",
+    "1": "disgusted",
+    "2": "fearful",
+    "3": "happy",
+    "4": "neutral",
+    "5": "sad",
+    "6": "surprised"
+  },
+  "label2id": {
+    "angry": 0,
+    "disgusted": 1,
+    "fearful": 2,
+    "happy": 3,
+    "neutral": 4,
+    "sad": 5,
+    "surprised": 6
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-fer2013-batch_size_64_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet50-fer2013-batch_size_64_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-fer2013-batch_size_64_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-fer2013-batch_size_64_lr_0.01_training_data_ratio_0.8-3000/README.md b/resnet50-fer2013-batch_size_64_lr_0.01_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..66ebbfc994841bf8ec402bbffbba564e9afd3f14
--- /dev/null
+++ b/resnet50-fer2013-batch_size_64_lr_0.01_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,74 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset fer2013.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: fer2013
+    pretrained: true
+test_datasets: null
+train_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: train
+type: transformers
+val_datasets:
+  fer2013:
+    _target_: fusion_bench.dataset.fer2013.load_fer2013
+    split: test
+```
+
diff --git a/resnet50-fer2013-batch_size_64_lr_0.01_training_data_ratio_0.8-3000/config.json b/resnet50-fer2013-batch_size_64_lr_0.01_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..f25f031e5d55136af7a32fa76d4d09b952d788fc
--- /dev/null
+++ b/resnet50-fer2013-batch_size_64_lr_0.01_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,57 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "angry",
+    "1": "disgusted",
+    "2": "fearful",
+    "3": "happy",
+    "4": "neutral",
+    "5": "sad",
+    "6": "surprised"
+  },
+  "label2id": {
+    "angry": 0,
+    "disgusted": 1,
+    "fearful": 2,
+    "happy": 3,
+    "neutral": 4,
+    "sad": 5,
+    "surprised": 6
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-fer2013-batch_size_64_lr_0.01_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet50-fer2013-batch_size_64_lr_0.01_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-fer2013-batch_size_64_lr_0.01_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-food101-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md b/resnet50-food101-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..f90347eee83461007db0dced4aea08a543449eed
--- /dev/null
+++ b/resnet50-food101-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset food101.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: food101
+    pretrained: true
+test_datasets: null
+train_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: train
+type: transformers
+val_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: validation
+```
+
diff --git a/resnet50-food101-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/config.json b/resnet50-food101-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..d9f442b44934b43685324cae134e295127e8bfb3
--- /dev/null
+++ b/resnet50-food101-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,245 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "apple pie",
+    "1": "baby back ribs",
+    "2": "baklava",
+    "3": "beef carpaccio",
+    "4": "beef tartare",
+    "5": "beet salad",
+    "6": "beignets",
+    "7": "bibimbap",
+    "8": "bread pudding",
+    "9": "breakfast burrito",
+    "10": "bruschetta",
+    "11": "caesar salad",
+    "12": "cannoli",
+    "13": "caprese salad",
+    "14": "carrot cake",
+    "15": "ceviche",
+    "16": "cheese plate",
+    "17": "cheesecake",
+    "18": "chicken curry",
+    "19": "chicken quesadilla",
+    "20": "chicken wings",
+    "21": "chocolate cake",
+    "22": "chocolate mousse",
+    "23": "churros",
+    "24": "clam chowder",
+    "25": "club sandwich",
+    "26": "crab cakes",
+    "27": "creme brulee",
+    "28": "croque madame",
+    "29": "cup cakes",
+    "30": "deviled eggs",
+    "31": "donuts",
+    "32": "dumplings",
+    "33": "edamame",
+    "34": "eggs benedict",
+    "35": "escargots",
+    "36": "falafel",
+    "37": "filet mignon",
+    "38": "fish and chips",
+    "39": "foie gras",
+    "40": "french fries",
+    "41": "french onion soup",
+    "42": "french toast",
+    "43": "fried calamari",
+    "44": "fried rice",
+    "45": "frozen yogurt",
+    "46": "garlic bread",
+    "47": "gnocchi",
+    "48": "greek salad",
+    "49": "grilled cheese sandwich",
+    "50": "grilled salmon",
+    "51": "guacamole",
+    "52": "gyoza",
+    "53": "hamburger",
+    "54": "hot and sour soup",
+    "55": "hot dog",
+    "56": "huevos rancheros",
+    "57": "hummus",
+    "58": "ice cream",
+    "59": "lasagna",
+    "60": "lobster bisque",
+    "61": "lobster roll sandwich",
+    "62": "macaroni and cheese",
+    "63": "macarons",
+    "64": "miso soup",
+    "65": "mussels",
+    "66": "nachos",
+    "67": "omelette",
+    "68": "onion rings",
+    "69": "oysters",
+    "70": "pad thai",
+    "71": "paella",
+    "72": "pancakes",
+    "73": "panna cotta",
+    "74": "peking duck",
+    "75": "pho",
+    "76": "pizza",
+    "77": "pork chop",
+    "78": "poutine",
+    "79": "prime rib",
+    "80": "pulled pork sandwich",
+    "81": "ramen",
+    "82": "ravioli",
+    "83": "red velvet cake",
+    "84": "risotto",
+    "85": "samosa",
+    "86": "sashimi",
+    "87": "scallops",
+    "88": "seaweed salad",
+    "89": "shrimp and grits",
+    "90": "spaghetti bolognese",
+    "91": "spaghetti carbonara",
+    "92": "spring rolls",
+    "93": "steak",
+    "94": "strawberry shortcake",
+    "95": "sushi",
+    "96": "tacos",
+    "97": "takoyaki",
+    "98": "tiramisu",
+    "99": "tuna tartare",
+    "100": "waffles"
+  },
+  "label2id": {
+    "apple pie": 0,
+    "baby back ribs": 1,
+    "baklava": 2,
+    "beef carpaccio": 3,
+    "beef tartare": 4,
+    "beet salad": 5,
+    "beignets": 6,
+    "bibimbap": 7,
+    "bread pudding": 8,
+    "breakfast burrito": 9,
+    "bruschetta": 10,
+    "caesar salad": 11,
+    "cannoli": 12,
+    "caprese salad": 13,
+    "carrot cake": 14,
+    "ceviche": 15,
+    "cheese plate": 16,
+    "cheesecake": 17,
+    "chicken curry": 18,
+    "chicken quesadilla": 19,
+    "chicken wings": 20,
+    "chocolate cake": 21,
+    "chocolate mousse": 22,
+    "churros": 23,
+    "clam chowder": 24,
+    "club sandwich": 25,
+    "crab cakes": 26,
+    "creme brulee": 27,
+    "croque madame": 28,
+    "cup cakes": 29,
+    "deviled eggs": 30,
+    "donuts": 31,
+    "dumplings": 32,
+    "edamame": 33,
+    "eggs benedict": 34,
+    "escargots": 35,
+    "falafel": 36,
+    "filet mignon": 37,
+    "fish and chips": 38,
+    "foie gras": 39,
+    "french fries": 40,
+    "french onion soup": 41,
+    "french toast": 42,
+    "fried calamari": 43,
+    "fried rice": 44,
+    "frozen yogurt": 45,
+    "garlic bread": 46,
+    "gnocchi": 47,
+    "greek salad": 48,
+    "grilled cheese sandwich": 49,
+    "grilled salmon": 50,
+    "guacamole": 51,
+    "gyoza": 52,
+    "hamburger": 53,
+    "hot and sour soup": 54,
+    "hot dog": 55,
+    "huevos rancheros": 56,
+    "hummus": 57,
+    "ice cream": 58,
+    "lasagna": 59,
+    "lobster bisque": 60,
+    "lobster roll sandwich": 61,
+    "macaroni and cheese": 62,
+    "macarons": 63,
+    "miso soup": 64,
+    "mussels": 65,
+    "nachos": 66,
+    "omelette": 67,
+    "onion rings": 68,
+    "oysters": 69,
+    "pad thai": 70,
+    "paella": 71,
+    "pancakes": 72,
+    "panna cotta": 73,
+    "peking duck": 74,
+    "pho": 75,
+    "pizza": 76,
+    "pork chop": 77,
+    "poutine": 78,
+    "prime rib": 79,
+    "pulled pork sandwich": 80,
+    "ramen": 81,
+    "ravioli": 82,
+    "red velvet cake": 83,
+    "risotto": 84,
+    "samosa": 85,
+    "sashimi": 86,
+    "scallops": 87,
+    "seaweed salad": 88,
+    "shrimp and grits": 89,
+    "spaghetti bolognese": 90,
+    "spaghetti carbonara": 91,
+    "spring rolls": 92,
+    "steak": 93,
+    "strawberry shortcake": 94,
+    "sushi": 95,
+    "tacos": 96,
+    "takoyaki": 97,
+    "tiramisu": 98,
+    "tuna tartare": 99,
+    "waffles": 100
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-food101-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet50-food101-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-food101-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-food101-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/README.md b/resnet50-food101-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..b2002f7813117ed345859d3816684285abcef01b
--- /dev/null
+++ b/resnet50-food101-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset food101.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: food101
+    pretrained: true
+test_datasets: null
+train_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: train
+type: transformers
+val_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: validation
+```
+
diff --git a/resnet50-food101-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/config.json b/resnet50-food101-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..d9f442b44934b43685324cae134e295127e8bfb3
--- /dev/null
+++ b/resnet50-food101-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,245 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "apple pie",
+    "1": "baby back ribs",
+    "2": "baklava",
+    "3": "beef carpaccio",
+    "4": "beef tartare",
+    "5": "beet salad",
+    "6": "beignets",
+    "7": "bibimbap",
+    "8": "bread pudding",
+    "9": "breakfast burrito",
+    "10": "bruschetta",
+    "11": "caesar salad",
+    "12": "cannoli",
+    "13": "caprese salad",
+    "14": "carrot cake",
+    "15": "ceviche",
+    "16": "cheese plate",
+    "17": "cheesecake",
+    "18": "chicken curry",
+    "19": "chicken quesadilla",
+    "20": "chicken wings",
+    "21": "chocolate cake",
+    "22": "chocolate mousse",
+    "23": "churros",
+    "24": "clam chowder",
+    "25": "club sandwich",
+    "26": "crab cakes",
+    "27": "creme brulee",
+    "28": "croque madame",
+    "29": "cup cakes",
+    "30": "deviled eggs",
+    "31": "donuts",
+    "32": "dumplings",
+    "33": "edamame",
+    "34": "eggs benedict",
+    "35": "escargots",
+    "36": "falafel",
+    "37": "filet mignon",
+    "38": "fish and chips",
+    "39": "foie gras",
+    "40": "french fries",
+    "41": "french onion soup",
+    "42": "french toast",
+    "43": "fried calamari",
+    "44": "fried rice",
+    "45": "frozen yogurt",
+    "46": "garlic bread",
+    "47": "gnocchi",
+    "48": "greek salad",
+    "49": "grilled cheese sandwich",
+    "50": "grilled salmon",
+    "51": "guacamole",
+    "52": "gyoza",
+    "53": "hamburger",
+    "54": "hot and sour soup",
+    "55": "hot dog",
+    "56": "huevos rancheros",
+    "57": "hummus",
+    "58": "ice cream",
+    "59": "lasagna",
+    "60": "lobster bisque",
+    "61": "lobster roll sandwich",
+    "62": "macaroni and cheese",
+    "63": "macarons",
+    "64": "miso soup",
+    "65": "mussels",
+    "66": "nachos",
+    "67": "omelette",
+    "68": "onion rings",
+    "69": "oysters",
+    "70": "pad thai",
+    "71": "paella",
+    "72": "pancakes",
+    "73": "panna cotta",
+    "74": "peking duck",
+    "75": "pho",
+    "76": "pizza",
+    "77": "pork chop",
+    "78": "poutine",
+    "79": "prime rib",
+    "80": "pulled pork sandwich",
+    "81": "ramen",
+    "82": "ravioli",
+    "83": "red velvet cake",
+    "84": "risotto",
+    "85": "samosa",
+    "86": "sashimi",
+    "87": "scallops",
+    "88": "seaweed salad",
+    "89": "shrimp and grits",
+    "90": "spaghetti bolognese",
+    "91": "spaghetti carbonara",
+    "92": "spring rolls",
+    "93": "steak",
+    "94": "strawberry shortcake",
+    "95": "sushi",
+    "96": "tacos",
+    "97": "takoyaki",
+    "98": "tiramisu",
+    "99": "tuna tartare",
+    "100": "waffles"
+  },
+  "label2id": {
+    "apple pie": 0,
+    "baby back ribs": 1,
+    "baklava": 2,
+    "beef carpaccio": 3,
+    "beef tartare": 4,
+    "beet salad": 5,
+    "beignets": 6,
+    "bibimbap": 7,
+    "bread pudding": 8,
+    "breakfast burrito": 9,
+    "bruschetta": 10,
+    "caesar salad": 11,
+    "cannoli": 12,
+    "caprese salad": 13,
+    "carrot cake": 14,
+    "ceviche": 15,
+    "cheese plate": 16,
+    "cheesecake": 17,
+    "chicken curry": 18,
+    "chicken quesadilla": 19,
+    "chicken wings": 20,
+    "chocolate cake": 21,
+    "chocolate mousse": 22,
+    "churros": 23,
+    "clam chowder": 24,
+    "club sandwich": 25,
+    "crab cakes": 26,
+    "creme brulee": 27,
+    "croque madame": 28,
+    "cup cakes": 29,
+    "deviled eggs": 30,
+    "donuts": 31,
+    "dumplings": 32,
+    "edamame": 33,
+    "eggs benedict": 34,
+    "escargots": 35,
+    "falafel": 36,
+    "filet mignon": 37,
+    "fish and chips": 38,
+    "foie gras": 39,
+    "french fries": 40,
+    "french onion soup": 41,
+    "french toast": 42,
+    "fried calamari": 43,
+    "fried rice": 44,
+    "frozen yogurt": 45,
+    "garlic bread": 46,
+    "gnocchi": 47,
+    "greek salad": 48,
+    "grilled cheese sandwich": 49,
+    "grilled salmon": 50,
+    "guacamole": 51,
+    "gyoza": 52,
+    "hamburger": 53,
+    "hot and sour soup": 54,
+    "hot dog": 55,
+    "huevos rancheros": 56,
+    "hummus": 57,
+    "ice cream": 58,
+    "lasagna": 59,
+    "lobster bisque": 60,
+    "lobster roll sandwich": 61,
+    "macaroni and cheese": 62,
+    "macarons": 63,
+    "miso soup": 64,
+    "mussels": 65,
+    "nachos": 66,
+    "omelette": 67,
+    "onion rings": 68,
+    "oysters": 69,
+    "pad thai": 70,
+    "paella": 71,
+    "pancakes": 72,
+    "panna cotta": 73,
+    "peking duck": 74,
+    "pho": 75,
+    "pizza": 76,
+    "pork chop": 77,
+    "poutine": 78,
+    "prime rib": 79,
+    "pulled pork sandwich": 80,
+    "ramen": 81,
+    "ravioli": 82,
+    "red velvet cake": 83,
+    "risotto": 84,
+    "samosa": 85,
+    "sashimi": 86,
+    "scallops": 87,
+    "seaweed salad": 88,
+    "shrimp and grits": 89,
+    "spaghetti bolognese": 90,
+    "spaghetti carbonara": 91,
+    "spring rolls": 92,
+    "steak": 93,
+    "strawberry shortcake": 94,
+    "sushi": 95,
+    "tacos": 96,
+    "takoyaki": 97,
+    "tiramisu": 98,
+    "tuna tartare": 99,
+    "waffles": 100
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-food101-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet50-food101-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-food101-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-food101-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/README.md b/resnet50-food101-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..495666e735da519637fe8892028809904f11067e
--- /dev/null
+++ b/resnet50-food101-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset food101.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: food101
+    pretrained: true
+test_datasets: null
+train_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: train
+type: transformers
+val_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: validation
+```
+
diff --git a/resnet50-food101-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/config.json b/resnet50-food101-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..d9f442b44934b43685324cae134e295127e8bfb3
--- /dev/null
+++ b/resnet50-food101-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,245 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "apple pie",
+    "1": "baby back ribs",
+    "2": "baklava",
+    "3": "beef carpaccio",
+    "4": "beef tartare",
+    "5": "beet salad",
+    "6": "beignets",
+    "7": "bibimbap",
+    "8": "bread pudding",
+    "9": "breakfast burrito",
+    "10": "bruschetta",
+    "11": "caesar salad",
+    "12": "cannoli",
+    "13": "caprese salad",
+    "14": "carrot cake",
+    "15": "ceviche",
+    "16": "cheese plate",
+    "17": "cheesecake",
+    "18": "chicken curry",
+    "19": "chicken quesadilla",
+    "20": "chicken wings",
+    "21": "chocolate cake",
+    "22": "chocolate mousse",
+    "23": "churros",
+    "24": "clam chowder",
+    "25": "club sandwich",
+    "26": "crab cakes",
+    "27": "creme brulee",
+    "28": "croque madame",
+    "29": "cup cakes",
+    "30": "deviled eggs",
+    "31": "donuts",
+    "32": "dumplings",
+    "33": "edamame",
+    "34": "eggs benedict",
+    "35": "escargots",
+    "36": "falafel",
+    "37": "filet mignon",
+    "38": "fish and chips",
+    "39": "foie gras",
+    "40": "french fries",
+    "41": "french onion soup",
+    "42": "french toast",
+    "43": "fried calamari",
+    "44": "fried rice",
+    "45": "frozen yogurt",
+    "46": "garlic bread",
+    "47": "gnocchi",
+    "48": "greek salad",
+    "49": "grilled cheese sandwich",
+    "50": "grilled salmon",
+    "51": "guacamole",
+    "52": "gyoza",
+    "53": "hamburger",
+    "54": "hot and sour soup",
+    "55": "hot dog",
+    "56": "huevos rancheros",
+    "57": "hummus",
+    "58": "ice cream",
+    "59": "lasagna",
+    "60": "lobster bisque",
+    "61": "lobster roll sandwich",
+    "62": "macaroni and cheese",
+    "63": "macarons",
+    "64": "miso soup",
+    "65": "mussels",
+    "66": "nachos",
+    "67": "omelette",
+    "68": "onion rings",
+    "69": "oysters",
+    "70": "pad thai",
+    "71": "paella",
+    "72": "pancakes",
+    "73": "panna cotta",
+    "74": "peking duck",
+    "75": "pho",
+    "76": "pizza",
+    "77": "pork chop",
+    "78": "poutine",
+    "79": "prime rib",
+    "80": "pulled pork sandwich",
+    "81": "ramen",
+    "82": "ravioli",
+    "83": "red velvet cake",
+    "84": "risotto",
+    "85": "samosa",
+    "86": "sashimi",
+    "87": "scallops",
+    "88": "seaweed salad",
+    "89": "shrimp and grits",
+    "90": "spaghetti bolognese",
+    "91": "spaghetti carbonara",
+    "92": "spring rolls",
+    "93": "steak",
+    "94": "strawberry shortcake",
+    "95": "sushi",
+    "96": "tacos",
+    "97": "takoyaki",
+    "98": "tiramisu",
+    "99": "tuna tartare",
+    "100": "waffles"
+  },
+  "label2id": {
+    "apple pie": 0,
+    "baby back ribs": 1,
+    "baklava": 2,
+    "beef carpaccio": 3,
+    "beef tartare": 4,
+    "beet salad": 5,
+    "beignets": 6,
+    "bibimbap": 7,
+    "bread pudding": 8,
+    "breakfast burrito": 9,
+    "bruschetta": 10,
+    "caesar salad": 11,
+    "cannoli": 12,
+    "caprese salad": 13,
+    "carrot cake": 14,
+    "ceviche": 15,
+    "cheese plate": 16,
+    "cheesecake": 17,
+    "chicken curry": 18,
+    "chicken quesadilla": 19,
+    "chicken wings": 20,
+    "chocolate cake": 21,
+    "chocolate mousse": 22,
+    "churros": 23,
+    "clam chowder": 24,
+    "club sandwich": 25,
+    "crab cakes": 26,
+    "creme brulee": 27,
+    "croque madame": 28,
+    "cup cakes": 29,
+    "deviled eggs": 30,
+    "donuts": 31,
+    "dumplings": 32,
+    "edamame": 33,
+    "eggs benedict": 34,
+    "escargots": 35,
+    "falafel": 36,
+    "filet mignon": 37,
+    "fish and chips": 38,
+    "foie gras": 39,
+    "french fries": 40,
+    "french onion soup": 41,
+    "french toast": 42,
+    "fried calamari": 43,
+    "fried rice": 44,
+    "frozen yogurt": 45,
+    "garlic bread": 46,
+    "gnocchi": 47,
+    "greek salad": 48,
+    "grilled cheese sandwich": 49,
+    "grilled salmon": 50,
+    "guacamole": 51,
+    "gyoza": 52,
+    "hamburger": 53,
+    "hot and sour soup": 54,
+    "hot dog": 55,
+    "huevos rancheros": 56,
+    "hummus": 57,
+    "ice cream": 58,
+    "lasagna": 59,
+    "lobster bisque": 60,
+    "lobster roll sandwich": 61,
+    "macaroni and cheese": 62,
+    "macarons": 63,
+    "miso soup": 64,
+    "mussels": 65,
+    "nachos": 66,
+    "omelette": 67,
+    "onion rings": 68,
+    "oysters": 69,
+    "pad thai": 70,
+    "paella": 71,
+    "pancakes": 72,
+    "panna cotta": 73,
+    "peking duck": 74,
+    "pho": 75,
+    "pizza": 76,
+    "pork chop": 77,
+    "poutine": 78,
+    "prime rib": 79,
+    "pulled pork sandwich": 80,
+    "ramen": 81,
+    "ravioli": 82,
+    "red velvet cake": 83,
+    "risotto": 84,
+    "samosa": 85,
+    "sashimi": 86,
+    "scallops": 87,
+    "seaweed salad": 88,
+    "shrimp and grits": 89,
+    "spaghetti bolognese": 90,
+    "spaghetti carbonara": 91,
+    "spring rolls": 92,
+    "steak": 93,
+    "strawberry shortcake": 94,
+    "sushi": 95,
+    "tacos": 96,
+    "takoyaki": 97,
+    "tiramisu": 98,
+    "tuna tartare": 99,
+    "waffles": 100
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-food101-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet50-food101-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-food101-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-food101-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/README.md b/resnet50-food101-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..9ac788616883574ac2788eb8ebf5e623cb2db132
--- /dev/null
+++ b/resnet50-food101-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset food101.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: food101
+    pretrained: true
+test_datasets: null
+train_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: train
+type: transformers
+val_datasets:
+  food101:
+    _target_: datasets.load_dataset
+    path: ethz/food101
+    split: validation
+```
+
diff --git a/resnet50-food101-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/config.json b/resnet50-food101-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..d9f442b44934b43685324cae134e295127e8bfb3
--- /dev/null
+++ b/resnet50-food101-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,245 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "apple pie",
+    "1": "baby back ribs",
+    "2": "baklava",
+    "3": "beef carpaccio",
+    "4": "beef tartare",
+    "5": "beet salad",
+    "6": "beignets",
+    "7": "bibimbap",
+    "8": "bread pudding",
+    "9": "breakfast burrito",
+    "10": "bruschetta",
+    "11": "caesar salad",
+    "12": "cannoli",
+    "13": "caprese salad",
+    "14": "carrot cake",
+    "15": "ceviche",
+    "16": "cheese plate",
+    "17": "cheesecake",
+    "18": "chicken curry",
+    "19": "chicken quesadilla",
+    "20": "chicken wings",
+    "21": "chocolate cake",
+    "22": "chocolate mousse",
+    "23": "churros",
+    "24": "clam chowder",
+    "25": "club sandwich",
+    "26": "crab cakes",
+    "27": "creme brulee",
+    "28": "croque madame",
+    "29": "cup cakes",
+    "30": "deviled eggs",
+    "31": "donuts",
+    "32": "dumplings",
+    "33": "edamame",
+    "34": "eggs benedict",
+    "35": "escargots",
+    "36": "falafel",
+    "37": "filet mignon",
+    "38": "fish and chips",
+    "39": "foie gras",
+    "40": "french fries",
+    "41": "french onion soup",
+    "42": "french toast",
+    "43": "fried calamari",
+    "44": "fried rice",
+    "45": "frozen yogurt",
+    "46": "garlic bread",
+    "47": "gnocchi",
+    "48": "greek salad",
+    "49": "grilled cheese sandwich",
+    "50": "grilled salmon",
+    "51": "guacamole",
+    "52": "gyoza",
+    "53": "hamburger",
+    "54": "hot and sour soup",
+    "55": "hot dog",
+    "56": "huevos rancheros",
+    "57": "hummus",
+    "58": "ice cream",
+    "59": "lasagna",
+    "60": "lobster bisque",
+    "61": "lobster roll sandwich",
+    "62": "macaroni and cheese",
+    "63": "macarons",
+    "64": "miso soup",
+    "65": "mussels",
+    "66": "nachos",
+    "67": "omelette",
+    "68": "onion rings",
+    "69": "oysters",
+    "70": "pad thai",
+    "71": "paella",
+    "72": "pancakes",
+    "73": "panna cotta",
+    "74": "peking duck",
+    "75": "pho",
+    "76": "pizza",
+    "77": "pork chop",
+    "78": "poutine",
+    "79": "prime rib",
+    "80": "pulled pork sandwich",
+    "81": "ramen",
+    "82": "ravioli",
+    "83": "red velvet cake",
+    "84": "risotto",
+    "85": "samosa",
+    "86": "sashimi",
+    "87": "scallops",
+    "88": "seaweed salad",
+    "89": "shrimp and grits",
+    "90": "spaghetti bolognese",
+    "91": "spaghetti carbonara",
+    "92": "spring rolls",
+    "93": "steak",
+    "94": "strawberry shortcake",
+    "95": "sushi",
+    "96": "tacos",
+    "97": "takoyaki",
+    "98": "tiramisu",
+    "99": "tuna tartare",
+    "100": "waffles"
+  },
+  "label2id": {
+    "apple pie": 0,
+    "baby back ribs": 1,
+    "baklava": 2,
+    "beef carpaccio": 3,
+    "beef tartare": 4,
+    "beet salad": 5,
+    "beignets": 6,
+    "bibimbap": 7,
+    "bread pudding": 8,
+    "breakfast burrito": 9,
+    "bruschetta": 10,
+    "caesar salad": 11,
+    "cannoli": 12,
+    "caprese salad": 13,
+    "carrot cake": 14,
+    "ceviche": 15,
+    "cheese plate": 16,
+    "cheesecake": 17,
+    "chicken curry": 18,
+    "chicken quesadilla": 19,
+    "chicken wings": 20,
+    "chocolate cake": 21,
+    "chocolate mousse": 22,
+    "churros": 23,
+    "clam chowder": 24,
+    "club sandwich": 25,
+    "crab cakes": 26,
+    "creme brulee": 27,
+    "croque madame": 28,
+    "cup cakes": 29,
+    "deviled eggs": 30,
+    "donuts": 31,
+    "dumplings": 32,
+    "edamame": 33,
+    "eggs benedict": 34,
+    "escargots": 35,
+    "falafel": 36,
+    "filet mignon": 37,
+    "fish and chips": 38,
+    "foie gras": 39,
+    "french fries": 40,
+    "french onion soup": 41,
+    "french toast": 42,
+    "fried calamari": 43,
+    "fried rice": 44,
+    "frozen yogurt": 45,
+    "garlic bread": 46,
+    "gnocchi": 47,
+    "greek salad": 48,
+    "grilled cheese sandwich": 49,
+    "grilled salmon": 50,
+    "guacamole": 51,
+    "gyoza": 52,
+    "hamburger": 53,
+    "hot and sour soup": 54,
+    "hot dog": 55,
+    "huevos rancheros": 56,
+    "hummus": 57,
+    "ice cream": 58,
+    "lasagna": 59,
+    "lobster bisque": 60,
+    "lobster roll sandwich": 61,
+    "macaroni and cheese": 62,
+    "macarons": 63,
+    "miso soup": 64,
+    "mussels": 65,
+    "nachos": 66,
+    "omelette": 67,
+    "onion rings": 68,
+    "oysters": 69,
+    "pad thai": 70,
+    "paella": 71,
+    "pancakes": 72,
+    "panna cotta": 73,
+    "peking duck": 74,
+    "pho": 75,
+    "pizza": 76,
+    "pork chop": 77,
+    "poutine": 78,
+    "prime rib": 79,
+    "pulled pork sandwich": 80,
+    "ramen": 81,
+    "ravioli": 82,
+    "red velvet cake": 83,
+    "risotto": 84,
+    "samosa": 85,
+    "sashimi": 86,
+    "scallops": 87,
+    "seaweed salad": 88,
+    "shrimp and grits": 89,
+    "spaghetti bolognese": 90,
+    "spaghetti carbonara": 91,
+    "spring rolls": 92,
+    "steak": 93,
+    "strawberry shortcake": 94,
+    "sushi": 95,
+    "tacos": 96,
+    "takoyaki": 97,
+    "tiramisu": 98,
+    "tuna tartare": 99,
+    "waffles": 100
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-food101-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet50-food101-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-food101-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-gtsrb-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/README.md b/resnet50-gtsrb-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..f61314be74c0f29eb9c88777a5bb2687276f441c
--- /dev/null
+++ b/resnet50-gtsrb-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset gtsrb.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: gtsrb
+    pretrained: true
+test_datasets: null
+train_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: train
+type: transformers
+val_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: test
+```
+
diff --git a/resnet50-gtsrb-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/config.json b/resnet50-gtsrb-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..72e5aa2e6ca1e8845fcf4a68dc7cd82ec3c90ca4
--- /dev/null
+++ b/resnet50-gtsrb-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,129 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "red and white circle 20 kph speed limit",
+    "1": "red and white circle 30 kph speed limit",
+    "2": "red and white circle 50 kph speed limit",
+    "3": "red and white circle 60 kph speed limit",
+    "4": "red and white circle 70 kph speed limit",
+    "5": "red and white circle 80 kph speed limit",
+    "6": "end / de-restriction of 80 kph speed limit",
+    "7": "red and white circle 100 kph speed limit",
+    "8": "red and white circle 120 kph speed limit",
+    "9": "red and white circle red car and black car no passing",
+    "10": "red and white circle red truck and black car no passing",
+    "11": "red and white triangle road intersection warning",
+    "12": "white and yellow diamond priority road",
+    "13": "red and white upside down triangle yield right-of-way",
+    "14": "stop",
+    "15": "empty red and white circle",
+    "16": "red and white circle no truck entry",
+    "17": "red circle with white horizonal stripe no entry",
+    "18": "red and white triangle with exclamation mark warning",
+    "19": "red and white triangle with black left curve approaching warning",
+    "20": "red and white triangle with black right curve approaching warning",
+    "21": "red and white triangle with black double curve approaching warning",
+    "22": "red and white triangle rough / bumpy road warning",
+    "23": "red and white triangle car skidding / slipping warning",
+    "24": "red and white triangle with merging / narrow lanes warning",
+    "25": "red and white triangle with person digging / construction / road work warning",
+    "26": "red and white triangle with traffic light approaching warning",
+    "27": "red and white triangle with person walking warning",
+    "28": "red and white triangle with child and person walking warning",
+    "29": "red and white triangle with bicyle warning",
+    "30": "red and white triangle with snowflake / ice warning",
+    "31": "red and white triangle with deer warning",
+    "32": "white circle with gray strike bar no speed limit",
+    "33": "blue circle with white right turn arrow mandatory",
+    "34": "blue circle with white left turn arrow mandatory",
+    "35": "blue circle with white forward arrow mandatory",
+    "36": "blue circle with white forward or right turn arrow mandatory",
+    "37": "blue circle with white forward or left turn arrow mandatory",
+    "38": "blue circle with white keep right arrow mandatory",
+    "39": "blue circle with white keep left arrow mandatory",
+    "40": "blue circle with white arrows indicating a traffic circle",
+    "41": "white circle with gray strike bar indicating no passing for cars has ended",
+    "42": "white circle with gray strike bar indicating no passing for trucks has ended"
+  },
+  "label2id": {
+    "blue circle with white arrows indicating a traffic circle": 40,
+    "blue circle with white forward arrow mandatory": 35,
+    "blue circle with white forward or left turn arrow mandatory": 37,
+    "blue circle with white forward or right turn arrow mandatory": 36,
+    "blue circle with white keep left arrow mandatory": 39,
+    "blue circle with white keep right arrow mandatory": 38,
+    "blue circle with white left turn arrow mandatory": 34,
+    "blue circle with white right turn arrow mandatory": 33,
+    "empty red and white circle": 15,
+    "end / de-restriction of 80 kph speed limit": 6,
+    "red and white circle 100 kph speed limit": 7,
+    "red and white circle 120 kph speed limit": 8,
+    "red and white circle 20 kph speed limit": 0,
+    "red and white circle 30 kph speed limit": 1,
+    "red and white circle 50 kph speed limit": 2,
+    "red and white circle 60 kph speed limit": 3,
+    "red and white circle 70 kph speed limit": 4,
+    "red and white circle 80 kph speed limit": 5,
+    "red and white circle no truck entry": 16,
+    "red and white circle red car and black car no passing": 9,
+    "red and white circle red truck and black car no passing": 10,
+    "red and white triangle car skidding / slipping warning": 23,
+    "red and white triangle road intersection warning": 11,
+    "red and white triangle rough / bumpy road warning": 22,
+    "red and white triangle with bicyle warning": 29,
+    "red and white triangle with black double curve approaching warning": 21,
+    "red and white triangle with black left curve approaching warning": 19,
+    "red and white triangle with black right curve approaching warning": 20,
+    "red and white triangle with child and person walking warning": 28,
+    "red and white triangle with deer warning": 31,
+    "red and white triangle with exclamation mark warning": 18,
+    "red and white triangle with merging / narrow lanes warning": 24,
+    "red and white triangle with person digging / construction / road work warning": 25,
+    "red and white triangle with person walking warning": 27,
+    "red and white triangle with snowflake / ice warning": 30,
+    "red and white triangle with traffic light approaching warning": 26,
+    "red and white upside down triangle yield right-of-way": 13,
+    "red circle with white horizonal stripe no entry": 17,
+    "stop": 14,
+    "white and yellow diamond priority road": 12,
+    "white circle with gray strike bar indicating no passing for cars has ended": 41,
+    "white circle with gray strike bar indicating no passing for trucks has ended": 42,
+    "white circle with gray strike bar no speed limit": 32
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-gtsrb-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet50-gtsrb-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-gtsrb-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-gtsrb-batch_size_256_lr_0.005_training_data_ratio_0.5-3000/README.md b/resnet50-gtsrb-batch_size_256_lr_0.005_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..a93fc4f03b015f91af1170d7efc8eef2bebc3d25
--- /dev/null
+++ b/resnet50-gtsrb-batch_size_256_lr_0.005_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset gtsrb.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: gtsrb
+    pretrained: true
+test_datasets: null
+train_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: train
+type: transformers
+val_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: test
+```
+
diff --git a/resnet50-gtsrb-batch_size_256_lr_0.005_training_data_ratio_0.5-3000/config.json b/resnet50-gtsrb-batch_size_256_lr_0.005_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..72e5aa2e6ca1e8845fcf4a68dc7cd82ec3c90ca4
--- /dev/null
+++ b/resnet50-gtsrb-batch_size_256_lr_0.005_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,129 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "red and white circle 20 kph speed limit",
+    "1": "red and white circle 30 kph speed limit",
+    "2": "red and white circle 50 kph speed limit",
+    "3": "red and white circle 60 kph speed limit",
+    "4": "red and white circle 70 kph speed limit",
+    "5": "red and white circle 80 kph speed limit",
+    "6": "end / de-restriction of 80 kph speed limit",
+    "7": "red and white circle 100 kph speed limit",
+    "8": "red and white circle 120 kph speed limit",
+    "9": "red and white circle red car and black car no passing",
+    "10": "red and white circle red truck and black car no passing",
+    "11": "red and white triangle road intersection warning",
+    "12": "white and yellow diamond priority road",
+    "13": "red and white upside down triangle yield right-of-way",
+    "14": "stop",
+    "15": "empty red and white circle",
+    "16": "red and white circle no truck entry",
+    "17": "red circle with white horizonal stripe no entry",
+    "18": "red and white triangle with exclamation mark warning",
+    "19": "red and white triangle with black left curve approaching warning",
+    "20": "red and white triangle with black right curve approaching warning",
+    "21": "red and white triangle with black double curve approaching warning",
+    "22": "red and white triangle rough / bumpy road warning",
+    "23": "red and white triangle car skidding / slipping warning",
+    "24": "red and white triangle with merging / narrow lanes warning",
+    "25": "red and white triangle with person digging / construction / road work warning",
+    "26": "red and white triangle with traffic light approaching warning",
+    "27": "red and white triangle with person walking warning",
+    "28": "red and white triangle with child and person walking warning",
+    "29": "red and white triangle with bicyle warning",
+    "30": "red and white triangle with snowflake / ice warning",
+    "31": "red and white triangle with deer warning",
+    "32": "white circle with gray strike bar no speed limit",
+    "33": "blue circle with white right turn arrow mandatory",
+    "34": "blue circle with white left turn arrow mandatory",
+    "35": "blue circle with white forward arrow mandatory",
+    "36": "blue circle with white forward or right turn arrow mandatory",
+    "37": "blue circle with white forward or left turn arrow mandatory",
+    "38": "blue circle with white keep right arrow mandatory",
+    "39": "blue circle with white keep left arrow mandatory",
+    "40": "blue circle with white arrows indicating a traffic circle",
+    "41": "white circle with gray strike bar indicating no passing for cars has ended",
+    "42": "white circle with gray strike bar indicating no passing for trucks has ended"
+  },
+  "label2id": {
+    "blue circle with white arrows indicating a traffic circle": 40,
+    "blue circle with white forward arrow mandatory": 35,
+    "blue circle with white forward or left turn arrow mandatory": 37,
+    "blue circle with white forward or right turn arrow mandatory": 36,
+    "blue circle with white keep left arrow mandatory": 39,
+    "blue circle with white keep right arrow mandatory": 38,
+    "blue circle with white left turn arrow mandatory": 34,
+    "blue circle with white right turn arrow mandatory": 33,
+    "empty red and white circle": 15,
+    "end / de-restriction of 80 kph speed limit": 6,
+    "red and white circle 100 kph speed limit": 7,
+    "red and white circle 120 kph speed limit": 8,
+    "red and white circle 20 kph speed limit": 0,
+    "red and white circle 30 kph speed limit": 1,
+    "red and white circle 50 kph speed limit": 2,
+    "red and white circle 60 kph speed limit": 3,
+    "red and white circle 70 kph speed limit": 4,
+    "red and white circle 80 kph speed limit": 5,
+    "red and white circle no truck entry": 16,
+    "red and white circle red car and black car no passing": 9,
+    "red and white circle red truck and black car no passing": 10,
+    "red and white triangle car skidding / slipping warning": 23,
+    "red and white triangle road intersection warning": 11,
+    "red and white triangle rough / bumpy road warning": 22,
+    "red and white triangle with bicyle warning": 29,
+    "red and white triangle with black double curve approaching warning": 21,
+    "red and white triangle with black left curve approaching warning": 19,
+    "red and white triangle with black right curve approaching warning": 20,
+    "red and white triangle with child and person walking warning": 28,
+    "red and white triangle with deer warning": 31,
+    "red and white triangle with exclamation mark warning": 18,
+    "red and white triangle with merging / narrow lanes warning": 24,
+    "red and white triangle with person digging / construction / road work warning": 25,
+    "red and white triangle with person walking warning": 27,
+    "red and white triangle with snowflake / ice warning": 30,
+    "red and white triangle with traffic light approaching warning": 26,
+    "red and white upside down triangle yield right-of-way": 13,
+    "red circle with white horizonal stripe no entry": 17,
+    "stop": 14,
+    "white and yellow diamond priority road": 12,
+    "white circle with gray strike bar indicating no passing for cars has ended": 41,
+    "white circle with gray strike bar indicating no passing for trucks has ended": 42,
+    "white circle with gray strike bar no speed limit": 32
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-gtsrb-batch_size_256_lr_0.005_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet50-gtsrb-batch_size_256_lr_0.005_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-gtsrb-batch_size_256_lr_0.005_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-gtsrb-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/README.md b/resnet50-gtsrb-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..3a3deb062433a2358882542951fedff957505bef
--- /dev/null
+++ b/resnet50-gtsrb-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset gtsrb.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: gtsrb
+    pretrained: true
+test_datasets: null
+train_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: train
+type: transformers
+val_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: test
+```
+
diff --git a/resnet50-gtsrb-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/config.json b/resnet50-gtsrb-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..72e5aa2e6ca1e8845fcf4a68dc7cd82ec3c90ca4
--- /dev/null
+++ b/resnet50-gtsrb-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,129 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "red and white circle 20 kph speed limit",
+    "1": "red and white circle 30 kph speed limit",
+    "2": "red and white circle 50 kph speed limit",
+    "3": "red and white circle 60 kph speed limit",
+    "4": "red and white circle 70 kph speed limit",
+    "5": "red and white circle 80 kph speed limit",
+    "6": "end / de-restriction of 80 kph speed limit",
+    "7": "red and white circle 100 kph speed limit",
+    "8": "red and white circle 120 kph speed limit",
+    "9": "red and white circle red car and black car no passing",
+    "10": "red and white circle red truck and black car no passing",
+    "11": "red and white triangle road intersection warning",
+    "12": "white and yellow diamond priority road",
+    "13": "red and white upside down triangle yield right-of-way",
+    "14": "stop",
+    "15": "empty red and white circle",
+    "16": "red and white circle no truck entry",
+    "17": "red circle with white horizonal stripe no entry",
+    "18": "red and white triangle with exclamation mark warning",
+    "19": "red and white triangle with black left curve approaching warning",
+    "20": "red and white triangle with black right curve approaching warning",
+    "21": "red and white triangle with black double curve approaching warning",
+    "22": "red and white triangle rough / bumpy road warning",
+    "23": "red and white triangle car skidding / slipping warning",
+    "24": "red and white triangle with merging / narrow lanes warning",
+    "25": "red and white triangle with person digging / construction / road work warning",
+    "26": "red and white triangle with traffic light approaching warning",
+    "27": "red and white triangle with person walking warning",
+    "28": "red and white triangle with child and person walking warning",
+    "29": "red and white triangle with bicyle warning",
+    "30": "red and white triangle with snowflake / ice warning",
+    "31": "red and white triangle with deer warning",
+    "32": "white circle with gray strike bar no speed limit",
+    "33": "blue circle with white right turn arrow mandatory",
+    "34": "blue circle with white left turn arrow mandatory",
+    "35": "blue circle with white forward arrow mandatory",
+    "36": "blue circle with white forward or right turn arrow mandatory",
+    "37": "blue circle with white forward or left turn arrow mandatory",
+    "38": "blue circle with white keep right arrow mandatory",
+    "39": "blue circle with white keep left arrow mandatory",
+    "40": "blue circle with white arrows indicating a traffic circle",
+    "41": "white circle with gray strike bar indicating no passing for cars has ended",
+    "42": "white circle with gray strike bar indicating no passing for trucks has ended"
+  },
+  "label2id": {
+    "blue circle with white arrows indicating a traffic circle": 40,
+    "blue circle with white forward arrow mandatory": 35,
+    "blue circle with white forward or left turn arrow mandatory": 37,
+    "blue circle with white forward or right turn arrow mandatory": 36,
+    "blue circle with white keep left arrow mandatory": 39,
+    "blue circle with white keep right arrow mandatory": 38,
+    "blue circle with white left turn arrow mandatory": 34,
+    "blue circle with white right turn arrow mandatory": 33,
+    "empty red and white circle": 15,
+    "end / de-restriction of 80 kph speed limit": 6,
+    "red and white circle 100 kph speed limit": 7,
+    "red and white circle 120 kph speed limit": 8,
+    "red and white circle 20 kph speed limit": 0,
+    "red and white circle 30 kph speed limit": 1,
+    "red and white circle 50 kph speed limit": 2,
+    "red and white circle 60 kph speed limit": 3,
+    "red and white circle 70 kph speed limit": 4,
+    "red and white circle 80 kph speed limit": 5,
+    "red and white circle no truck entry": 16,
+    "red and white circle red car and black car no passing": 9,
+    "red and white circle red truck and black car no passing": 10,
+    "red and white triangle car skidding / slipping warning": 23,
+    "red and white triangle road intersection warning": 11,
+    "red and white triangle rough / bumpy road warning": 22,
+    "red and white triangle with bicyle warning": 29,
+    "red and white triangle with black double curve approaching warning": 21,
+    "red and white triangle with black left curve approaching warning": 19,
+    "red and white triangle with black right curve approaching warning": 20,
+    "red and white triangle with child and person walking warning": 28,
+    "red and white triangle with deer warning": 31,
+    "red and white triangle with exclamation mark warning": 18,
+    "red and white triangle with merging / narrow lanes warning": 24,
+    "red and white triangle with person digging / construction / road work warning": 25,
+    "red and white triangle with person walking warning": 27,
+    "red and white triangle with snowflake / ice warning": 30,
+    "red and white triangle with traffic light approaching warning": 26,
+    "red and white upside down triangle yield right-of-way": 13,
+    "red circle with white horizonal stripe no entry": 17,
+    "stop": 14,
+    "white and yellow diamond priority road": 12,
+    "white circle with gray strike bar indicating no passing for cars has ended": 41,
+    "white circle with gray strike bar indicating no passing for trucks has ended": 42,
+    "white circle with gray strike bar no speed limit": 32
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-gtsrb-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet50-gtsrb-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-gtsrb-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/README.md b/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..96ca5e83e39b87195509d8cee83a12c1143a830e
--- /dev/null
+++ b/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset gtsrb.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: gtsrb
+    pretrained: true
+test_datasets: null
+train_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: train
+type: transformers
+val_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: test
+```
+
diff --git a/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/config.json b/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..72e5aa2e6ca1e8845fcf4a68dc7cd82ec3c90ca4
--- /dev/null
+++ b/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,129 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "red and white circle 20 kph speed limit",
+    "1": "red and white circle 30 kph speed limit",
+    "2": "red and white circle 50 kph speed limit",
+    "3": "red and white circle 60 kph speed limit",
+    "4": "red and white circle 70 kph speed limit",
+    "5": "red and white circle 80 kph speed limit",
+    "6": "end / de-restriction of 80 kph speed limit",
+    "7": "red and white circle 100 kph speed limit",
+    "8": "red and white circle 120 kph speed limit",
+    "9": "red and white circle red car and black car no passing",
+    "10": "red and white circle red truck and black car no passing",
+    "11": "red and white triangle road intersection warning",
+    "12": "white and yellow diamond priority road",
+    "13": "red and white upside down triangle yield right-of-way",
+    "14": "stop",
+    "15": "empty red and white circle",
+    "16": "red and white circle no truck entry",
+    "17": "red circle with white horizonal stripe no entry",
+    "18": "red and white triangle with exclamation mark warning",
+    "19": "red and white triangle with black left curve approaching warning",
+    "20": "red and white triangle with black right curve approaching warning",
+    "21": "red and white triangle with black double curve approaching warning",
+    "22": "red and white triangle rough / bumpy road warning",
+    "23": "red and white triangle car skidding / slipping warning",
+    "24": "red and white triangle with merging / narrow lanes warning",
+    "25": "red and white triangle with person digging / construction / road work warning",
+    "26": "red and white triangle with traffic light approaching warning",
+    "27": "red and white triangle with person walking warning",
+    "28": "red and white triangle with child and person walking warning",
+    "29": "red and white triangle with bicyle warning",
+    "30": "red and white triangle with snowflake / ice warning",
+    "31": "red and white triangle with deer warning",
+    "32": "white circle with gray strike bar no speed limit",
+    "33": "blue circle with white right turn arrow mandatory",
+    "34": "blue circle with white left turn arrow mandatory",
+    "35": "blue circle with white forward arrow mandatory",
+    "36": "blue circle with white forward or right turn arrow mandatory",
+    "37": "blue circle with white forward or left turn arrow mandatory",
+    "38": "blue circle with white keep right arrow mandatory",
+    "39": "blue circle with white keep left arrow mandatory",
+    "40": "blue circle with white arrows indicating a traffic circle",
+    "41": "white circle with gray strike bar indicating no passing for cars has ended",
+    "42": "white circle with gray strike bar indicating no passing for trucks has ended"
+  },
+  "label2id": {
+    "blue circle with white arrows indicating a traffic circle": 40,
+    "blue circle with white forward arrow mandatory": 35,
+    "blue circle with white forward or left turn arrow mandatory": 37,
+    "blue circle with white forward or right turn arrow mandatory": 36,
+    "blue circle with white keep left arrow mandatory": 39,
+    "blue circle with white keep right arrow mandatory": 38,
+    "blue circle with white left turn arrow mandatory": 34,
+    "blue circle with white right turn arrow mandatory": 33,
+    "empty red and white circle": 15,
+    "end / de-restriction of 80 kph speed limit": 6,
+    "red and white circle 100 kph speed limit": 7,
+    "red and white circle 120 kph speed limit": 8,
+    "red and white circle 20 kph speed limit": 0,
+    "red and white circle 30 kph speed limit": 1,
+    "red and white circle 50 kph speed limit": 2,
+    "red and white circle 60 kph speed limit": 3,
+    "red and white circle 70 kph speed limit": 4,
+    "red and white circle 80 kph speed limit": 5,
+    "red and white circle no truck entry": 16,
+    "red and white circle red car and black car no passing": 9,
+    "red and white circle red truck and black car no passing": 10,
+    "red and white triangle car skidding / slipping warning": 23,
+    "red and white triangle road intersection warning": 11,
+    "red and white triangle rough / bumpy road warning": 22,
+    "red and white triangle with bicyle warning": 29,
+    "red and white triangle with black double curve approaching warning": 21,
+    "red and white triangle with black left curve approaching warning": 19,
+    "red and white triangle with black right curve approaching warning": 20,
+    "red and white triangle with child and person walking warning": 28,
+    "red and white triangle with deer warning": 31,
+    "red and white triangle with exclamation mark warning": 18,
+    "red and white triangle with merging / narrow lanes warning": 24,
+    "red and white triangle with person digging / construction / road work warning": 25,
+    "red and white triangle with person walking warning": 27,
+    "red and white triangle with snowflake / ice warning": 30,
+    "red and white triangle with traffic light approaching warning": 26,
+    "red and white upside down triangle yield right-of-way": 13,
+    "red circle with white horizonal stripe no entry": 17,
+    "stop": 14,
+    "white and yellow diamond priority road": 12,
+    "white circle with gray strike bar indicating no passing for cars has ended": 41,
+    "white circle with gray strike bar indicating no passing for trucks has ended": 42,
+    "white circle with gray strike bar no speed limit": 32
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/README.md b/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..96ca5e83e39b87195509d8cee83a12c1143a830e
--- /dev/null
+++ b/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset gtsrb.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: gtsrb
+    pretrained: true
+test_datasets: null
+train_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: train
+type: transformers
+val_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: test
+```
+
diff --git a/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/config.json b/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..72e5aa2e6ca1e8845fcf4a68dc7cd82ec3c90ca4
--- /dev/null
+++ b/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,129 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "red and white circle 20 kph speed limit",
+    "1": "red and white circle 30 kph speed limit",
+    "2": "red and white circle 50 kph speed limit",
+    "3": "red and white circle 60 kph speed limit",
+    "4": "red and white circle 70 kph speed limit",
+    "5": "red and white circle 80 kph speed limit",
+    "6": "end / de-restriction of 80 kph speed limit",
+    "7": "red and white circle 100 kph speed limit",
+    "8": "red and white circle 120 kph speed limit",
+    "9": "red and white circle red car and black car no passing",
+    "10": "red and white circle red truck and black car no passing",
+    "11": "red and white triangle road intersection warning",
+    "12": "white and yellow diamond priority road",
+    "13": "red and white upside down triangle yield right-of-way",
+    "14": "stop",
+    "15": "empty red and white circle",
+    "16": "red and white circle no truck entry",
+    "17": "red circle with white horizonal stripe no entry",
+    "18": "red and white triangle with exclamation mark warning",
+    "19": "red and white triangle with black left curve approaching warning",
+    "20": "red and white triangle with black right curve approaching warning",
+    "21": "red and white triangle with black double curve approaching warning",
+    "22": "red and white triangle rough / bumpy road warning",
+    "23": "red and white triangle car skidding / slipping warning",
+    "24": "red and white triangle with merging / narrow lanes warning",
+    "25": "red and white triangle with person digging / construction / road work warning",
+    "26": "red and white triangle with traffic light approaching warning",
+    "27": "red and white triangle with person walking warning",
+    "28": "red and white triangle with child and person walking warning",
+    "29": "red and white triangle with bicyle warning",
+    "30": "red and white triangle with snowflake / ice warning",
+    "31": "red and white triangle with deer warning",
+    "32": "white circle with gray strike bar no speed limit",
+    "33": "blue circle with white right turn arrow mandatory",
+    "34": "blue circle with white left turn arrow mandatory",
+    "35": "blue circle with white forward arrow mandatory",
+    "36": "blue circle with white forward or right turn arrow mandatory",
+    "37": "blue circle with white forward or left turn arrow mandatory",
+    "38": "blue circle with white keep right arrow mandatory",
+    "39": "blue circle with white keep left arrow mandatory",
+    "40": "blue circle with white arrows indicating a traffic circle",
+    "41": "white circle with gray strike bar indicating no passing for cars has ended",
+    "42": "white circle with gray strike bar indicating no passing for trucks has ended"
+  },
+  "label2id": {
+    "blue circle with white arrows indicating a traffic circle": 40,
+    "blue circle with white forward arrow mandatory": 35,
+    "blue circle with white forward or left turn arrow mandatory": 37,
+    "blue circle with white forward or right turn arrow mandatory": 36,
+    "blue circle with white keep left arrow mandatory": 39,
+    "blue circle with white keep right arrow mandatory": 38,
+    "blue circle with white left turn arrow mandatory": 34,
+    "blue circle with white right turn arrow mandatory": 33,
+    "empty red and white circle": 15,
+    "end / de-restriction of 80 kph speed limit": 6,
+    "red and white circle 100 kph speed limit": 7,
+    "red and white circle 120 kph speed limit": 8,
+    "red and white circle 20 kph speed limit": 0,
+    "red and white circle 30 kph speed limit": 1,
+    "red and white circle 50 kph speed limit": 2,
+    "red and white circle 60 kph speed limit": 3,
+    "red and white circle 70 kph speed limit": 4,
+    "red and white circle 80 kph speed limit": 5,
+    "red and white circle no truck entry": 16,
+    "red and white circle red car and black car no passing": 9,
+    "red and white circle red truck and black car no passing": 10,
+    "red and white triangle car skidding / slipping warning": 23,
+    "red and white triangle road intersection warning": 11,
+    "red and white triangle rough / bumpy road warning": 22,
+    "red and white triangle with bicyle warning": 29,
+    "red and white triangle with black double curve approaching warning": 21,
+    "red and white triangle with black left curve approaching warning": 19,
+    "red and white triangle with black right curve approaching warning": 20,
+    "red and white triangle with child and person walking warning": 28,
+    "red and white triangle with deer warning": 31,
+    "red and white triangle with exclamation mark warning": 18,
+    "red and white triangle with merging / narrow lanes warning": 24,
+    "red and white triangle with person digging / construction / road work warning": 25,
+    "red and white triangle with person walking warning": 27,
+    "red and white triangle with snowflake / ice warning": 30,
+    "red and white triangle with traffic light approaching warning": 26,
+    "red and white upside down triangle yield right-of-way": 13,
+    "red circle with white horizonal stripe no entry": 17,
+    "stop": 14,
+    "white and yellow diamond priority road": 12,
+    "white circle with gray strike bar indicating no passing for cars has ended": 41,
+    "white circle with gray strike bar indicating no passing for trucks has ended": 42,
+    "white circle with gray strike bar no speed limit": 32
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/README.md b/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..be2c3616c24dea7b57f92493e3ce5dbbbe50d867
--- /dev/null
+++ b/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset gtsrb.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: gtsrb
+    pretrained: true
+test_datasets: null
+train_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: train
+type: transformers
+val_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: test
+```
+
diff --git a/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/config.json b/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..72e5aa2e6ca1e8845fcf4a68dc7cd82ec3c90ca4
--- /dev/null
+++ b/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,129 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "red and white circle 20 kph speed limit",
+    "1": "red and white circle 30 kph speed limit",
+    "2": "red and white circle 50 kph speed limit",
+    "3": "red and white circle 60 kph speed limit",
+    "4": "red and white circle 70 kph speed limit",
+    "5": "red and white circle 80 kph speed limit",
+    "6": "end / de-restriction of 80 kph speed limit",
+    "7": "red and white circle 100 kph speed limit",
+    "8": "red and white circle 120 kph speed limit",
+    "9": "red and white circle red car and black car no passing",
+    "10": "red and white circle red truck and black car no passing",
+    "11": "red and white triangle road intersection warning",
+    "12": "white and yellow diamond priority road",
+    "13": "red and white upside down triangle yield right-of-way",
+    "14": "stop",
+    "15": "empty red and white circle",
+    "16": "red and white circle no truck entry",
+    "17": "red circle with white horizonal stripe no entry",
+    "18": "red and white triangle with exclamation mark warning",
+    "19": "red and white triangle with black left curve approaching warning",
+    "20": "red and white triangle with black right curve approaching warning",
+    "21": "red and white triangle with black double curve approaching warning",
+    "22": "red and white triangle rough / bumpy road warning",
+    "23": "red and white triangle car skidding / slipping warning",
+    "24": "red and white triangle with merging / narrow lanes warning",
+    "25": "red and white triangle with person digging / construction / road work warning",
+    "26": "red and white triangle with traffic light approaching warning",
+    "27": "red and white triangle with person walking warning",
+    "28": "red and white triangle with child and person walking warning",
+    "29": "red and white triangle with bicyle warning",
+    "30": "red and white triangle with snowflake / ice warning",
+    "31": "red and white triangle with deer warning",
+    "32": "white circle with gray strike bar no speed limit",
+    "33": "blue circle with white right turn arrow mandatory",
+    "34": "blue circle with white left turn arrow mandatory",
+    "35": "blue circle with white forward arrow mandatory",
+    "36": "blue circle with white forward or right turn arrow mandatory",
+    "37": "blue circle with white forward or left turn arrow mandatory",
+    "38": "blue circle with white keep right arrow mandatory",
+    "39": "blue circle with white keep left arrow mandatory",
+    "40": "blue circle with white arrows indicating a traffic circle",
+    "41": "white circle with gray strike bar indicating no passing for cars has ended",
+    "42": "white circle with gray strike bar indicating no passing for trucks has ended"
+  },
+  "label2id": {
+    "blue circle with white arrows indicating a traffic circle": 40,
+    "blue circle with white forward arrow mandatory": 35,
+    "blue circle with white forward or left turn arrow mandatory": 37,
+    "blue circle with white forward or right turn arrow mandatory": 36,
+    "blue circle with white keep left arrow mandatory": 39,
+    "blue circle with white keep right arrow mandatory": 38,
+    "blue circle with white left turn arrow mandatory": 34,
+    "blue circle with white right turn arrow mandatory": 33,
+    "empty red and white circle": 15,
+    "end / de-restriction of 80 kph speed limit": 6,
+    "red and white circle 100 kph speed limit": 7,
+    "red and white circle 120 kph speed limit": 8,
+    "red and white circle 20 kph speed limit": 0,
+    "red and white circle 30 kph speed limit": 1,
+    "red and white circle 50 kph speed limit": 2,
+    "red and white circle 60 kph speed limit": 3,
+    "red and white circle 70 kph speed limit": 4,
+    "red and white circle 80 kph speed limit": 5,
+    "red and white circle no truck entry": 16,
+    "red and white circle red car and black car no passing": 9,
+    "red and white circle red truck and black car no passing": 10,
+    "red and white triangle car skidding / slipping warning": 23,
+    "red and white triangle road intersection warning": 11,
+    "red and white triangle rough / bumpy road warning": 22,
+    "red and white triangle with bicyle warning": 29,
+    "red and white triangle with black double curve approaching warning": 21,
+    "red and white triangle with black left curve approaching warning": 19,
+    "red and white triangle with black right curve approaching warning": 20,
+    "red and white triangle with child and person walking warning": 28,
+    "red and white triangle with deer warning": 31,
+    "red and white triangle with exclamation mark warning": 18,
+    "red and white triangle with merging / narrow lanes warning": 24,
+    "red and white triangle with person digging / construction / road work warning": 25,
+    "red and white triangle with person walking warning": 27,
+    "red and white triangle with snowflake / ice warning": 30,
+    "red and white triangle with traffic light approaching warning": 26,
+    "red and white upside down triangle yield right-of-way": 13,
+    "red circle with white horizonal stripe no entry": 17,
+    "stop": 14,
+    "white and yellow diamond priority road": 12,
+    "white circle with gray strike bar indicating no passing for cars has ended": 41,
+    "white circle with gray strike bar indicating no passing for trucks has ended": 42,
+    "white circle with gray strike bar no speed limit": 32
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/README.md b/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..be2c3616c24dea7b57f92493e3ce5dbbbe50d867
--- /dev/null
+++ b/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset gtsrb.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: gtsrb
+    pretrained: true
+test_datasets: null
+train_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: train
+type: transformers
+val_datasets:
+  gtsrb:
+    _target_: datasets.load_dataset
+    path: tanganke/gtsrb
+    split: test
+```
+
diff --git a/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/config.json b/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..72e5aa2e6ca1e8845fcf4a68dc7cd82ec3c90ca4
--- /dev/null
+++ b/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,129 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "red and white circle 20 kph speed limit",
+    "1": "red and white circle 30 kph speed limit",
+    "2": "red and white circle 50 kph speed limit",
+    "3": "red and white circle 60 kph speed limit",
+    "4": "red and white circle 70 kph speed limit",
+    "5": "red and white circle 80 kph speed limit",
+    "6": "end / de-restriction of 80 kph speed limit",
+    "7": "red and white circle 100 kph speed limit",
+    "8": "red and white circle 120 kph speed limit",
+    "9": "red and white circle red car and black car no passing",
+    "10": "red and white circle red truck and black car no passing",
+    "11": "red and white triangle road intersection warning",
+    "12": "white and yellow diamond priority road",
+    "13": "red and white upside down triangle yield right-of-way",
+    "14": "stop",
+    "15": "empty red and white circle",
+    "16": "red and white circle no truck entry",
+    "17": "red circle with white horizonal stripe no entry",
+    "18": "red and white triangle with exclamation mark warning",
+    "19": "red and white triangle with black left curve approaching warning",
+    "20": "red and white triangle with black right curve approaching warning",
+    "21": "red and white triangle with black double curve approaching warning",
+    "22": "red and white triangle rough / bumpy road warning",
+    "23": "red and white triangle car skidding / slipping warning",
+    "24": "red and white triangle with merging / narrow lanes warning",
+    "25": "red and white triangle with person digging / construction / road work warning",
+    "26": "red and white triangle with traffic light approaching warning",
+    "27": "red and white triangle with person walking warning",
+    "28": "red and white triangle with child and person walking warning",
+    "29": "red and white triangle with bicyle warning",
+    "30": "red and white triangle with snowflake / ice warning",
+    "31": "red and white triangle with deer warning",
+    "32": "white circle with gray strike bar no speed limit",
+    "33": "blue circle with white right turn arrow mandatory",
+    "34": "blue circle with white left turn arrow mandatory",
+    "35": "blue circle with white forward arrow mandatory",
+    "36": "blue circle with white forward or right turn arrow mandatory",
+    "37": "blue circle with white forward or left turn arrow mandatory",
+    "38": "blue circle with white keep right arrow mandatory",
+    "39": "blue circle with white keep left arrow mandatory",
+    "40": "blue circle with white arrows indicating a traffic circle",
+    "41": "white circle with gray strike bar indicating no passing for cars has ended",
+    "42": "white circle with gray strike bar indicating no passing for trucks has ended"
+  },
+  "label2id": {
+    "blue circle with white arrows indicating a traffic circle": 40,
+    "blue circle with white forward arrow mandatory": 35,
+    "blue circle with white forward or left turn arrow mandatory": 37,
+    "blue circle with white forward or right turn arrow mandatory": 36,
+    "blue circle with white keep left arrow mandatory": 39,
+    "blue circle with white keep right arrow mandatory": 38,
+    "blue circle with white left turn arrow mandatory": 34,
+    "blue circle with white right turn arrow mandatory": 33,
+    "empty red and white circle": 15,
+    "end / de-restriction of 80 kph speed limit": 6,
+    "red and white circle 100 kph speed limit": 7,
+    "red and white circle 120 kph speed limit": 8,
+    "red and white circle 20 kph speed limit": 0,
+    "red and white circle 30 kph speed limit": 1,
+    "red and white circle 50 kph speed limit": 2,
+    "red and white circle 60 kph speed limit": 3,
+    "red and white circle 70 kph speed limit": 4,
+    "red and white circle 80 kph speed limit": 5,
+    "red and white circle no truck entry": 16,
+    "red and white circle red car and black car no passing": 9,
+    "red and white circle red truck and black car no passing": 10,
+    "red and white triangle car skidding / slipping warning": 23,
+    "red and white triangle road intersection warning": 11,
+    "red and white triangle rough / bumpy road warning": 22,
+    "red and white triangle with bicyle warning": 29,
+    "red and white triangle with black double curve approaching warning": 21,
+    "red and white triangle with black left curve approaching warning": 19,
+    "red and white triangle with black right curve approaching warning": 20,
+    "red and white triangle with child and person walking warning": 28,
+    "red and white triangle with deer warning": 31,
+    "red and white triangle with exclamation mark warning": 18,
+    "red and white triangle with merging / narrow lanes warning": 24,
+    "red and white triangle with person digging / construction / road work warning": 25,
+    "red and white triangle with person walking warning": 27,
+    "red and white triangle with snowflake / ice warning": 30,
+    "red and white triangle with traffic light approaching warning": 26,
+    "red and white upside down triangle yield right-of-way": 13,
+    "red circle with white horizonal stripe no entry": 17,
+    "stop": 14,
+    "white and yellow diamond priority road": 12,
+    "white circle with gray strike bar indicating no passing for cars has ended": 41,
+    "white circle with gray strike bar indicating no passing for trucks has ended": 42,
+    "white circle with gray strike bar no speed limit": 32
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-kmnist-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/README.md b/resnet50-kmnist-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..61795938e138d120309cd9854cc223c36ea22bbc
--- /dev/null
+++ b/resnet50-kmnist-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset kmnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: kmnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: train
+type: transformers
+val_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: test
+```
+
diff --git a/resnet50-kmnist-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/config.json b/resnet50-kmnist-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..7cb9e38ace4738e265b487d7c814cd0f7cdbeae1
--- /dev/null
+++ b/resnet50-kmnist-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "\u304a",
+    "1": "\u304d",
+    "2": "\u3059",
+    "3": "\u3064",
+    "4": "\u306a",
+    "5": "\u306f",
+    "6": "\u307e",
+    "7": "\u3084",
+    "8": "\u308c",
+    "9": "\u3092"
+  },
+  "label2id": {
+    "\u304a": 0,
+    "\u304d": 1,
+    "\u3059": 2,
+    "\u3064": 3,
+    "\u306a": 4,
+    "\u306f": 5,
+    "\u307e": 6,
+    "\u3084": 7,
+    "\u308c": 8,
+    "\u3092": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-kmnist-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet50-kmnist-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-kmnist-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-kmnist-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/README.md b/resnet50-kmnist-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..d54bb175dc6ba657485e2d66692d5715a04fbf3e
--- /dev/null
+++ b/resnet50-kmnist-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset kmnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: kmnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: train
+type: transformers
+val_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: test
+```
+
diff --git a/resnet50-kmnist-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/config.json b/resnet50-kmnist-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..7cb9e38ace4738e265b487d7c814cd0f7cdbeae1
--- /dev/null
+++ b/resnet50-kmnist-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "\u304a",
+    "1": "\u304d",
+    "2": "\u3059",
+    "3": "\u3064",
+    "4": "\u306a",
+    "5": "\u306f",
+    "6": "\u307e",
+    "7": "\u3084",
+    "8": "\u308c",
+    "9": "\u3092"
+  },
+  "label2id": {
+    "\u304a": 0,
+    "\u304d": 1,
+    "\u3059": 2,
+    "\u3064": 3,
+    "\u306a": 4,
+    "\u306f": 5,
+    "\u307e": 6,
+    "\u3084": 7,
+    "\u308c": 8,
+    "\u3092": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-kmnist-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet50-kmnist-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-kmnist-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-kmnist-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/README.md b/resnet50-kmnist-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..abba662edb67ef51b9191f45420947288d101fe2
--- /dev/null
+++ b/resnet50-kmnist-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset kmnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: kmnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: train
+type: transformers
+val_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: test
+```
+
diff --git a/resnet50-kmnist-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/config.json b/resnet50-kmnist-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..7cb9e38ace4738e265b487d7c814cd0f7cdbeae1
--- /dev/null
+++ b/resnet50-kmnist-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "\u304a",
+    "1": "\u304d",
+    "2": "\u3059",
+    "3": "\u3064",
+    "4": "\u306a",
+    "5": "\u306f",
+    "6": "\u307e",
+    "7": "\u3084",
+    "8": "\u308c",
+    "9": "\u3092"
+  },
+  "label2id": {
+    "\u304a": 0,
+    "\u304d": 1,
+    "\u3059": 2,
+    "\u3064": 3,
+    "\u306a": 4,
+    "\u306f": 5,
+    "\u307e": 6,
+    "\u3084": 7,
+    "\u308c": 8,
+    "\u3092": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-kmnist-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet50-kmnist-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-kmnist-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-kmnist-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/README.md b/resnet50-kmnist-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..61ab6d70e77853299d65c3d7471f23ee8c88a49d
--- /dev/null
+++ b/resnet50-kmnist-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset kmnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: kmnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: train
+type: transformers
+val_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: test
+```
+
diff --git a/resnet50-kmnist-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/config.json b/resnet50-kmnist-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..7cb9e38ace4738e265b487d7c814cd0f7cdbeae1
--- /dev/null
+++ b/resnet50-kmnist-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "\u304a",
+    "1": "\u304d",
+    "2": "\u3059",
+    "3": "\u3064",
+    "4": "\u306a",
+    "5": "\u306f",
+    "6": "\u307e",
+    "7": "\u3084",
+    "8": "\u308c",
+    "9": "\u3092"
+  },
+  "label2id": {
+    "\u304a": 0,
+    "\u304d": 1,
+    "\u3059": 2,
+    "\u3064": 3,
+    "\u306a": 4,
+    "\u306f": 5,
+    "\u307e": 6,
+    "\u3084": 7,
+    "\u308c": 8,
+    "\u3092": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-kmnist-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet50-kmnist-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-kmnist-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/README.md b/resnet50-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..b1853de0ebf784254ee50b9cf6c478062e5701c8
--- /dev/null
+++ b/resnet50-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset kmnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: kmnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: train
+type: transformers
+val_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: test
+```
+
diff --git a/resnet50-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/config.json b/resnet50-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..7cb9e38ace4738e265b487d7c814cd0f7cdbeae1
--- /dev/null
+++ b/resnet50-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "\u304a",
+    "1": "\u304d",
+    "2": "\u3059",
+    "3": "\u3064",
+    "4": "\u306a",
+    "5": "\u306f",
+    "6": "\u307e",
+    "7": "\u3084",
+    "8": "\u308c",
+    "9": "\u3092"
+  },
+  "label2id": {
+    "\u304a": 0,
+    "\u304d": 1,
+    "\u3059": 2,
+    "\u3064": 3,
+    "\u306a": 4,
+    "\u306f": 5,
+    "\u307e": 6,
+    "\u3084": 7,
+    "\u308c": 8,
+    "\u3092": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet50-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-kmnist-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/README.md b/resnet50-kmnist-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..bacf4cf0d3b457e292062eae24e5695919610685
--- /dev/null
+++ b/resnet50-kmnist-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset kmnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: kmnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: train
+type: transformers
+val_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: test
+```
+
diff --git a/resnet50-kmnist-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/config.json b/resnet50-kmnist-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..7cb9e38ace4738e265b487d7c814cd0f7cdbeae1
--- /dev/null
+++ b/resnet50-kmnist-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "\u304a",
+    "1": "\u304d",
+    "2": "\u3059",
+    "3": "\u3064",
+    "4": "\u306a",
+    "5": "\u306f",
+    "6": "\u307e",
+    "7": "\u3084",
+    "8": "\u308c",
+    "9": "\u3092"
+  },
+  "label2id": {
+    "\u304a": 0,
+    "\u304d": 1,
+    "\u3059": 2,
+    "\u3064": 3,
+    "\u306a": 4,
+    "\u306f": 5,
+    "\u307e": 6,
+    "\u3084": 7,
+    "\u308c": 8,
+    "\u3092": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-kmnist-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet50-kmnist-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-kmnist-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-kmnist-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/README.md b/resnet50-kmnist-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..76193e95ac475e686e44057e85bd797fbc69e559
--- /dev/null
+++ b/resnet50-kmnist-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset kmnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: kmnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: train
+type: transformers
+val_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: test
+```
+
diff --git a/resnet50-kmnist-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/config.json b/resnet50-kmnist-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..7cb9e38ace4738e265b487d7c814cd0f7cdbeae1
--- /dev/null
+++ b/resnet50-kmnist-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "\u304a",
+    "1": "\u304d",
+    "2": "\u3059",
+    "3": "\u3064",
+    "4": "\u306a",
+    "5": "\u306f",
+    "6": "\u307e",
+    "7": "\u3084",
+    "8": "\u308c",
+    "9": "\u3092"
+  },
+  "label2id": {
+    "\u304a": 0,
+    "\u304d": 1,
+    "\u3059": 2,
+    "\u3064": 3,
+    "\u306a": 4,
+    "\u306f": 5,
+    "\u307e": 6,
+    "\u3084": 7,
+    "\u308c": 8,
+    "\u3092": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-kmnist-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet50-kmnist-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-kmnist-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-kmnist-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/README.md b/resnet50-kmnist-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..24a0e447d972d67dd99738d71dcab92d84ad27c4
--- /dev/null
+++ b/resnet50-kmnist-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset kmnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: kmnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: train
+type: transformers
+val_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: test
+```
+
diff --git a/resnet50-kmnist-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/config.json b/resnet50-kmnist-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..7cb9e38ace4738e265b487d7c814cd0f7cdbeae1
--- /dev/null
+++ b/resnet50-kmnist-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "\u304a",
+    "1": "\u304d",
+    "2": "\u3059",
+    "3": "\u3064",
+    "4": "\u306a",
+    "5": "\u306f",
+    "6": "\u307e",
+    "7": "\u3084",
+    "8": "\u308c",
+    "9": "\u3092"
+  },
+  "label2id": {
+    "\u304a": 0,
+    "\u304d": 1,
+    "\u3059": 2,
+    "\u3064": 3,
+    "\u306a": 4,
+    "\u306f": 5,
+    "\u307e": 6,
+    "\u3084": 7,
+    "\u308c": 8,
+    "\u3092": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-kmnist-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet50-kmnist-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-kmnist-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-kmnist-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/README.md b/resnet50-kmnist-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..02ec8026cd6322864534da3a06142a8a0d77f32c
--- /dev/null
+++ b/resnet50-kmnist-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset kmnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: kmnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: train
+type: transformers
+val_datasets:
+  kmnist:
+    _target_: datasets.load_dataset
+    path: tanganke/kmnist
+    split: test
+```
+
diff --git a/resnet50-kmnist-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/config.json b/resnet50-kmnist-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..7cb9e38ace4738e265b487d7c814cd0f7cdbeae1
--- /dev/null
+++ b/resnet50-kmnist-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "\u304a",
+    "1": "\u304d",
+    "2": "\u3059",
+    "3": "\u3064",
+    "4": "\u306a",
+    "5": "\u306f",
+    "6": "\u307e",
+    "7": "\u3084",
+    "8": "\u308c",
+    "9": "\u3092"
+  },
+  "label2id": {
+    "\u304a": 0,
+    "\u304d": 1,
+    "\u3059": 2,
+    "\u3064": 3,
+    "\u306a": 4,
+    "\u306f": 5,
+    "\u307e": 6,
+    "\u3084": 7,
+    "\u308c": 8,
+    "\u3092": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-kmnist-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet50-kmnist-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-kmnist-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/README.md b/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..3512c1ab0e6146788cec370d35cc2112ccc889ac
--- /dev/null
+++ b/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: train
+type: transformers
+val_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: test
+```
+
diff --git a/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/config.json b/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1edcdd247f31547feb0c0bebd29bf1cd24a4532f
--- /dev/null
+++ b/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/README.md b/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..03ae5b566d7b5af780a0fb163c7a862c9d739bf9
--- /dev/null
+++ b/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: train
+type: transformers
+val_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: test
+```
+
diff --git a/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/config.json b/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1edcdd247f31547feb0c0bebd29bf1cd24a4532f
--- /dev/null
+++ b/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/README.md b/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..4a1913ab98f277d0329c2806f61dcdcecf9ff238
--- /dev/null
+++ b/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: train
+type: transformers
+val_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: test
+```
+
diff --git a/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/config.json b/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1edcdd247f31547feb0c0bebd29bf1cd24a4532f
--- /dev/null
+++ b/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/README.md b/resnet50-mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..83a7d6b96d67ea57920612c1642a7748e093dad3
--- /dev/null
+++ b/resnet50-mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: train
+type: transformers
+val_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: test
+```
+
diff --git a/resnet50-mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/config.json b/resnet50-mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1edcdd247f31547feb0c0bebd29bf1cd24a4532f
--- /dev/null
+++ b/resnet50-mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet50-mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-mnist-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/README.md b/resnet50-mnist-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..44fac79fa3eef1fd60d4454671f22a055758abcb
--- /dev/null
+++ b/resnet50-mnist-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: train
+type: transformers
+val_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: test
+```
+
diff --git a/resnet50-mnist-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/config.json b/resnet50-mnist-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1edcdd247f31547feb0c0bebd29bf1cd24a4532f
--- /dev/null
+++ b/resnet50-mnist-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-mnist-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet50-mnist-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-mnist-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/README.md b/resnet50-mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..b735a5016afa010fcd878114134444d55e7de1a9
--- /dev/null
+++ b/resnet50-mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: train
+type: transformers
+val_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: test
+```
+
diff --git a/resnet50-mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/config.json b/resnet50-mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1edcdd247f31547feb0c0bebd29bf1cd24a4532f
--- /dev/null
+++ b/resnet50-mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet50-mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-mnist-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/README.md b/resnet50-mnist-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..73ac6c72390cb309ad5d9676f670a5c184a986e5
--- /dev/null
+++ b/resnet50-mnist-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: train
+type: transformers
+val_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: test
+```
+
diff --git a/resnet50-mnist-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/config.json b/resnet50-mnist-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1edcdd247f31547feb0c0bebd29bf1cd24a4532f
--- /dev/null
+++ b/resnet50-mnist-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-mnist-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet50-mnist-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-mnist-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-mnist-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/README.md b/resnet50-mnist-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..0ea52e2b16c56e99bfbfc8683462869e37d7fa87
--- /dev/null
+++ b/resnet50-mnist-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: train
+type: transformers
+val_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: test
+```
+
diff --git a/resnet50-mnist-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/config.json b/resnet50-mnist-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1edcdd247f31547feb0c0bebd29bf1cd24a4532f
--- /dev/null
+++ b/resnet50-mnist-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-mnist-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet50-mnist-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-mnist-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/README.md b/resnet50-mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e40961c52501862b7176b308ca89acc8d396a3b9
--- /dev/null
+++ b/resnet50-mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: train
+type: transformers
+val_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: test
+```
+
diff --git a/resnet50-mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/config.json b/resnet50-mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1edcdd247f31547feb0c0bebd29bf1cd24a4532f
--- /dev/null
+++ b/resnet50-mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet50-mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-mnist-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/README.md b/resnet50-mnist-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..424d4e80fd8875ac26a18772c99a88eaa9ed79ba
--- /dev/null
+++ b/resnet50-mnist-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset mnist.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: mnist
+    pretrained: true
+test_datasets: null
+train_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: train
+type: transformers
+val_datasets:
+  mnist:
+    _target_: datasets.load_dataset
+    path: mnist
+    split: test
+```
+
diff --git a/resnet50-mnist-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/config.json b/resnet50-mnist-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1edcdd247f31547feb0c0bebd29bf1cd24a4532f
--- /dev/null
+++ b/resnet50-mnist-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-mnist-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet50-mnist-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-mnist-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-oxford-iiit-pet-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/README.md b/resnet50-oxford-iiit-pet-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..c58bcd3f5dc7fc500a86d0670808a8bb9907f1d2
--- /dev/null
+++ b/resnet50-oxford-iiit-pet-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford-iiit-pet.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: oxford-iiit-pet
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford-iiit-pet:
+    _target_: datasets.load_dataset
+    path: timm/oxford-iiit-pet
+    split: train
+type: transformers
+val_datasets:
+  oxford-iiit-pet:
+    _target_: datasets.load_dataset
+    path: timm/oxford-iiit-pet
+    split: test
+```
+
diff --git a/resnet50-oxford-iiit-pet-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/config.json b/resnet50-oxford-iiit-pet-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..70c303978f48704b0d2ed76247d55f7c0a3fe6b2
--- /dev/null
+++ b/resnet50-oxford-iiit-pet-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,117 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "abyssinian",
+    "1": "american_bulldog",
+    "2": "american_pit_bull_terrier",
+    "3": "basset_hound",
+    "4": "beagle",
+    "5": "bengal",
+    "6": "birman",
+    "7": "bombay",
+    "8": "boxer",
+    "9": "british_shorthair",
+    "10": "chihuahua",
+    "11": "egyptian_mau",
+    "12": "english_cocker_spaniel",
+    "13": "english_setter",
+    "14": "german_shorthaired",
+    "15": "great_pyrenees",
+    "16": "havanese",
+    "17": "japanese_chin",
+    "18": "keeshond",
+    "19": "leonberger",
+    "20": "maine_coon",
+    "21": "miniature_pinscher",
+    "22": "newfoundland",
+    "23": "persian",
+    "24": "pomeranian",
+    "25": "pug",
+    "26": "ragdoll",
+    "27": "russian_blue",
+    "28": "saint_bernard",
+    "29": "samoyed",
+    "30": "scottish_terrier",
+    "31": "shiba_inu",
+    "32": "siamese",
+    "33": "sphynx",
+    "34": "staffordshire_bull_terrier",
+    "35": "wheaten_terrier",
+    "36": "yorkshire_terrier"
+  },
+  "label2id": {
+    "abyssinian": 0,
+    "american_bulldog": 1,
+    "american_pit_bull_terrier": 2,
+    "basset_hound": 3,
+    "beagle": 4,
+    "bengal": 5,
+    "birman": 6,
+    "bombay": 7,
+    "boxer": 8,
+    "british_shorthair": 9,
+    "chihuahua": 10,
+    "egyptian_mau": 11,
+    "english_cocker_spaniel": 12,
+    "english_setter": 13,
+    "german_shorthaired": 14,
+    "great_pyrenees": 15,
+    "havanese": 16,
+    "japanese_chin": 17,
+    "keeshond": 18,
+    "leonberger": 19,
+    "maine_coon": 20,
+    "miniature_pinscher": 21,
+    "newfoundland": 22,
+    "persian": 23,
+    "pomeranian": 24,
+    "pug": 25,
+    "ragdoll": 26,
+    "russian_blue": 27,
+    "saint_bernard": 28,
+    "samoyed": 29,
+    "scottish_terrier": 30,
+    "shiba_inu": 31,
+    "siamese": 32,
+    "sphynx": 33,
+    "staffordshire_bull_terrier": 34,
+    "wheaten_terrier": 35,
+    "yorkshire_terrier": 36
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-oxford-iiit-pet-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet50-oxford-iiit-pet-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-oxford-iiit-pet-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/README.md b/resnet50-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..f2ad1a325c8f9db2eb242fd5a7850f5003fdcc14
--- /dev/null
+++ b/resnet50-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford_flowers102.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: oxford_flowers102
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: train
+type: transformers
+val_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: test
+```
+
diff --git a/resnet50-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/config.json b/resnet50-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..ee05e378f6d60c8217f7b8db60be10c17bce37e2
--- /dev/null
+++ b/resnet50-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,247 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "pink primrose",
+    "1": "hard-leaved pocket orchid",
+    "2": "canterbury bells",
+    "3": "sweet pea",
+    "4": "english marigold",
+    "5": "tiger lily",
+    "6": "moon orchid",
+    "7": "bird of paradise",
+    "8": "monkshood",
+    "9": "globe thistle",
+    "10": "snapdragon",
+    "11": "colt's foot",
+    "12": "king protea",
+    "13": "spear thistle",
+    "14": "yellow iris",
+    "15": "globe-flower",
+    "16": "purple coneflower",
+    "17": "peruvian lily",
+    "18": "balloon flower",
+    "19": "giant white arum lily",
+    "20": "fire lily",
+    "21": "pincushion flower",
+    "22": "fritillary",
+    "23": "red ginger",
+    "24": "grape hyacinth",
+    "25": "corn poppy",
+    "26": "prince of wales feathers",
+    "27": "stemless gentian",
+    "28": "artichoke",
+    "29": "sweet william",
+    "30": "carnation",
+    "31": "garden phlox",
+    "32": "love in the mist",
+    "33": "mexican aster",
+    "34": "alpine sea holly",
+    "35": "ruby-lipped cattleya",
+    "36": "cape flower",
+    "37": "great masterwort",
+    "38": "siam tulip",
+    "39": "lenten rose",
+    "40": "barbeton daisy",
+    "41": "daffodil",
+    "42": "sword lily",
+    "43": "poinsettia",
+    "44": "bolero deep blue",
+    "45": "wallflower",
+    "46": "marigold",
+    "47": "buttercup",
+    "48": "oxeye daisy",
+    "49": "common dandelion",
+    "50": "petunia",
+    "51": "wild pansy",
+    "52": "primula",
+    "53": "sunflower",
+    "54": "pelargonium",
+    "55": "bishop of llandaff",
+    "56": "gaura",
+    "57": "geranium",
+    "58": "orange dahlia",
+    "59": "pink-yellow dahlia?",
+    "60": "cautleya spicata",
+    "61": "japanese anemone",
+    "62": "black-eyed susan",
+    "63": "silverbush",
+    "64": "californian poppy",
+    "65": "osteospermum",
+    "66": "spring crocus",
+    "67": "bearded iris",
+    "68": "windflower",
+    "69": "tree poppy",
+    "70": "gazania",
+    "71": "azalea",
+    "72": "water lily",
+    "73": "rose",
+    "74": "thorn apple",
+    "75": "morning glory",
+    "76": "passion flower",
+    "77": "lotus",
+    "78": "toad lily",
+    "79": "anthurium",
+    "80": "frangipani",
+    "81": "clematis",
+    "82": "hibiscus",
+    "83": "columbine",
+    "84": "desert-rose",
+    "85": "tree mallow",
+    "86": "magnolia",
+    "87": "cyclamen",
+    "88": "watercress",
+    "89": "canna lily",
+    "90": "hippeastrum",
+    "91": "bee balm",
+    "92": "ball moss",
+    "93": "foxglove",
+    "94": "bougainvillea",
+    "95": "camellia",
+    "96": "mallow",
+    "97": "mexican petunia",
+    "98": "bromelia",
+    "99": "blanket flower",
+    "100": "trumpet creeper",
+    "101": "blackberry lily"
+  },
+  "label2id": {
+    "alpine sea holly": 34,
+    "anthurium": 79,
+    "artichoke": 28,
+    "azalea": 71,
+    "ball moss": 92,
+    "balloon flower": 18,
+    "barbeton daisy": 40,
+    "bearded iris": 67,
+    "bee balm": 91,
+    "bird of paradise": 7,
+    "bishop of llandaff": 55,
+    "black-eyed susan": 62,
+    "blackberry lily": 101,
+    "blanket flower": 99,
+    "bolero deep blue": 44,
+    "bougainvillea": 94,
+    "bromelia": 98,
+    "buttercup": 47,
+    "californian poppy": 64,
+    "camellia": 95,
+    "canna lily": 89,
+    "canterbury bells": 2,
+    "cape flower": 36,
+    "carnation": 30,
+    "cautleya spicata": 60,
+    "clematis": 81,
+    "colt's foot": 11,
+    "columbine": 83,
+    "common dandelion": 49,
+    "corn poppy": 25,
+    "cyclamen": 87,
+    "daffodil": 41,
+    "desert-rose": 84,
+    "english marigold": 4,
+    "fire lily": 20,
+    "foxglove": 93,
+    "frangipani": 80,
+    "fritillary": 22,
+    "garden phlox": 31,
+    "gaura": 56,
+    "gazania": 70,
+    "geranium": 57,
+    "giant white arum lily": 19,
+    "globe thistle": 9,
+    "globe-flower": 15,
+    "grape hyacinth": 24,
+    "great masterwort": 37,
+    "hard-leaved pocket orchid": 1,
+    "hibiscus": 82,
+    "hippeastrum": 90,
+    "japanese anemone": 61,
+    "king protea": 12,
+    "lenten rose": 39,
+    "lotus": 77,
+    "love in the mist": 32,
+    "magnolia": 86,
+    "mallow": 96,
+    "marigold": 46,
+    "mexican aster": 33,
+    "mexican petunia": 97,
+    "monkshood": 8,
+    "moon orchid": 6,
+    "morning glory": 75,
+    "orange dahlia": 58,
+    "osteospermum": 65,
+    "oxeye daisy": 48,
+    "passion flower": 76,
+    "pelargonium": 54,
+    "peruvian lily": 17,
+    "petunia": 50,
+    "pincushion flower": 21,
+    "pink primrose": 0,
+    "pink-yellow dahlia?": 59,
+    "poinsettia": 43,
+    "primula": 52,
+    "prince of wales feathers": 26,
+    "purple coneflower": 16,
+    "red ginger": 23,
+    "rose": 73,
+    "ruby-lipped cattleya": 35,
+    "siam tulip": 38,
+    "silverbush": 63,
+    "snapdragon": 10,
+    "spear thistle": 13,
+    "spring crocus": 66,
+    "stemless gentian": 27,
+    "sunflower": 53,
+    "sweet pea": 3,
+    "sweet william": 29,
+    "sword lily": 42,
+    "thorn apple": 74,
+    "tiger lily": 5,
+    "toad lily": 78,
+    "tree mallow": 85,
+    "tree poppy": 69,
+    "trumpet creeper": 100,
+    "wallflower": 45,
+    "water lily": 72,
+    "watercress": 88,
+    "wild pansy": 51,
+    "windflower": 68,
+    "yellow iris": 14
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet50-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-oxford_flowers102-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/README.md b/resnet50-oxford_flowers102-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..b0eb7d5e89686cbdbd259dd6c7547691388d470e
--- /dev/null
+++ b/resnet50-oxford_flowers102-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford_flowers102.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: oxford_flowers102
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: train
+type: transformers
+val_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: test
+```
+
diff --git a/resnet50-oxford_flowers102-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/config.json b/resnet50-oxford_flowers102-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..ee05e378f6d60c8217f7b8db60be10c17bce37e2
--- /dev/null
+++ b/resnet50-oxford_flowers102-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,247 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "pink primrose",
+    "1": "hard-leaved pocket orchid",
+    "2": "canterbury bells",
+    "3": "sweet pea",
+    "4": "english marigold",
+    "5": "tiger lily",
+    "6": "moon orchid",
+    "7": "bird of paradise",
+    "8": "monkshood",
+    "9": "globe thistle",
+    "10": "snapdragon",
+    "11": "colt's foot",
+    "12": "king protea",
+    "13": "spear thistle",
+    "14": "yellow iris",
+    "15": "globe-flower",
+    "16": "purple coneflower",
+    "17": "peruvian lily",
+    "18": "balloon flower",
+    "19": "giant white arum lily",
+    "20": "fire lily",
+    "21": "pincushion flower",
+    "22": "fritillary",
+    "23": "red ginger",
+    "24": "grape hyacinth",
+    "25": "corn poppy",
+    "26": "prince of wales feathers",
+    "27": "stemless gentian",
+    "28": "artichoke",
+    "29": "sweet william",
+    "30": "carnation",
+    "31": "garden phlox",
+    "32": "love in the mist",
+    "33": "mexican aster",
+    "34": "alpine sea holly",
+    "35": "ruby-lipped cattleya",
+    "36": "cape flower",
+    "37": "great masterwort",
+    "38": "siam tulip",
+    "39": "lenten rose",
+    "40": "barbeton daisy",
+    "41": "daffodil",
+    "42": "sword lily",
+    "43": "poinsettia",
+    "44": "bolero deep blue",
+    "45": "wallflower",
+    "46": "marigold",
+    "47": "buttercup",
+    "48": "oxeye daisy",
+    "49": "common dandelion",
+    "50": "petunia",
+    "51": "wild pansy",
+    "52": "primula",
+    "53": "sunflower",
+    "54": "pelargonium",
+    "55": "bishop of llandaff",
+    "56": "gaura",
+    "57": "geranium",
+    "58": "orange dahlia",
+    "59": "pink-yellow dahlia?",
+    "60": "cautleya spicata",
+    "61": "japanese anemone",
+    "62": "black-eyed susan",
+    "63": "silverbush",
+    "64": "californian poppy",
+    "65": "osteospermum",
+    "66": "spring crocus",
+    "67": "bearded iris",
+    "68": "windflower",
+    "69": "tree poppy",
+    "70": "gazania",
+    "71": "azalea",
+    "72": "water lily",
+    "73": "rose",
+    "74": "thorn apple",
+    "75": "morning glory",
+    "76": "passion flower",
+    "77": "lotus",
+    "78": "toad lily",
+    "79": "anthurium",
+    "80": "frangipani",
+    "81": "clematis",
+    "82": "hibiscus",
+    "83": "columbine",
+    "84": "desert-rose",
+    "85": "tree mallow",
+    "86": "magnolia",
+    "87": "cyclamen",
+    "88": "watercress",
+    "89": "canna lily",
+    "90": "hippeastrum",
+    "91": "bee balm",
+    "92": "ball moss",
+    "93": "foxglove",
+    "94": "bougainvillea",
+    "95": "camellia",
+    "96": "mallow",
+    "97": "mexican petunia",
+    "98": "bromelia",
+    "99": "blanket flower",
+    "100": "trumpet creeper",
+    "101": "blackberry lily"
+  },
+  "label2id": {
+    "alpine sea holly": 34,
+    "anthurium": 79,
+    "artichoke": 28,
+    "azalea": 71,
+    "ball moss": 92,
+    "balloon flower": 18,
+    "barbeton daisy": 40,
+    "bearded iris": 67,
+    "bee balm": 91,
+    "bird of paradise": 7,
+    "bishop of llandaff": 55,
+    "black-eyed susan": 62,
+    "blackberry lily": 101,
+    "blanket flower": 99,
+    "bolero deep blue": 44,
+    "bougainvillea": 94,
+    "bromelia": 98,
+    "buttercup": 47,
+    "californian poppy": 64,
+    "camellia": 95,
+    "canna lily": 89,
+    "canterbury bells": 2,
+    "cape flower": 36,
+    "carnation": 30,
+    "cautleya spicata": 60,
+    "clematis": 81,
+    "colt's foot": 11,
+    "columbine": 83,
+    "common dandelion": 49,
+    "corn poppy": 25,
+    "cyclamen": 87,
+    "daffodil": 41,
+    "desert-rose": 84,
+    "english marigold": 4,
+    "fire lily": 20,
+    "foxglove": 93,
+    "frangipani": 80,
+    "fritillary": 22,
+    "garden phlox": 31,
+    "gaura": 56,
+    "gazania": 70,
+    "geranium": 57,
+    "giant white arum lily": 19,
+    "globe thistle": 9,
+    "globe-flower": 15,
+    "grape hyacinth": 24,
+    "great masterwort": 37,
+    "hard-leaved pocket orchid": 1,
+    "hibiscus": 82,
+    "hippeastrum": 90,
+    "japanese anemone": 61,
+    "king protea": 12,
+    "lenten rose": 39,
+    "lotus": 77,
+    "love in the mist": 32,
+    "magnolia": 86,
+    "mallow": 96,
+    "marigold": 46,
+    "mexican aster": 33,
+    "mexican petunia": 97,
+    "monkshood": 8,
+    "moon orchid": 6,
+    "morning glory": 75,
+    "orange dahlia": 58,
+    "osteospermum": 65,
+    "oxeye daisy": 48,
+    "passion flower": 76,
+    "pelargonium": 54,
+    "peruvian lily": 17,
+    "petunia": 50,
+    "pincushion flower": 21,
+    "pink primrose": 0,
+    "pink-yellow dahlia?": 59,
+    "poinsettia": 43,
+    "primula": 52,
+    "prince of wales feathers": 26,
+    "purple coneflower": 16,
+    "red ginger": 23,
+    "rose": 73,
+    "ruby-lipped cattleya": 35,
+    "siam tulip": 38,
+    "silverbush": 63,
+    "snapdragon": 10,
+    "spear thistle": 13,
+    "spring crocus": 66,
+    "stemless gentian": 27,
+    "sunflower": 53,
+    "sweet pea": 3,
+    "sweet william": 29,
+    "sword lily": 42,
+    "thorn apple": 74,
+    "tiger lily": 5,
+    "toad lily": 78,
+    "tree mallow": 85,
+    "tree poppy": 69,
+    "trumpet creeper": 100,
+    "wallflower": 45,
+    "water lily": 72,
+    "watercress": 88,
+    "wild pansy": 51,
+    "windflower": 68,
+    "yellow iris": 14
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-oxford_flowers102-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet50-oxford_flowers102-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-oxford_flowers102-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/README.md b/resnet50-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..3265e96f4c38c2fe5a41efea96664e37da81a985
--- /dev/null
+++ b/resnet50-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford_flowers102.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: oxford_flowers102
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: train
+type: transformers
+val_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: test
+```
+
diff --git a/resnet50-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/config.json b/resnet50-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..ee05e378f6d60c8217f7b8db60be10c17bce37e2
--- /dev/null
+++ b/resnet50-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,247 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "pink primrose",
+    "1": "hard-leaved pocket orchid",
+    "2": "canterbury bells",
+    "3": "sweet pea",
+    "4": "english marigold",
+    "5": "tiger lily",
+    "6": "moon orchid",
+    "7": "bird of paradise",
+    "8": "monkshood",
+    "9": "globe thistle",
+    "10": "snapdragon",
+    "11": "colt's foot",
+    "12": "king protea",
+    "13": "spear thistle",
+    "14": "yellow iris",
+    "15": "globe-flower",
+    "16": "purple coneflower",
+    "17": "peruvian lily",
+    "18": "balloon flower",
+    "19": "giant white arum lily",
+    "20": "fire lily",
+    "21": "pincushion flower",
+    "22": "fritillary",
+    "23": "red ginger",
+    "24": "grape hyacinth",
+    "25": "corn poppy",
+    "26": "prince of wales feathers",
+    "27": "stemless gentian",
+    "28": "artichoke",
+    "29": "sweet william",
+    "30": "carnation",
+    "31": "garden phlox",
+    "32": "love in the mist",
+    "33": "mexican aster",
+    "34": "alpine sea holly",
+    "35": "ruby-lipped cattleya",
+    "36": "cape flower",
+    "37": "great masterwort",
+    "38": "siam tulip",
+    "39": "lenten rose",
+    "40": "barbeton daisy",
+    "41": "daffodil",
+    "42": "sword lily",
+    "43": "poinsettia",
+    "44": "bolero deep blue",
+    "45": "wallflower",
+    "46": "marigold",
+    "47": "buttercup",
+    "48": "oxeye daisy",
+    "49": "common dandelion",
+    "50": "petunia",
+    "51": "wild pansy",
+    "52": "primula",
+    "53": "sunflower",
+    "54": "pelargonium",
+    "55": "bishop of llandaff",
+    "56": "gaura",
+    "57": "geranium",
+    "58": "orange dahlia",
+    "59": "pink-yellow dahlia?",
+    "60": "cautleya spicata",
+    "61": "japanese anemone",
+    "62": "black-eyed susan",
+    "63": "silverbush",
+    "64": "californian poppy",
+    "65": "osteospermum",
+    "66": "spring crocus",
+    "67": "bearded iris",
+    "68": "windflower",
+    "69": "tree poppy",
+    "70": "gazania",
+    "71": "azalea",
+    "72": "water lily",
+    "73": "rose",
+    "74": "thorn apple",
+    "75": "morning glory",
+    "76": "passion flower",
+    "77": "lotus",
+    "78": "toad lily",
+    "79": "anthurium",
+    "80": "frangipani",
+    "81": "clematis",
+    "82": "hibiscus",
+    "83": "columbine",
+    "84": "desert-rose",
+    "85": "tree mallow",
+    "86": "magnolia",
+    "87": "cyclamen",
+    "88": "watercress",
+    "89": "canna lily",
+    "90": "hippeastrum",
+    "91": "bee balm",
+    "92": "ball moss",
+    "93": "foxglove",
+    "94": "bougainvillea",
+    "95": "camellia",
+    "96": "mallow",
+    "97": "mexican petunia",
+    "98": "bromelia",
+    "99": "blanket flower",
+    "100": "trumpet creeper",
+    "101": "blackberry lily"
+  },
+  "label2id": {
+    "alpine sea holly": 34,
+    "anthurium": 79,
+    "artichoke": 28,
+    "azalea": 71,
+    "ball moss": 92,
+    "balloon flower": 18,
+    "barbeton daisy": 40,
+    "bearded iris": 67,
+    "bee balm": 91,
+    "bird of paradise": 7,
+    "bishop of llandaff": 55,
+    "black-eyed susan": 62,
+    "blackberry lily": 101,
+    "blanket flower": 99,
+    "bolero deep blue": 44,
+    "bougainvillea": 94,
+    "bromelia": 98,
+    "buttercup": 47,
+    "californian poppy": 64,
+    "camellia": 95,
+    "canna lily": 89,
+    "canterbury bells": 2,
+    "cape flower": 36,
+    "carnation": 30,
+    "cautleya spicata": 60,
+    "clematis": 81,
+    "colt's foot": 11,
+    "columbine": 83,
+    "common dandelion": 49,
+    "corn poppy": 25,
+    "cyclamen": 87,
+    "daffodil": 41,
+    "desert-rose": 84,
+    "english marigold": 4,
+    "fire lily": 20,
+    "foxglove": 93,
+    "frangipani": 80,
+    "fritillary": 22,
+    "garden phlox": 31,
+    "gaura": 56,
+    "gazania": 70,
+    "geranium": 57,
+    "giant white arum lily": 19,
+    "globe thistle": 9,
+    "globe-flower": 15,
+    "grape hyacinth": 24,
+    "great masterwort": 37,
+    "hard-leaved pocket orchid": 1,
+    "hibiscus": 82,
+    "hippeastrum": 90,
+    "japanese anemone": 61,
+    "king protea": 12,
+    "lenten rose": 39,
+    "lotus": 77,
+    "love in the mist": 32,
+    "magnolia": 86,
+    "mallow": 96,
+    "marigold": 46,
+    "mexican aster": 33,
+    "mexican petunia": 97,
+    "monkshood": 8,
+    "moon orchid": 6,
+    "morning glory": 75,
+    "orange dahlia": 58,
+    "osteospermum": 65,
+    "oxeye daisy": 48,
+    "passion flower": 76,
+    "pelargonium": 54,
+    "peruvian lily": 17,
+    "petunia": 50,
+    "pincushion flower": 21,
+    "pink primrose": 0,
+    "pink-yellow dahlia?": 59,
+    "poinsettia": 43,
+    "primula": 52,
+    "prince of wales feathers": 26,
+    "purple coneflower": 16,
+    "red ginger": 23,
+    "rose": 73,
+    "ruby-lipped cattleya": 35,
+    "siam tulip": 38,
+    "silverbush": 63,
+    "snapdragon": 10,
+    "spear thistle": 13,
+    "spring crocus": 66,
+    "stemless gentian": 27,
+    "sunflower": 53,
+    "sweet pea": 3,
+    "sweet william": 29,
+    "sword lily": 42,
+    "thorn apple": 74,
+    "tiger lily": 5,
+    "toad lily": 78,
+    "tree mallow": 85,
+    "tree poppy": 69,
+    "trumpet creeper": 100,
+    "wallflower": 45,
+    "water lily": 72,
+    "watercress": 88,
+    "wild pansy": 51,
+    "windflower": 68,
+    "yellow iris": 14
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet50-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/README.md b/resnet50-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..667c145990791f8bb15a5cdc0ac03165f56e715b
--- /dev/null
+++ b/resnet50-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford_flowers102.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: oxford_flowers102
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: train
+type: transformers
+val_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: test
+```
+
diff --git a/resnet50-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/config.json b/resnet50-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..ee05e378f6d60c8217f7b8db60be10c17bce37e2
--- /dev/null
+++ b/resnet50-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/config.json
@@ -0,0 +1,247 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "pink primrose",
+    "1": "hard-leaved pocket orchid",
+    "2": "canterbury bells",
+    "3": "sweet pea",
+    "4": "english marigold",
+    "5": "tiger lily",
+    "6": "moon orchid",
+    "7": "bird of paradise",
+    "8": "monkshood",
+    "9": "globe thistle",
+    "10": "snapdragon",
+    "11": "colt's foot",
+    "12": "king protea",
+    "13": "spear thistle",
+    "14": "yellow iris",
+    "15": "globe-flower",
+    "16": "purple coneflower",
+    "17": "peruvian lily",
+    "18": "balloon flower",
+    "19": "giant white arum lily",
+    "20": "fire lily",
+    "21": "pincushion flower",
+    "22": "fritillary",
+    "23": "red ginger",
+    "24": "grape hyacinth",
+    "25": "corn poppy",
+    "26": "prince of wales feathers",
+    "27": "stemless gentian",
+    "28": "artichoke",
+    "29": "sweet william",
+    "30": "carnation",
+    "31": "garden phlox",
+    "32": "love in the mist",
+    "33": "mexican aster",
+    "34": "alpine sea holly",
+    "35": "ruby-lipped cattleya",
+    "36": "cape flower",
+    "37": "great masterwort",
+    "38": "siam tulip",
+    "39": "lenten rose",
+    "40": "barbeton daisy",
+    "41": "daffodil",
+    "42": "sword lily",
+    "43": "poinsettia",
+    "44": "bolero deep blue",
+    "45": "wallflower",
+    "46": "marigold",
+    "47": "buttercup",
+    "48": "oxeye daisy",
+    "49": "common dandelion",
+    "50": "petunia",
+    "51": "wild pansy",
+    "52": "primula",
+    "53": "sunflower",
+    "54": "pelargonium",
+    "55": "bishop of llandaff",
+    "56": "gaura",
+    "57": "geranium",
+    "58": "orange dahlia",
+    "59": "pink-yellow dahlia?",
+    "60": "cautleya spicata",
+    "61": "japanese anemone",
+    "62": "black-eyed susan",
+    "63": "silverbush",
+    "64": "californian poppy",
+    "65": "osteospermum",
+    "66": "spring crocus",
+    "67": "bearded iris",
+    "68": "windflower",
+    "69": "tree poppy",
+    "70": "gazania",
+    "71": "azalea",
+    "72": "water lily",
+    "73": "rose",
+    "74": "thorn apple",
+    "75": "morning glory",
+    "76": "passion flower",
+    "77": "lotus",
+    "78": "toad lily",
+    "79": "anthurium",
+    "80": "frangipani",
+    "81": "clematis",
+    "82": "hibiscus",
+    "83": "columbine",
+    "84": "desert-rose",
+    "85": "tree mallow",
+    "86": "magnolia",
+    "87": "cyclamen",
+    "88": "watercress",
+    "89": "canna lily",
+    "90": "hippeastrum",
+    "91": "bee balm",
+    "92": "ball moss",
+    "93": "foxglove",
+    "94": "bougainvillea",
+    "95": "camellia",
+    "96": "mallow",
+    "97": "mexican petunia",
+    "98": "bromelia",
+    "99": "blanket flower",
+    "100": "trumpet creeper",
+    "101": "blackberry lily"
+  },
+  "label2id": {
+    "alpine sea holly": 34,
+    "anthurium": 79,
+    "artichoke": 28,
+    "azalea": 71,
+    "ball moss": 92,
+    "balloon flower": 18,
+    "barbeton daisy": 40,
+    "bearded iris": 67,
+    "bee balm": 91,
+    "bird of paradise": 7,
+    "bishop of llandaff": 55,
+    "black-eyed susan": 62,
+    "blackberry lily": 101,
+    "blanket flower": 99,
+    "bolero deep blue": 44,
+    "bougainvillea": 94,
+    "bromelia": 98,
+    "buttercup": 47,
+    "californian poppy": 64,
+    "camellia": 95,
+    "canna lily": 89,
+    "canterbury bells": 2,
+    "cape flower": 36,
+    "carnation": 30,
+    "cautleya spicata": 60,
+    "clematis": 81,
+    "colt's foot": 11,
+    "columbine": 83,
+    "common dandelion": 49,
+    "corn poppy": 25,
+    "cyclamen": 87,
+    "daffodil": 41,
+    "desert-rose": 84,
+    "english marigold": 4,
+    "fire lily": 20,
+    "foxglove": 93,
+    "frangipani": 80,
+    "fritillary": 22,
+    "garden phlox": 31,
+    "gaura": 56,
+    "gazania": 70,
+    "geranium": 57,
+    "giant white arum lily": 19,
+    "globe thistle": 9,
+    "globe-flower": 15,
+    "grape hyacinth": 24,
+    "great masterwort": 37,
+    "hard-leaved pocket orchid": 1,
+    "hibiscus": 82,
+    "hippeastrum": 90,
+    "japanese anemone": 61,
+    "king protea": 12,
+    "lenten rose": 39,
+    "lotus": 77,
+    "love in the mist": 32,
+    "magnolia": 86,
+    "mallow": 96,
+    "marigold": 46,
+    "mexican aster": 33,
+    "mexican petunia": 97,
+    "monkshood": 8,
+    "moon orchid": 6,
+    "morning glory": 75,
+    "orange dahlia": 58,
+    "osteospermum": 65,
+    "oxeye daisy": 48,
+    "passion flower": 76,
+    "pelargonium": 54,
+    "peruvian lily": 17,
+    "petunia": 50,
+    "pincushion flower": 21,
+    "pink primrose": 0,
+    "pink-yellow dahlia?": 59,
+    "poinsettia": 43,
+    "primula": 52,
+    "prince of wales feathers": 26,
+    "purple coneflower": 16,
+    "red ginger": 23,
+    "rose": 73,
+    "ruby-lipped cattleya": 35,
+    "siam tulip": 38,
+    "silverbush": 63,
+    "snapdragon": 10,
+    "spear thistle": 13,
+    "spring crocus": 66,
+    "stemless gentian": 27,
+    "sunflower": 53,
+    "sweet pea": 3,
+    "sweet william": 29,
+    "sword lily": 42,
+    "thorn apple": 74,
+    "tiger lily": 5,
+    "toad lily": 78,
+    "tree mallow": 85,
+    "tree poppy": 69,
+    "trumpet creeper": 100,
+    "wallflower": 45,
+    "water lily": 72,
+    "watercress": 88,
+    "wild pansy": 51,
+    "windflower": 68,
+    "yellow iris": 14
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet50-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-oxford_flowers102-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/README.md b/resnet50-oxford_flowers102-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..7c2e0e1ed79bdcc14d9da2028357def9b815e8f0
--- /dev/null
+++ b/resnet50-oxford_flowers102-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford_flowers102.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: oxford_flowers102
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: train
+type: transformers
+val_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: test
+```
+
diff --git a/resnet50-oxford_flowers102-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/config.json b/resnet50-oxford_flowers102-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..ee05e378f6d60c8217f7b8db60be10c17bce37e2
--- /dev/null
+++ b/resnet50-oxford_flowers102-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,247 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "pink primrose",
+    "1": "hard-leaved pocket orchid",
+    "2": "canterbury bells",
+    "3": "sweet pea",
+    "4": "english marigold",
+    "5": "tiger lily",
+    "6": "moon orchid",
+    "7": "bird of paradise",
+    "8": "monkshood",
+    "9": "globe thistle",
+    "10": "snapdragon",
+    "11": "colt's foot",
+    "12": "king protea",
+    "13": "spear thistle",
+    "14": "yellow iris",
+    "15": "globe-flower",
+    "16": "purple coneflower",
+    "17": "peruvian lily",
+    "18": "balloon flower",
+    "19": "giant white arum lily",
+    "20": "fire lily",
+    "21": "pincushion flower",
+    "22": "fritillary",
+    "23": "red ginger",
+    "24": "grape hyacinth",
+    "25": "corn poppy",
+    "26": "prince of wales feathers",
+    "27": "stemless gentian",
+    "28": "artichoke",
+    "29": "sweet william",
+    "30": "carnation",
+    "31": "garden phlox",
+    "32": "love in the mist",
+    "33": "mexican aster",
+    "34": "alpine sea holly",
+    "35": "ruby-lipped cattleya",
+    "36": "cape flower",
+    "37": "great masterwort",
+    "38": "siam tulip",
+    "39": "lenten rose",
+    "40": "barbeton daisy",
+    "41": "daffodil",
+    "42": "sword lily",
+    "43": "poinsettia",
+    "44": "bolero deep blue",
+    "45": "wallflower",
+    "46": "marigold",
+    "47": "buttercup",
+    "48": "oxeye daisy",
+    "49": "common dandelion",
+    "50": "petunia",
+    "51": "wild pansy",
+    "52": "primula",
+    "53": "sunflower",
+    "54": "pelargonium",
+    "55": "bishop of llandaff",
+    "56": "gaura",
+    "57": "geranium",
+    "58": "orange dahlia",
+    "59": "pink-yellow dahlia?",
+    "60": "cautleya spicata",
+    "61": "japanese anemone",
+    "62": "black-eyed susan",
+    "63": "silverbush",
+    "64": "californian poppy",
+    "65": "osteospermum",
+    "66": "spring crocus",
+    "67": "bearded iris",
+    "68": "windflower",
+    "69": "tree poppy",
+    "70": "gazania",
+    "71": "azalea",
+    "72": "water lily",
+    "73": "rose",
+    "74": "thorn apple",
+    "75": "morning glory",
+    "76": "passion flower",
+    "77": "lotus",
+    "78": "toad lily",
+    "79": "anthurium",
+    "80": "frangipani",
+    "81": "clematis",
+    "82": "hibiscus",
+    "83": "columbine",
+    "84": "desert-rose",
+    "85": "tree mallow",
+    "86": "magnolia",
+    "87": "cyclamen",
+    "88": "watercress",
+    "89": "canna lily",
+    "90": "hippeastrum",
+    "91": "bee balm",
+    "92": "ball moss",
+    "93": "foxglove",
+    "94": "bougainvillea",
+    "95": "camellia",
+    "96": "mallow",
+    "97": "mexican petunia",
+    "98": "bromelia",
+    "99": "blanket flower",
+    "100": "trumpet creeper",
+    "101": "blackberry lily"
+  },
+  "label2id": {
+    "alpine sea holly": 34,
+    "anthurium": 79,
+    "artichoke": 28,
+    "azalea": 71,
+    "ball moss": 92,
+    "balloon flower": 18,
+    "barbeton daisy": 40,
+    "bearded iris": 67,
+    "bee balm": 91,
+    "bird of paradise": 7,
+    "bishop of llandaff": 55,
+    "black-eyed susan": 62,
+    "blackberry lily": 101,
+    "blanket flower": 99,
+    "bolero deep blue": 44,
+    "bougainvillea": 94,
+    "bromelia": 98,
+    "buttercup": 47,
+    "californian poppy": 64,
+    "camellia": 95,
+    "canna lily": 89,
+    "canterbury bells": 2,
+    "cape flower": 36,
+    "carnation": 30,
+    "cautleya spicata": 60,
+    "clematis": 81,
+    "colt's foot": 11,
+    "columbine": 83,
+    "common dandelion": 49,
+    "corn poppy": 25,
+    "cyclamen": 87,
+    "daffodil": 41,
+    "desert-rose": 84,
+    "english marigold": 4,
+    "fire lily": 20,
+    "foxglove": 93,
+    "frangipani": 80,
+    "fritillary": 22,
+    "garden phlox": 31,
+    "gaura": 56,
+    "gazania": 70,
+    "geranium": 57,
+    "giant white arum lily": 19,
+    "globe thistle": 9,
+    "globe-flower": 15,
+    "grape hyacinth": 24,
+    "great masterwort": 37,
+    "hard-leaved pocket orchid": 1,
+    "hibiscus": 82,
+    "hippeastrum": 90,
+    "japanese anemone": 61,
+    "king protea": 12,
+    "lenten rose": 39,
+    "lotus": 77,
+    "love in the mist": 32,
+    "magnolia": 86,
+    "mallow": 96,
+    "marigold": 46,
+    "mexican aster": 33,
+    "mexican petunia": 97,
+    "monkshood": 8,
+    "moon orchid": 6,
+    "morning glory": 75,
+    "orange dahlia": 58,
+    "osteospermum": 65,
+    "oxeye daisy": 48,
+    "passion flower": 76,
+    "pelargonium": 54,
+    "peruvian lily": 17,
+    "petunia": 50,
+    "pincushion flower": 21,
+    "pink primrose": 0,
+    "pink-yellow dahlia?": 59,
+    "poinsettia": 43,
+    "primula": 52,
+    "prince of wales feathers": 26,
+    "purple coneflower": 16,
+    "red ginger": 23,
+    "rose": 73,
+    "ruby-lipped cattleya": 35,
+    "siam tulip": 38,
+    "silverbush": 63,
+    "snapdragon": 10,
+    "spear thistle": 13,
+    "spring crocus": 66,
+    "stemless gentian": 27,
+    "sunflower": 53,
+    "sweet pea": 3,
+    "sweet william": 29,
+    "sword lily": 42,
+    "thorn apple": 74,
+    "tiger lily": 5,
+    "toad lily": 78,
+    "tree mallow": 85,
+    "tree poppy": 69,
+    "trumpet creeper": 100,
+    "wallflower": 45,
+    "water lily": 72,
+    "watercress": 88,
+    "wild pansy": 51,
+    "windflower": 68,
+    "yellow iris": 14
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-oxford_flowers102-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet50-oxford_flowers102-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-oxford_flowers102-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/README.md b/resnet50-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..620f292cb1f974acb20b2676542fa71785a3ed47
--- /dev/null
+++ b/resnet50-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford_flowers102.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: oxford_flowers102
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: train
+type: transformers
+val_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: test
+```
+
diff --git a/resnet50-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/config.json b/resnet50-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..ee05e378f6d60c8217f7b8db60be10c17bce37e2
--- /dev/null
+++ b/resnet50-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/config.json
@@ -0,0 +1,247 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "pink primrose",
+    "1": "hard-leaved pocket orchid",
+    "2": "canterbury bells",
+    "3": "sweet pea",
+    "4": "english marigold",
+    "5": "tiger lily",
+    "6": "moon orchid",
+    "7": "bird of paradise",
+    "8": "monkshood",
+    "9": "globe thistle",
+    "10": "snapdragon",
+    "11": "colt's foot",
+    "12": "king protea",
+    "13": "spear thistle",
+    "14": "yellow iris",
+    "15": "globe-flower",
+    "16": "purple coneflower",
+    "17": "peruvian lily",
+    "18": "balloon flower",
+    "19": "giant white arum lily",
+    "20": "fire lily",
+    "21": "pincushion flower",
+    "22": "fritillary",
+    "23": "red ginger",
+    "24": "grape hyacinth",
+    "25": "corn poppy",
+    "26": "prince of wales feathers",
+    "27": "stemless gentian",
+    "28": "artichoke",
+    "29": "sweet william",
+    "30": "carnation",
+    "31": "garden phlox",
+    "32": "love in the mist",
+    "33": "mexican aster",
+    "34": "alpine sea holly",
+    "35": "ruby-lipped cattleya",
+    "36": "cape flower",
+    "37": "great masterwort",
+    "38": "siam tulip",
+    "39": "lenten rose",
+    "40": "barbeton daisy",
+    "41": "daffodil",
+    "42": "sword lily",
+    "43": "poinsettia",
+    "44": "bolero deep blue",
+    "45": "wallflower",
+    "46": "marigold",
+    "47": "buttercup",
+    "48": "oxeye daisy",
+    "49": "common dandelion",
+    "50": "petunia",
+    "51": "wild pansy",
+    "52": "primula",
+    "53": "sunflower",
+    "54": "pelargonium",
+    "55": "bishop of llandaff",
+    "56": "gaura",
+    "57": "geranium",
+    "58": "orange dahlia",
+    "59": "pink-yellow dahlia?",
+    "60": "cautleya spicata",
+    "61": "japanese anemone",
+    "62": "black-eyed susan",
+    "63": "silverbush",
+    "64": "californian poppy",
+    "65": "osteospermum",
+    "66": "spring crocus",
+    "67": "bearded iris",
+    "68": "windflower",
+    "69": "tree poppy",
+    "70": "gazania",
+    "71": "azalea",
+    "72": "water lily",
+    "73": "rose",
+    "74": "thorn apple",
+    "75": "morning glory",
+    "76": "passion flower",
+    "77": "lotus",
+    "78": "toad lily",
+    "79": "anthurium",
+    "80": "frangipani",
+    "81": "clematis",
+    "82": "hibiscus",
+    "83": "columbine",
+    "84": "desert-rose",
+    "85": "tree mallow",
+    "86": "magnolia",
+    "87": "cyclamen",
+    "88": "watercress",
+    "89": "canna lily",
+    "90": "hippeastrum",
+    "91": "bee balm",
+    "92": "ball moss",
+    "93": "foxglove",
+    "94": "bougainvillea",
+    "95": "camellia",
+    "96": "mallow",
+    "97": "mexican petunia",
+    "98": "bromelia",
+    "99": "blanket flower",
+    "100": "trumpet creeper",
+    "101": "blackberry lily"
+  },
+  "label2id": {
+    "alpine sea holly": 34,
+    "anthurium": 79,
+    "artichoke": 28,
+    "azalea": 71,
+    "ball moss": 92,
+    "balloon flower": 18,
+    "barbeton daisy": 40,
+    "bearded iris": 67,
+    "bee balm": 91,
+    "bird of paradise": 7,
+    "bishop of llandaff": 55,
+    "black-eyed susan": 62,
+    "blackberry lily": 101,
+    "blanket flower": 99,
+    "bolero deep blue": 44,
+    "bougainvillea": 94,
+    "bromelia": 98,
+    "buttercup": 47,
+    "californian poppy": 64,
+    "camellia": 95,
+    "canna lily": 89,
+    "canterbury bells": 2,
+    "cape flower": 36,
+    "carnation": 30,
+    "cautleya spicata": 60,
+    "clematis": 81,
+    "colt's foot": 11,
+    "columbine": 83,
+    "common dandelion": 49,
+    "corn poppy": 25,
+    "cyclamen": 87,
+    "daffodil": 41,
+    "desert-rose": 84,
+    "english marigold": 4,
+    "fire lily": 20,
+    "foxglove": 93,
+    "frangipani": 80,
+    "fritillary": 22,
+    "garden phlox": 31,
+    "gaura": 56,
+    "gazania": 70,
+    "geranium": 57,
+    "giant white arum lily": 19,
+    "globe thistle": 9,
+    "globe-flower": 15,
+    "grape hyacinth": 24,
+    "great masterwort": 37,
+    "hard-leaved pocket orchid": 1,
+    "hibiscus": 82,
+    "hippeastrum": 90,
+    "japanese anemone": 61,
+    "king protea": 12,
+    "lenten rose": 39,
+    "lotus": 77,
+    "love in the mist": 32,
+    "magnolia": 86,
+    "mallow": 96,
+    "marigold": 46,
+    "mexican aster": 33,
+    "mexican petunia": 97,
+    "monkshood": 8,
+    "moon orchid": 6,
+    "morning glory": 75,
+    "orange dahlia": 58,
+    "osteospermum": 65,
+    "oxeye daisy": 48,
+    "passion flower": 76,
+    "pelargonium": 54,
+    "peruvian lily": 17,
+    "petunia": 50,
+    "pincushion flower": 21,
+    "pink primrose": 0,
+    "pink-yellow dahlia?": 59,
+    "poinsettia": 43,
+    "primula": 52,
+    "prince of wales feathers": 26,
+    "purple coneflower": 16,
+    "red ginger": 23,
+    "rose": 73,
+    "ruby-lipped cattleya": 35,
+    "siam tulip": 38,
+    "silverbush": 63,
+    "snapdragon": 10,
+    "spear thistle": 13,
+    "spring crocus": 66,
+    "stemless gentian": 27,
+    "sunflower": 53,
+    "sweet pea": 3,
+    "sweet william": 29,
+    "sword lily": 42,
+    "thorn apple": 74,
+    "tiger lily": 5,
+    "toad lily": 78,
+    "tree mallow": 85,
+    "tree poppy": 69,
+    "trumpet creeper": 100,
+    "wallflower": 45,
+    "water lily": 72,
+    "watercress": 88,
+    "wild pansy": 51,
+    "windflower": 68,
+    "yellow iris": 14
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet50-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/README.md b/resnet50-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..620f292cb1f974acb20b2676542fa71785a3ed47
--- /dev/null
+++ b/resnet50-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford_flowers102.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: oxford_flowers102
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: train
+type: transformers
+val_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: test
+```
+
diff --git a/resnet50-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/config.json b/resnet50-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..ee05e378f6d60c8217f7b8db60be10c17bce37e2
--- /dev/null
+++ b/resnet50-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,247 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "pink primrose",
+    "1": "hard-leaved pocket orchid",
+    "2": "canterbury bells",
+    "3": "sweet pea",
+    "4": "english marigold",
+    "5": "tiger lily",
+    "6": "moon orchid",
+    "7": "bird of paradise",
+    "8": "monkshood",
+    "9": "globe thistle",
+    "10": "snapdragon",
+    "11": "colt's foot",
+    "12": "king protea",
+    "13": "spear thistle",
+    "14": "yellow iris",
+    "15": "globe-flower",
+    "16": "purple coneflower",
+    "17": "peruvian lily",
+    "18": "balloon flower",
+    "19": "giant white arum lily",
+    "20": "fire lily",
+    "21": "pincushion flower",
+    "22": "fritillary",
+    "23": "red ginger",
+    "24": "grape hyacinth",
+    "25": "corn poppy",
+    "26": "prince of wales feathers",
+    "27": "stemless gentian",
+    "28": "artichoke",
+    "29": "sweet william",
+    "30": "carnation",
+    "31": "garden phlox",
+    "32": "love in the mist",
+    "33": "mexican aster",
+    "34": "alpine sea holly",
+    "35": "ruby-lipped cattleya",
+    "36": "cape flower",
+    "37": "great masterwort",
+    "38": "siam tulip",
+    "39": "lenten rose",
+    "40": "barbeton daisy",
+    "41": "daffodil",
+    "42": "sword lily",
+    "43": "poinsettia",
+    "44": "bolero deep blue",
+    "45": "wallflower",
+    "46": "marigold",
+    "47": "buttercup",
+    "48": "oxeye daisy",
+    "49": "common dandelion",
+    "50": "petunia",
+    "51": "wild pansy",
+    "52": "primula",
+    "53": "sunflower",
+    "54": "pelargonium",
+    "55": "bishop of llandaff",
+    "56": "gaura",
+    "57": "geranium",
+    "58": "orange dahlia",
+    "59": "pink-yellow dahlia?",
+    "60": "cautleya spicata",
+    "61": "japanese anemone",
+    "62": "black-eyed susan",
+    "63": "silverbush",
+    "64": "californian poppy",
+    "65": "osteospermum",
+    "66": "spring crocus",
+    "67": "bearded iris",
+    "68": "windflower",
+    "69": "tree poppy",
+    "70": "gazania",
+    "71": "azalea",
+    "72": "water lily",
+    "73": "rose",
+    "74": "thorn apple",
+    "75": "morning glory",
+    "76": "passion flower",
+    "77": "lotus",
+    "78": "toad lily",
+    "79": "anthurium",
+    "80": "frangipani",
+    "81": "clematis",
+    "82": "hibiscus",
+    "83": "columbine",
+    "84": "desert-rose",
+    "85": "tree mallow",
+    "86": "magnolia",
+    "87": "cyclamen",
+    "88": "watercress",
+    "89": "canna lily",
+    "90": "hippeastrum",
+    "91": "bee balm",
+    "92": "ball moss",
+    "93": "foxglove",
+    "94": "bougainvillea",
+    "95": "camellia",
+    "96": "mallow",
+    "97": "mexican petunia",
+    "98": "bromelia",
+    "99": "blanket flower",
+    "100": "trumpet creeper",
+    "101": "blackberry lily"
+  },
+  "label2id": {
+    "alpine sea holly": 34,
+    "anthurium": 79,
+    "artichoke": 28,
+    "azalea": 71,
+    "ball moss": 92,
+    "balloon flower": 18,
+    "barbeton daisy": 40,
+    "bearded iris": 67,
+    "bee balm": 91,
+    "bird of paradise": 7,
+    "bishop of llandaff": 55,
+    "black-eyed susan": 62,
+    "blackberry lily": 101,
+    "blanket flower": 99,
+    "bolero deep blue": 44,
+    "bougainvillea": 94,
+    "bromelia": 98,
+    "buttercup": 47,
+    "californian poppy": 64,
+    "camellia": 95,
+    "canna lily": 89,
+    "canterbury bells": 2,
+    "cape flower": 36,
+    "carnation": 30,
+    "cautleya spicata": 60,
+    "clematis": 81,
+    "colt's foot": 11,
+    "columbine": 83,
+    "common dandelion": 49,
+    "corn poppy": 25,
+    "cyclamen": 87,
+    "daffodil": 41,
+    "desert-rose": 84,
+    "english marigold": 4,
+    "fire lily": 20,
+    "foxglove": 93,
+    "frangipani": 80,
+    "fritillary": 22,
+    "garden phlox": 31,
+    "gaura": 56,
+    "gazania": 70,
+    "geranium": 57,
+    "giant white arum lily": 19,
+    "globe thistle": 9,
+    "globe-flower": 15,
+    "grape hyacinth": 24,
+    "great masterwort": 37,
+    "hard-leaved pocket orchid": 1,
+    "hibiscus": 82,
+    "hippeastrum": 90,
+    "japanese anemone": 61,
+    "king protea": 12,
+    "lenten rose": 39,
+    "lotus": 77,
+    "love in the mist": 32,
+    "magnolia": 86,
+    "mallow": 96,
+    "marigold": 46,
+    "mexican aster": 33,
+    "mexican petunia": 97,
+    "monkshood": 8,
+    "moon orchid": 6,
+    "morning glory": 75,
+    "orange dahlia": 58,
+    "osteospermum": 65,
+    "oxeye daisy": 48,
+    "passion flower": 76,
+    "pelargonium": 54,
+    "peruvian lily": 17,
+    "petunia": 50,
+    "pincushion flower": 21,
+    "pink primrose": 0,
+    "pink-yellow dahlia?": 59,
+    "poinsettia": 43,
+    "primula": 52,
+    "prince of wales feathers": 26,
+    "purple coneflower": 16,
+    "red ginger": 23,
+    "rose": 73,
+    "ruby-lipped cattleya": 35,
+    "siam tulip": 38,
+    "silverbush": 63,
+    "snapdragon": 10,
+    "spear thistle": 13,
+    "spring crocus": 66,
+    "stemless gentian": 27,
+    "sunflower": 53,
+    "sweet pea": 3,
+    "sweet william": 29,
+    "sword lily": 42,
+    "thorn apple": 74,
+    "tiger lily": 5,
+    "toad lily": 78,
+    "tree mallow": 85,
+    "tree poppy": 69,
+    "trumpet creeper": 100,
+    "wallflower": 45,
+    "water lily": 72,
+    "watercress": 88,
+    "wild pansy": 51,
+    "windflower": 68,
+    "yellow iris": 14
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet50-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-oxford_flowers102-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/README.md b/resnet50-oxford_flowers102-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..d65e257b165be652faaf60854f1a1a52d5131154
--- /dev/null
+++ b/resnet50-oxford_flowers102-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset oxford_flowers102.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: oxford_flowers102
+    pretrained: true
+test_datasets: null
+train_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: train
+type: transformers
+val_datasets:
+  oxford_flowers102:
+    _target_: datasets.load_dataset
+    path: dpdl-benchmark/oxford_flowers102
+    split: test
+```
+
diff --git a/resnet50-oxford_flowers102-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/config.json b/resnet50-oxford_flowers102-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..ee05e378f6d60c8217f7b8db60be10c17bce37e2
--- /dev/null
+++ b/resnet50-oxford_flowers102-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/config.json
@@ -0,0 +1,247 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "pink primrose",
+    "1": "hard-leaved pocket orchid",
+    "2": "canterbury bells",
+    "3": "sweet pea",
+    "4": "english marigold",
+    "5": "tiger lily",
+    "6": "moon orchid",
+    "7": "bird of paradise",
+    "8": "monkshood",
+    "9": "globe thistle",
+    "10": "snapdragon",
+    "11": "colt's foot",
+    "12": "king protea",
+    "13": "spear thistle",
+    "14": "yellow iris",
+    "15": "globe-flower",
+    "16": "purple coneflower",
+    "17": "peruvian lily",
+    "18": "balloon flower",
+    "19": "giant white arum lily",
+    "20": "fire lily",
+    "21": "pincushion flower",
+    "22": "fritillary",
+    "23": "red ginger",
+    "24": "grape hyacinth",
+    "25": "corn poppy",
+    "26": "prince of wales feathers",
+    "27": "stemless gentian",
+    "28": "artichoke",
+    "29": "sweet william",
+    "30": "carnation",
+    "31": "garden phlox",
+    "32": "love in the mist",
+    "33": "mexican aster",
+    "34": "alpine sea holly",
+    "35": "ruby-lipped cattleya",
+    "36": "cape flower",
+    "37": "great masterwort",
+    "38": "siam tulip",
+    "39": "lenten rose",
+    "40": "barbeton daisy",
+    "41": "daffodil",
+    "42": "sword lily",
+    "43": "poinsettia",
+    "44": "bolero deep blue",
+    "45": "wallflower",
+    "46": "marigold",
+    "47": "buttercup",
+    "48": "oxeye daisy",
+    "49": "common dandelion",
+    "50": "petunia",
+    "51": "wild pansy",
+    "52": "primula",
+    "53": "sunflower",
+    "54": "pelargonium",
+    "55": "bishop of llandaff",
+    "56": "gaura",
+    "57": "geranium",
+    "58": "orange dahlia",
+    "59": "pink-yellow dahlia?",
+    "60": "cautleya spicata",
+    "61": "japanese anemone",
+    "62": "black-eyed susan",
+    "63": "silverbush",
+    "64": "californian poppy",
+    "65": "osteospermum",
+    "66": "spring crocus",
+    "67": "bearded iris",
+    "68": "windflower",
+    "69": "tree poppy",
+    "70": "gazania",
+    "71": "azalea",
+    "72": "water lily",
+    "73": "rose",
+    "74": "thorn apple",
+    "75": "morning glory",
+    "76": "passion flower",
+    "77": "lotus",
+    "78": "toad lily",
+    "79": "anthurium",
+    "80": "frangipani",
+    "81": "clematis",
+    "82": "hibiscus",
+    "83": "columbine",
+    "84": "desert-rose",
+    "85": "tree mallow",
+    "86": "magnolia",
+    "87": "cyclamen",
+    "88": "watercress",
+    "89": "canna lily",
+    "90": "hippeastrum",
+    "91": "bee balm",
+    "92": "ball moss",
+    "93": "foxglove",
+    "94": "bougainvillea",
+    "95": "camellia",
+    "96": "mallow",
+    "97": "mexican petunia",
+    "98": "bromelia",
+    "99": "blanket flower",
+    "100": "trumpet creeper",
+    "101": "blackberry lily"
+  },
+  "label2id": {
+    "alpine sea holly": 34,
+    "anthurium": 79,
+    "artichoke": 28,
+    "azalea": 71,
+    "ball moss": 92,
+    "balloon flower": 18,
+    "barbeton daisy": 40,
+    "bearded iris": 67,
+    "bee balm": 91,
+    "bird of paradise": 7,
+    "bishop of llandaff": 55,
+    "black-eyed susan": 62,
+    "blackberry lily": 101,
+    "blanket flower": 99,
+    "bolero deep blue": 44,
+    "bougainvillea": 94,
+    "bromelia": 98,
+    "buttercup": 47,
+    "californian poppy": 64,
+    "camellia": 95,
+    "canna lily": 89,
+    "canterbury bells": 2,
+    "cape flower": 36,
+    "carnation": 30,
+    "cautleya spicata": 60,
+    "clematis": 81,
+    "colt's foot": 11,
+    "columbine": 83,
+    "common dandelion": 49,
+    "corn poppy": 25,
+    "cyclamen": 87,
+    "daffodil": 41,
+    "desert-rose": 84,
+    "english marigold": 4,
+    "fire lily": 20,
+    "foxglove": 93,
+    "frangipani": 80,
+    "fritillary": 22,
+    "garden phlox": 31,
+    "gaura": 56,
+    "gazania": 70,
+    "geranium": 57,
+    "giant white arum lily": 19,
+    "globe thistle": 9,
+    "globe-flower": 15,
+    "grape hyacinth": 24,
+    "great masterwort": 37,
+    "hard-leaved pocket orchid": 1,
+    "hibiscus": 82,
+    "hippeastrum": 90,
+    "japanese anemone": 61,
+    "king protea": 12,
+    "lenten rose": 39,
+    "lotus": 77,
+    "love in the mist": 32,
+    "magnolia": 86,
+    "mallow": 96,
+    "marigold": 46,
+    "mexican aster": 33,
+    "mexican petunia": 97,
+    "monkshood": 8,
+    "moon orchid": 6,
+    "morning glory": 75,
+    "orange dahlia": 58,
+    "osteospermum": 65,
+    "oxeye daisy": 48,
+    "passion flower": 76,
+    "pelargonium": 54,
+    "peruvian lily": 17,
+    "petunia": 50,
+    "pincushion flower": 21,
+    "pink primrose": 0,
+    "pink-yellow dahlia?": 59,
+    "poinsettia": 43,
+    "primula": 52,
+    "prince of wales feathers": 26,
+    "purple coneflower": 16,
+    "red ginger": 23,
+    "rose": 73,
+    "ruby-lipped cattleya": 35,
+    "siam tulip": 38,
+    "silverbush": 63,
+    "snapdragon": 10,
+    "spear thistle": 13,
+    "spring crocus": 66,
+    "stemless gentian": 27,
+    "sunflower": 53,
+    "sweet pea": 3,
+    "sweet william": 29,
+    "sword lily": 42,
+    "thorn apple": 74,
+    "tiger lily": 5,
+    "toad lily": 78,
+    "tree mallow": 85,
+    "tree poppy": 69,
+    "trumpet creeper": 100,
+    "wallflower": 45,
+    "water lily": 72,
+    "watercress": 88,
+    "wild pansy": 51,
+    "windflower": 68,
+    "yellow iris": 14
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-oxford_flowers102-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet50-oxford_flowers102-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-oxford_flowers102-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-pcam-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/README.md b/resnet50-pcam-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..617925b862a29abdbe23a87a3e8b6c0aa6125129
--- /dev/null
+++ b/resnet50-pcam-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset pcam.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: pcam
+    pretrained: true
+test_datasets: null
+train_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: train
+type: transformers
+val_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: test
+```
+
diff --git a/resnet50-pcam-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/config.json b/resnet50-pcam-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..4b0ac74d3d8fd86ac59d6ac1791d9e00ac89d34c
--- /dev/null
+++ b/resnet50-pcam-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "lymph node",
+    "1": "lymph node containing metastatic tumor tissue"
+  },
+  "label2id": {
+    "lymph node": 0,
+    "lymph node containing metastatic tumor tissue": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-pcam-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet50-pcam-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-pcam-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-pcam-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/README.md b/resnet50-pcam-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..df8c87a7e54ea55a972b98415487bb4fa4286cf5
--- /dev/null
+++ b/resnet50-pcam-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset pcam.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: pcam
+    pretrained: true
+test_datasets: null
+train_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: train
+type: transformers
+val_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: test
+```
+
diff --git a/resnet50-pcam-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/config.json b/resnet50-pcam-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..4b0ac74d3d8fd86ac59d6ac1791d9e00ac89d34c
--- /dev/null
+++ b/resnet50-pcam-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "lymph node",
+    "1": "lymph node containing metastatic tumor tissue"
+  },
+  "label2id": {
+    "lymph node": 0,
+    "lymph node containing metastatic tumor tissue": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-pcam-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet50-pcam-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-pcam-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-pcam-batch_size_256_lr_0.01_training_data_ratio_0.8-1000/README.md b/resnet50-pcam-batch_size_256_lr_0.01_training_data_ratio_0.8-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..a298a91cfb3b4dbf02b3220fa2b1e4cd560dfc06
--- /dev/null
+++ b/resnet50-pcam-batch_size_256_lr_0.01_training_data_ratio_0.8-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset pcam.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: pcam
+    pretrained: true
+test_datasets: null
+train_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: train
+type: transformers
+val_datasets:
+  pcam:
+    _target_: datasets.load_dataset
+    path: 1aurent/PatchCamelyon
+    split: test
+```
+
diff --git a/resnet50-pcam-batch_size_256_lr_0.01_training_data_ratio_0.8-1000/config.json b/resnet50-pcam-batch_size_256_lr_0.01_training_data_ratio_0.8-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..4b0ac74d3d8fd86ac59d6ac1791d9e00ac89d34c
--- /dev/null
+++ b/resnet50-pcam-batch_size_256_lr_0.01_training_data_ratio_0.8-1000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "lymph node",
+    "1": "lymph node containing metastatic tumor tissue"
+  },
+  "label2id": {
+    "lymph node": 0,
+    "lymph node containing metastatic tumor tissue": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-pcam-batch_size_256_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet50-pcam-batch_size_256_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-pcam-batch_size_256_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/README.md b/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..549a16e02bad0ccfbc7f8a9b28aeb1f706b14d08
--- /dev/null
+++ b/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset rendered-sst2.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: rendered-sst2
+    pretrained: true
+test_datasets: null
+train_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: train
+type: transformers
+val_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: test
+```
+
diff --git a/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/config.json b/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8e2d395685cee2a9c76c2b7224752720ae236c37
--- /dev/null
+++ b/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "negative",
+    "1": "positive"
+  },
+  "label2id": {
+    "negative": 0,
+    "positive": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/README.md b/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..71a0cc97806f5984caa901708115e20a7c882734
--- /dev/null
+++ b/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset rendered-sst2.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: rendered-sst2
+    pretrained: true
+test_datasets: null
+train_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: train
+type: transformers
+val_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: test
+```
+
diff --git a/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/config.json b/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8e2d395685cee2a9c76c2b7224752720ae236c37
--- /dev/null
+++ b/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "negative",
+    "1": "positive"
+  },
+  "label2id": {
+    "negative": 0,
+    "positive": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/README.md b/resnet50-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..49602a1def5c280aab10b587c37a260e8f29711e
--- /dev/null
+++ b/resnet50-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset rendered-sst2.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: rendered-sst2
+    pretrained: true
+test_datasets: null
+train_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: train
+type: transformers
+val_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: test
+```
+
diff --git a/resnet50-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/config.json b/resnet50-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8e2d395685cee2a9c76c2b7224752720ae236c37
--- /dev/null
+++ b/resnet50-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "negative",
+    "1": "positive"
+  },
+  "label2id": {
+    "negative": 0,
+    "positive": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet50-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-rendered-sst2-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/README.md b/resnet50-rendered-sst2-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..aef2bab900ebe48fd387c9b87ed3f4217ed35c7a
--- /dev/null
+++ b/resnet50-rendered-sst2-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset rendered-sst2.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: rendered-sst2
+    pretrained: true
+test_datasets: null
+train_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: train
+type: transformers
+val_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: test
+```
+
diff --git a/resnet50-rendered-sst2-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/config.json b/resnet50-rendered-sst2-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8e2d395685cee2a9c76c2b7224752720ae236c37
--- /dev/null
+++ b/resnet50-rendered-sst2-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "negative",
+    "1": "positive"
+  },
+  "label2id": {
+    "negative": 0,
+    "positive": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-rendered-sst2-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet50-rendered-sst2-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-rendered-sst2-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-rendered-sst2-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/README.md b/resnet50-rendered-sst2-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..1d64ad7d40d3b47e0e05a3729a0c8152eeeb18dd
--- /dev/null
+++ b/resnet50-rendered-sst2-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset rendered-sst2.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: rendered-sst2
+    pretrained: true
+test_datasets: null
+train_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: train
+type: transformers
+val_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: test
+```
+
diff --git a/resnet50-rendered-sst2-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/config.json b/resnet50-rendered-sst2-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8e2d395685cee2a9c76c2b7224752720ae236c37
--- /dev/null
+++ b/resnet50-rendered-sst2-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "negative",
+    "1": "positive"
+  },
+  "label2id": {
+    "negative": 0,
+    "positive": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-rendered-sst2-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet50-rendered-sst2-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-rendered-sst2-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/README.md b/resnet50-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..fa9e322d107da3bca054884e5d9b707471d60494
--- /dev/null
+++ b/resnet50-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset rendered-sst2.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: rendered-sst2
+    pretrained: true
+test_datasets: null
+train_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: train
+type: transformers
+val_datasets:
+  rendered-sst2:
+    _target_: datasets.load_dataset
+    path: nateraw/rendered-sst2
+    split: test
+```
+
diff --git a/resnet50-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/config.json b/resnet50-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8e2d395685cee2a9c76c2b7224752720ae236c37
--- /dev/null
+++ b/resnet50-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "negative",
+    "1": "positive"
+  },
+  "label2id": {
+    "negative": 0,
+    "positive": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet50-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-rendered-sst2-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/config.json b/resnet50-rendered-sst2-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8e2d395685cee2a9c76c2b7224752720ae236c37
--- /dev/null
+++ b/resnet50-rendered-sst2-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,47 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "negative",
+    "1": "positive"
+  },
+  "label2id": {
+    "negative": 0,
+    "positive": 1
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-rendered-sst2-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet50-rendered-sst2-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-rendered-sst2-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-resisc45-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/README.md b/resnet50-resisc45-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..b9fe04566b73031f39bd65f0d4d7aeb3d7f66709
--- /dev/null
+++ b/resnet50-resisc45-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset resisc45.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: resisc45
+    pretrained: true
+test_datasets: null
+train_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: train
+type: transformers
+val_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: test
+```
+
diff --git a/resnet50-resisc45-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/config.json b/resnet50-resisc45-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..f19cd9d15140683527543a4e276977d9a205e4b4
--- /dev/null
+++ b/resnet50-resisc45-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,133 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "airport",
+    "2": "baseball diamond",
+    "3": "basketball court",
+    "4": "beach",
+    "5": "bridge",
+    "6": "chaparral",
+    "7": "church",
+    "8": "circular farmland",
+    "9": "cloud",
+    "10": "commercial area",
+    "11": "dense residential",
+    "12": "desert",
+    "13": "forest",
+    "14": "freeway",
+    "15": "golf course",
+    "16": "ground track field",
+    "17": "harbor",
+    "18": "industrial area",
+    "19": "intersection",
+    "20": "island",
+    "21": "lake",
+    "22": "meadow",
+    "23": "medium residential",
+    "24": "mobile home park",
+    "25": "mountain",
+    "26": "overpass",
+    "27": "palace",
+    "28": "parking lot",
+    "29": "railway",
+    "30": "railway station",
+    "31": "rectangular farmland",
+    "32": "river",
+    "33": "roundabout",
+    "34": "runway",
+    "35": "sea ice",
+    "36": "ship",
+    "37": "snowberg",
+    "38": "sparse residential",
+    "39": "stadium",
+    "40": "storage tank",
+    "41": "tennis court",
+    "42": "terrace",
+    "43": "thermal power station",
+    "44": "wetland"
+  },
+  "label2id": {
+    "airplane": 0,
+    "airport": 1,
+    "baseball diamond": 2,
+    "basketball court": 3,
+    "beach": 4,
+    "bridge": 5,
+    "chaparral": 6,
+    "church": 7,
+    "circular farmland": 8,
+    "cloud": 9,
+    "commercial area": 10,
+    "dense residential": 11,
+    "desert": 12,
+    "forest": 13,
+    "freeway": 14,
+    "golf course": 15,
+    "ground track field": 16,
+    "harbor": 17,
+    "industrial area": 18,
+    "intersection": 19,
+    "island": 20,
+    "lake": 21,
+    "meadow": 22,
+    "medium residential": 23,
+    "mobile home park": 24,
+    "mountain": 25,
+    "overpass": 26,
+    "palace": 27,
+    "parking lot": 28,
+    "railway": 29,
+    "railway station": 30,
+    "rectangular farmland": 31,
+    "river": 32,
+    "roundabout": 33,
+    "runway": 34,
+    "sea ice": 35,
+    "ship": 36,
+    "snowberg": 37,
+    "sparse residential": 38,
+    "stadium": 39,
+    "storage tank": 40,
+    "tennis court": 41,
+    "terrace": 42,
+    "thermal power station": 43,
+    "wetland": 44
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-resisc45-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet50-resisc45-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-resisc45-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-resisc45-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/README.md b/resnet50-resisc45-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..cdb209b1cd9c35830b0749c59123d977f6ec1333
--- /dev/null
+++ b/resnet50-resisc45-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset resisc45.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: resisc45
+    pretrained: true
+test_datasets: null
+train_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: train
+type: transformers
+val_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: test
+```
+
diff --git a/resnet50-resisc45-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/config.json b/resnet50-resisc45-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..f19cd9d15140683527543a4e276977d9a205e4b4
--- /dev/null
+++ b/resnet50-resisc45-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,133 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "airport",
+    "2": "baseball diamond",
+    "3": "basketball court",
+    "4": "beach",
+    "5": "bridge",
+    "6": "chaparral",
+    "7": "church",
+    "8": "circular farmland",
+    "9": "cloud",
+    "10": "commercial area",
+    "11": "dense residential",
+    "12": "desert",
+    "13": "forest",
+    "14": "freeway",
+    "15": "golf course",
+    "16": "ground track field",
+    "17": "harbor",
+    "18": "industrial area",
+    "19": "intersection",
+    "20": "island",
+    "21": "lake",
+    "22": "meadow",
+    "23": "medium residential",
+    "24": "mobile home park",
+    "25": "mountain",
+    "26": "overpass",
+    "27": "palace",
+    "28": "parking lot",
+    "29": "railway",
+    "30": "railway station",
+    "31": "rectangular farmland",
+    "32": "river",
+    "33": "roundabout",
+    "34": "runway",
+    "35": "sea ice",
+    "36": "ship",
+    "37": "snowberg",
+    "38": "sparse residential",
+    "39": "stadium",
+    "40": "storage tank",
+    "41": "tennis court",
+    "42": "terrace",
+    "43": "thermal power station",
+    "44": "wetland"
+  },
+  "label2id": {
+    "airplane": 0,
+    "airport": 1,
+    "baseball diamond": 2,
+    "basketball court": 3,
+    "beach": 4,
+    "bridge": 5,
+    "chaparral": 6,
+    "church": 7,
+    "circular farmland": 8,
+    "cloud": 9,
+    "commercial area": 10,
+    "dense residential": 11,
+    "desert": 12,
+    "forest": 13,
+    "freeway": 14,
+    "golf course": 15,
+    "ground track field": 16,
+    "harbor": 17,
+    "industrial area": 18,
+    "intersection": 19,
+    "island": 20,
+    "lake": 21,
+    "meadow": 22,
+    "medium residential": 23,
+    "mobile home park": 24,
+    "mountain": 25,
+    "overpass": 26,
+    "palace": 27,
+    "parking lot": 28,
+    "railway": 29,
+    "railway station": 30,
+    "rectangular farmland": 31,
+    "river": 32,
+    "roundabout": 33,
+    "runway": 34,
+    "sea ice": 35,
+    "ship": 36,
+    "snowberg": 37,
+    "sparse residential": 38,
+    "stadium": 39,
+    "storage tank": 40,
+    "tennis court": 41,
+    "terrace": 42,
+    "thermal power station": 43,
+    "wetland": 44
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-resisc45-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet50-resisc45-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-resisc45-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/README.md b/resnet50-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..bf3aa17492b5a3f23e57ce8b00400d42078b4386
--- /dev/null
+++ b/resnet50-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset resisc45.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: resisc45
+    pretrained: true
+test_datasets: null
+train_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: train
+type: transformers
+val_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: test
+```
+
diff --git a/resnet50-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/config.json b/resnet50-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..f19cd9d15140683527543a4e276977d9a205e4b4
--- /dev/null
+++ b/resnet50-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,133 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "airport",
+    "2": "baseball diamond",
+    "3": "basketball court",
+    "4": "beach",
+    "5": "bridge",
+    "6": "chaparral",
+    "7": "church",
+    "8": "circular farmland",
+    "9": "cloud",
+    "10": "commercial area",
+    "11": "dense residential",
+    "12": "desert",
+    "13": "forest",
+    "14": "freeway",
+    "15": "golf course",
+    "16": "ground track field",
+    "17": "harbor",
+    "18": "industrial area",
+    "19": "intersection",
+    "20": "island",
+    "21": "lake",
+    "22": "meadow",
+    "23": "medium residential",
+    "24": "mobile home park",
+    "25": "mountain",
+    "26": "overpass",
+    "27": "palace",
+    "28": "parking lot",
+    "29": "railway",
+    "30": "railway station",
+    "31": "rectangular farmland",
+    "32": "river",
+    "33": "roundabout",
+    "34": "runway",
+    "35": "sea ice",
+    "36": "ship",
+    "37": "snowberg",
+    "38": "sparse residential",
+    "39": "stadium",
+    "40": "storage tank",
+    "41": "tennis court",
+    "42": "terrace",
+    "43": "thermal power station",
+    "44": "wetland"
+  },
+  "label2id": {
+    "airplane": 0,
+    "airport": 1,
+    "baseball diamond": 2,
+    "basketball court": 3,
+    "beach": 4,
+    "bridge": 5,
+    "chaparral": 6,
+    "church": 7,
+    "circular farmland": 8,
+    "cloud": 9,
+    "commercial area": 10,
+    "dense residential": 11,
+    "desert": 12,
+    "forest": 13,
+    "freeway": 14,
+    "golf course": 15,
+    "ground track field": 16,
+    "harbor": 17,
+    "industrial area": 18,
+    "intersection": 19,
+    "island": 20,
+    "lake": 21,
+    "meadow": 22,
+    "medium residential": 23,
+    "mobile home park": 24,
+    "mountain": 25,
+    "overpass": 26,
+    "palace": 27,
+    "parking lot": 28,
+    "railway": 29,
+    "railway station": 30,
+    "rectangular farmland": 31,
+    "river": 32,
+    "roundabout": 33,
+    "runway": 34,
+    "sea ice": 35,
+    "ship": 36,
+    "snowberg": 37,
+    "sparse residential": 38,
+    "stadium": 39,
+    "storage tank": 40,
+    "tennis court": 41,
+    "terrace": 42,
+    "thermal power station": 43,
+    "wetland": 44
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet50-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/README.md b/resnet50-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..bf3aa17492b5a3f23e57ce8b00400d42078b4386
--- /dev/null
+++ b/resnet50-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset resisc45.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: resisc45
+    pretrained: true
+test_datasets: null
+train_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: train
+type: transformers
+val_datasets:
+  resisc45:
+    _target_: datasets.load_dataset
+    path: tanganke/resisc45
+    split: test
+```
+
diff --git a/resnet50-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/config.json b/resnet50-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..f19cd9d15140683527543a4e276977d9a205e4b4
--- /dev/null
+++ b/resnet50-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/config.json
@@ -0,0 +1,133 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "airport",
+    "2": "baseball diamond",
+    "3": "basketball court",
+    "4": "beach",
+    "5": "bridge",
+    "6": "chaparral",
+    "7": "church",
+    "8": "circular farmland",
+    "9": "cloud",
+    "10": "commercial area",
+    "11": "dense residential",
+    "12": "desert",
+    "13": "forest",
+    "14": "freeway",
+    "15": "golf course",
+    "16": "ground track field",
+    "17": "harbor",
+    "18": "industrial area",
+    "19": "intersection",
+    "20": "island",
+    "21": "lake",
+    "22": "meadow",
+    "23": "medium residential",
+    "24": "mobile home park",
+    "25": "mountain",
+    "26": "overpass",
+    "27": "palace",
+    "28": "parking lot",
+    "29": "railway",
+    "30": "railway station",
+    "31": "rectangular farmland",
+    "32": "river",
+    "33": "roundabout",
+    "34": "runway",
+    "35": "sea ice",
+    "36": "ship",
+    "37": "snowberg",
+    "38": "sparse residential",
+    "39": "stadium",
+    "40": "storage tank",
+    "41": "tennis court",
+    "42": "terrace",
+    "43": "thermal power station",
+    "44": "wetland"
+  },
+  "label2id": {
+    "airplane": 0,
+    "airport": 1,
+    "baseball diamond": 2,
+    "basketball court": 3,
+    "beach": 4,
+    "bridge": 5,
+    "chaparral": 6,
+    "church": 7,
+    "circular farmland": 8,
+    "cloud": 9,
+    "commercial area": 10,
+    "dense residential": 11,
+    "desert": 12,
+    "forest": 13,
+    "freeway": 14,
+    "golf course": 15,
+    "ground track field": 16,
+    "harbor": 17,
+    "industrial area": 18,
+    "intersection": 19,
+    "island": 20,
+    "lake": 21,
+    "meadow": 22,
+    "medium residential": 23,
+    "mobile home park": 24,
+    "mountain": 25,
+    "overpass": 26,
+    "palace": 27,
+    "parking lot": 28,
+    "railway": 29,
+    "railway station": 30,
+    "rectangular farmland": 31,
+    "river": 32,
+    "roundabout": 33,
+    "runway": 34,
+    "sea ice": 35,
+    "ship": 36,
+    "snowberg": 37,
+    "sparse residential": 38,
+    "stadium": 39,
+    "storage tank": 40,
+    "tennis court": 41,
+    "terrace": 42,
+    "thermal power station": 43,
+    "wetland": 44
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet50-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-resisc45-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-stanford-cars-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/README.md b/resnet50-stanford-cars-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..3880b16bd40ae00fb440771211cfa145775baeb5
--- /dev/null
+++ b/resnet50-stanford-cars-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stanford-cars.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: stanford-cars
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: train
+type: transformers
+val_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: test
+```
+
diff --git a/resnet50-stanford-cars-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/config.json b/resnet50-stanford-cars-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..4ab8a7f592f8381989e1ca00e428926f91d8a1a5
--- /dev/null
+++ b/resnet50-stanford-cars-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,435 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "AM General Hummer SUV 2000",
+    "1": "Acura RL Sedan 2012",
+    "2": "Acura TL Sedan 2012",
+    "3": "Acura TL Type-S 2008",
+    "4": "Acura TSX Sedan 2012",
+    "5": "Acura Integra Type R 2001",
+    "6": "Acura ZDX Hatchback 2012",
+    "7": "Aston Martin V8 Vantage Convertible 2012",
+    "8": "Aston Martin V8 Vantage Coupe 2012",
+    "9": "Aston Martin Virage Convertible 2012",
+    "10": "Aston Martin Virage Coupe 2012",
+    "11": "Audi RS 4 Convertible 2008",
+    "12": "Audi A5 Coupe 2012",
+    "13": "Audi TTS Coupe 2012",
+    "14": "Audi R8 Coupe 2012",
+    "15": "Audi V8 Sedan 1994",
+    "16": "Audi 100 Sedan 1994",
+    "17": "Audi 100 Wagon 1994",
+    "18": "Audi TT Hatchback 2011",
+    "19": "Audi S6 Sedan 2011",
+    "20": "Audi S5 Convertible 2012",
+    "21": "Audi S5 Coupe 2012",
+    "22": "Audi S4 Sedan 2012",
+    "23": "Audi S4 Sedan 2007",
+    "24": "Audi TT RS Coupe 2012",
+    "25": "BMW ActiveHybrid 5 Sedan 2012",
+    "26": "BMW 1 Series Convertible 2012",
+    "27": "BMW 1 Series Coupe 2012",
+    "28": "BMW 3 Series Sedan 2012",
+    "29": "BMW 3 Series Wagon 2012",
+    "30": "BMW 6 Series Convertible 2007",
+    "31": "BMW X5 SUV 2007",
+    "32": "BMW X6 SUV 2012",
+    "33": "BMW M3 Coupe 2012",
+    "34": "BMW M5 Sedan 2010",
+    "35": "BMW M6 Convertible 2010",
+    "36": "BMW X3 SUV 2012",
+    "37": "BMW Z4 Convertible 2012",
+    "38": "Bentley Continental Supersports Conv. Convertible 2012",
+    "39": "Bentley Arnage Sedan 2009",
+    "40": "Bentley Mulsanne Sedan 2011",
+    "41": "Bentley Continental GT Coupe 2012",
+    "42": "Bentley Continental GT Coupe 2007",
+    "43": "Bentley Continental Flying Spur Sedan 2007",
+    "44": "Bugatti Veyron 16.4 Convertible 2009",
+    "45": "Bugatti Veyron 16.4 Coupe 2009",
+    "46": "Buick Regal GS 2012",
+    "47": "Buick Rainier SUV 2007",
+    "48": "Buick Verano Sedan 2012",
+    "49": "Buick Enclave SUV 2012",
+    "50": "Cadillac CTS-V Sedan 2012",
+    "51": "Cadillac SRX SUV 2012",
+    "52": "Cadillac Escalade EXT Crew Cab 2007",
+    "53": "Chevrolet Silverado 1500 Hybrid Crew Cab 2012",
+    "54": "Chevrolet Corvette Convertible 2012",
+    "55": "Chevrolet Corvette ZR1 2012",
+    "56": "Chevrolet Corvette Ron Fellows Edition Z06 2007",
+    "57": "Chevrolet Traverse SUV 2012",
+    "58": "Chevrolet Camaro Convertible 2012",
+    "59": "Chevrolet HHR SS 2010",
+    "60": "Chevrolet Impala Sedan 2007",
+    "61": "Chevrolet Tahoe Hybrid SUV 2012",
+    "62": "Chevrolet Sonic Sedan 2012",
+    "63": "Chevrolet Express Cargo Van 2007",
+    "64": "Chevrolet Avalanche Crew Cab 2012",
+    "65": "Chevrolet Cobalt SS 2010",
+    "66": "Chevrolet Malibu Hybrid Sedan 2010",
+    "67": "Chevrolet TrailBlazer SS 2009",
+    "68": "Chevrolet Silverado 2500HD Regular Cab 2012",
+    "69": "Chevrolet Silverado 1500 Classic Extended Cab 2007",
+    "70": "Chevrolet Express Van 2007",
+    "71": "Chevrolet Monte Carlo Coupe 2007",
+    "72": "Chevrolet Malibu Sedan 2007",
+    "73": "Chevrolet Silverado 1500 Extended Cab 2012",
+    "74": "Chevrolet Silverado 1500 Regular Cab 2012",
+    "75": "Chrysler Aspen SUV 2009",
+    "76": "Chrysler Sebring Convertible 2010",
+    "77": "Chrysler Town and Country Minivan 2012",
+    "78": "Chrysler 300 SRT-8 2010",
+    "79": "Chrysler Crossfire Convertible 2008",
+    "80": "Chrysler PT Cruiser Convertible 2008",
+    "81": "Daewoo Nubira Wagon 2002",
+    "82": "Dodge Caliber Wagon 2012",
+    "83": "Dodge Caliber Wagon 2007",
+    "84": "Dodge Caravan Minivan 1997",
+    "85": "Dodge Ram Pickup 3500 Crew Cab 2010",
+    "86": "Dodge Ram Pickup 3500 Quad Cab 2009",
+    "87": "Dodge Sprinter Cargo Van 2009",
+    "88": "Dodge Journey SUV 2012",
+    "89": "Dodge Dakota Crew Cab 2010",
+    "90": "Dodge Dakota Club Cab 2007",
+    "91": "Dodge Magnum Wagon 2008",
+    "92": "Dodge Challenger SRT8 2011",
+    "93": "Dodge Durango SUV 2012",
+    "94": "Dodge Durango SUV 2007",
+    "95": "Dodge Charger Sedan 2012",
+    "96": "Dodge Charger SRT-8 2009",
+    "97": "Eagle Talon Hatchback 1998",
+    "98": "FIAT 500 Abarth 2012",
+    "99": "FIAT 500 Convertible 2012",
+    "100": "Ferrari FF Coupe 2012",
+    "101": "Ferrari California Convertible 2012",
+    "102": "Ferrari 458 Italia Convertible 2012",
+    "103": "Ferrari 458 Italia Coupe 2012",
+    "104": "Fisker Karma Sedan 2012",
+    "105": "Ford F-450 Super Duty Crew Cab 2012",
+    "106": "Ford Mustang Convertible 2007",
+    "107": "Ford Freestar Minivan 2007",
+    "108": "Ford Expedition EL SUV 2009",
+    "109": "Ford Edge SUV 2012",
+    "110": "Ford Ranger SuperCab 2011",
+    "111": "Ford GT Coupe 2006",
+    "112": "Ford F-150 Regular Cab 2012",
+    "113": "Ford F-150 Regular Cab 2007",
+    "114": "Ford Focus Sedan 2007",
+    "115": "Ford E-Series Wagon Van 2012",
+    "116": "Ford Fiesta Sedan 2012",
+    "117": "GMC Terrain SUV 2012",
+    "118": "GMC Savana Van 2012",
+    "119": "GMC Yukon Hybrid SUV 2012",
+    "120": "GMC Acadia SUV 2012",
+    "121": "GMC Canyon Extended Cab 2012",
+    "122": "Geo Metro Convertible 1993",
+    "123": "HUMMER H3T Crew Cab 2010",
+    "124": "HUMMER H2 SUT Crew Cab 2009",
+    "125": "Honda Odyssey Minivan 2012",
+    "126": "Honda Odyssey Minivan 2007",
+    "127": "Honda Accord Coupe 2012",
+    "128": "Honda Accord Sedan 2012",
+    "129": "Hyundai Veloster Hatchback 2012",
+    "130": "Hyundai Santa Fe SUV 2012",
+    "131": "Hyundai Tucson SUV 2012",
+    "132": "Hyundai Veracruz SUV 2012",
+    "133": "Hyundai Sonata Hybrid Sedan 2012",
+    "134": "Hyundai Elantra Sedan 2007",
+    "135": "Hyundai Accent Sedan 2012",
+    "136": "Hyundai Genesis Sedan 2012",
+    "137": "Hyundai Sonata Sedan 2012",
+    "138": "Hyundai Elantra Touring Hatchback 2012",
+    "139": "Hyundai Azera Sedan 2012",
+    "140": "Infiniti G Coupe IPL 2012",
+    "141": "Infiniti QX56 SUV 2011",
+    "142": "Isuzu Ascender SUV 2008",
+    "143": "Jaguar XK XKR 2012",
+    "144": "Jeep Patriot SUV 2012",
+    "145": "Jeep Wrangler SUV 2012",
+    "146": "Jeep Liberty SUV 2012",
+    "147": "Jeep Grand Cherokee SUV 2012",
+    "148": "Jeep Compass SUV 2012",
+    "149": "Lamborghini Reventon Coupe 2008",
+    "150": "Lamborghini Aventador Coupe 2012",
+    "151": "Lamborghini Gallardo LP 570-4 Superleggera 2012",
+    "152": "Lamborghini Diablo Coupe 2001",
+    "153": "Land Rover Range Rover SUV 2012",
+    "154": "Land Rover LR2 SUV 2012",
+    "155": "Lincoln Town Car Sedan 2011",
+    "156": "MINI Cooper Roadster Convertible 2012",
+    "157": "Maybach Landaulet Convertible 2012",
+    "158": "Mazda Tribute SUV 2011",
+    "159": "McLaren MP4-12C Coupe 2012",
+    "160": "Mercedes-Benz 300-Class Convertible 1993",
+    "161": "Mercedes-Benz C-Class Sedan 2012",
+    "162": "Mercedes-Benz SL-Class Coupe 2009",
+    "163": "Mercedes-Benz E-Class Sedan 2012",
+    "164": "Mercedes-Benz S-Class Sedan 2012",
+    "165": "Mercedes-Benz Sprinter Van 2012",
+    "166": "Mitsubishi Lancer Sedan 2012",
+    "167": "Nissan Leaf Hatchback 2012",
+    "168": "Nissan NV Passenger Van 2012",
+    "169": "Nissan Juke Hatchback 2012",
+    "170": "Nissan 240SX Coupe 1998",
+    "171": "Plymouth Neon Coupe 1999",
+    "172": "Porsche Panamera Sedan 2012",
+    "173": "Ram C/V Cargo Van Minivan 2012",
+    "174": "Rolls-Royce Phantom Drophead Coupe Convertible 2012",
+    "175": "Rolls-Royce Ghost Sedan 2012",
+    "176": "Rolls-Royce Phantom Sedan 2012",
+    "177": "Scion xD Hatchback 2012",
+    "178": "Spyker C8 Convertible 2009",
+    "179": "Spyker C8 Coupe 2009",
+    "180": "Suzuki Aerio Sedan 2007",
+    "181": "Suzuki Kizashi Sedan 2012",
+    "182": "Suzuki SX4 Hatchback 2012",
+    "183": "Suzuki SX4 Sedan 2012",
+    "184": "Tesla Model S Sedan 2012",
+    "185": "Toyota Sequoia SUV 2012",
+    "186": "Toyota Camry Sedan 2012",
+    "187": "Toyota Corolla Sedan 2012",
+    "188": "Toyota 4Runner SUV 2012",
+    "189": "Volkswagen Golf Hatchback 2012",
+    "190": "Volkswagen Golf Hatchback 1991",
+    "191": "Volkswagen Beetle Hatchback 2012",
+    "192": "Volvo C30 Hatchback 2012",
+    "193": "Volvo 240 Sedan 1993",
+    "194": "Volvo XC90 SUV 2007",
+    "195": "smart fortwo Convertible 2012"
+  },
+  "label2id": {
+    "AM General Hummer SUV 2000": 0,
+    "Acura Integra Type R 2001": 5,
+    "Acura RL Sedan 2012": 1,
+    "Acura TL Sedan 2012": 2,
+    "Acura TL Type-S 2008": 3,
+    "Acura TSX Sedan 2012": 4,
+    "Acura ZDX Hatchback 2012": 6,
+    "Aston Martin V8 Vantage Convertible 2012": 7,
+    "Aston Martin V8 Vantage Coupe 2012": 8,
+    "Aston Martin Virage Convertible 2012": 9,
+    "Aston Martin Virage Coupe 2012": 10,
+    "Audi 100 Sedan 1994": 16,
+    "Audi 100 Wagon 1994": 17,
+    "Audi A5 Coupe 2012": 12,
+    "Audi R8 Coupe 2012": 14,
+    "Audi RS 4 Convertible 2008": 11,
+    "Audi S4 Sedan 2007": 23,
+    "Audi S4 Sedan 2012": 22,
+    "Audi S5 Convertible 2012": 20,
+    "Audi S5 Coupe 2012": 21,
+    "Audi S6 Sedan 2011": 19,
+    "Audi TT Hatchback 2011": 18,
+    "Audi TT RS Coupe 2012": 24,
+    "Audi TTS Coupe 2012": 13,
+    "Audi V8 Sedan 1994": 15,
+    "BMW 1 Series Convertible 2012": 26,
+    "BMW 1 Series Coupe 2012": 27,
+    "BMW 3 Series Sedan 2012": 28,
+    "BMW 3 Series Wagon 2012": 29,
+    "BMW 6 Series Convertible 2007": 30,
+    "BMW ActiveHybrid 5 Sedan 2012": 25,
+    "BMW M3 Coupe 2012": 33,
+    "BMW M5 Sedan 2010": 34,
+    "BMW M6 Convertible 2010": 35,
+    "BMW X3 SUV 2012": 36,
+    "BMW X5 SUV 2007": 31,
+    "BMW X6 SUV 2012": 32,
+    "BMW Z4 Convertible 2012": 37,
+    "Bentley Arnage Sedan 2009": 39,
+    "Bentley Continental Flying Spur Sedan 2007": 43,
+    "Bentley Continental GT Coupe 2007": 42,
+    "Bentley Continental GT Coupe 2012": 41,
+    "Bentley Continental Supersports Conv. Convertible 2012": 38,
+    "Bentley Mulsanne Sedan 2011": 40,
+    "Bugatti Veyron 16.4 Convertible 2009": 44,
+    "Bugatti Veyron 16.4 Coupe 2009": 45,
+    "Buick Enclave SUV 2012": 49,
+    "Buick Rainier SUV 2007": 47,
+    "Buick Regal GS 2012": 46,
+    "Buick Verano Sedan 2012": 48,
+    "Cadillac CTS-V Sedan 2012": 50,
+    "Cadillac Escalade EXT Crew Cab 2007": 52,
+    "Cadillac SRX SUV 2012": 51,
+    "Chevrolet Avalanche Crew Cab 2012": 64,
+    "Chevrolet Camaro Convertible 2012": 58,
+    "Chevrolet Cobalt SS 2010": 65,
+    "Chevrolet Corvette Convertible 2012": 54,
+    "Chevrolet Corvette Ron Fellows Edition Z06 2007": 56,
+    "Chevrolet Corvette ZR1 2012": 55,
+    "Chevrolet Express Cargo Van 2007": 63,
+    "Chevrolet Express Van 2007": 70,
+    "Chevrolet HHR SS 2010": 59,
+    "Chevrolet Impala Sedan 2007": 60,
+    "Chevrolet Malibu Hybrid Sedan 2010": 66,
+    "Chevrolet Malibu Sedan 2007": 72,
+    "Chevrolet Monte Carlo Coupe 2007": 71,
+    "Chevrolet Silverado 1500 Classic Extended Cab 2007": 69,
+    "Chevrolet Silverado 1500 Extended Cab 2012": 73,
+    "Chevrolet Silverado 1500 Hybrid Crew Cab 2012": 53,
+    "Chevrolet Silverado 1500 Regular Cab 2012": 74,
+    "Chevrolet Silverado 2500HD Regular Cab 2012": 68,
+    "Chevrolet Sonic Sedan 2012": 62,
+    "Chevrolet Tahoe Hybrid SUV 2012": 61,
+    "Chevrolet TrailBlazer SS 2009": 67,
+    "Chevrolet Traverse SUV 2012": 57,
+    "Chrysler 300 SRT-8 2010": 78,
+    "Chrysler Aspen SUV 2009": 75,
+    "Chrysler Crossfire Convertible 2008": 79,
+    "Chrysler PT Cruiser Convertible 2008": 80,
+    "Chrysler Sebring Convertible 2010": 76,
+    "Chrysler Town and Country Minivan 2012": 77,
+    "Daewoo Nubira Wagon 2002": 81,
+    "Dodge Caliber Wagon 2007": 83,
+    "Dodge Caliber Wagon 2012": 82,
+    "Dodge Caravan Minivan 1997": 84,
+    "Dodge Challenger SRT8 2011": 92,
+    "Dodge Charger SRT-8 2009": 96,
+    "Dodge Charger Sedan 2012": 95,
+    "Dodge Dakota Club Cab 2007": 90,
+    "Dodge Dakota Crew Cab 2010": 89,
+    "Dodge Durango SUV 2007": 94,
+    "Dodge Durango SUV 2012": 93,
+    "Dodge Journey SUV 2012": 88,
+    "Dodge Magnum Wagon 2008": 91,
+    "Dodge Ram Pickup 3500 Crew Cab 2010": 85,
+    "Dodge Ram Pickup 3500 Quad Cab 2009": 86,
+    "Dodge Sprinter Cargo Van 2009": 87,
+    "Eagle Talon Hatchback 1998": 97,
+    "FIAT 500 Abarth 2012": 98,
+    "FIAT 500 Convertible 2012": 99,
+    "Ferrari 458 Italia Convertible 2012": 102,
+    "Ferrari 458 Italia Coupe 2012": 103,
+    "Ferrari California Convertible 2012": 101,
+    "Ferrari FF Coupe 2012": 100,
+    "Fisker Karma Sedan 2012": 104,
+    "Ford E-Series Wagon Van 2012": 115,
+    "Ford Edge SUV 2012": 109,
+    "Ford Expedition EL SUV 2009": 108,
+    "Ford F-150 Regular Cab 2007": 113,
+    "Ford F-150 Regular Cab 2012": 112,
+    "Ford F-450 Super Duty Crew Cab 2012": 105,
+    "Ford Fiesta Sedan 2012": 116,
+    "Ford Focus Sedan 2007": 114,
+    "Ford Freestar Minivan 2007": 107,
+    "Ford GT Coupe 2006": 111,
+    "Ford Mustang Convertible 2007": 106,
+    "Ford Ranger SuperCab 2011": 110,
+    "GMC Acadia SUV 2012": 120,
+    "GMC Canyon Extended Cab 2012": 121,
+    "GMC Savana Van 2012": 118,
+    "GMC Terrain SUV 2012": 117,
+    "GMC Yukon Hybrid SUV 2012": 119,
+    "Geo Metro Convertible 1993": 122,
+    "HUMMER H2 SUT Crew Cab 2009": 124,
+    "HUMMER H3T Crew Cab 2010": 123,
+    "Honda Accord Coupe 2012": 127,
+    "Honda Accord Sedan 2012": 128,
+    "Honda Odyssey Minivan 2007": 126,
+    "Honda Odyssey Minivan 2012": 125,
+    "Hyundai Accent Sedan 2012": 135,
+    "Hyundai Azera Sedan 2012": 139,
+    "Hyundai Elantra Sedan 2007": 134,
+    "Hyundai Elantra Touring Hatchback 2012": 138,
+    "Hyundai Genesis Sedan 2012": 136,
+    "Hyundai Santa Fe SUV 2012": 130,
+    "Hyundai Sonata Hybrid Sedan 2012": 133,
+    "Hyundai Sonata Sedan 2012": 137,
+    "Hyundai Tucson SUV 2012": 131,
+    "Hyundai Veloster Hatchback 2012": 129,
+    "Hyundai Veracruz SUV 2012": 132,
+    "Infiniti G Coupe IPL 2012": 140,
+    "Infiniti QX56 SUV 2011": 141,
+    "Isuzu Ascender SUV 2008": 142,
+    "Jaguar XK XKR 2012": 143,
+    "Jeep Compass SUV 2012": 148,
+    "Jeep Grand Cherokee SUV 2012": 147,
+    "Jeep Liberty SUV 2012": 146,
+    "Jeep Patriot SUV 2012": 144,
+    "Jeep Wrangler SUV 2012": 145,
+    "Lamborghini Aventador Coupe 2012": 150,
+    "Lamborghini Diablo Coupe 2001": 152,
+    "Lamborghini Gallardo LP 570-4 Superleggera 2012": 151,
+    "Lamborghini Reventon Coupe 2008": 149,
+    "Land Rover LR2 SUV 2012": 154,
+    "Land Rover Range Rover SUV 2012": 153,
+    "Lincoln Town Car Sedan 2011": 155,
+    "MINI Cooper Roadster Convertible 2012": 156,
+    "Maybach Landaulet Convertible 2012": 157,
+    "Mazda Tribute SUV 2011": 158,
+    "McLaren MP4-12C Coupe 2012": 159,
+    "Mercedes-Benz 300-Class Convertible 1993": 160,
+    "Mercedes-Benz C-Class Sedan 2012": 161,
+    "Mercedes-Benz E-Class Sedan 2012": 163,
+    "Mercedes-Benz S-Class Sedan 2012": 164,
+    "Mercedes-Benz SL-Class Coupe 2009": 162,
+    "Mercedes-Benz Sprinter Van 2012": 165,
+    "Mitsubishi Lancer Sedan 2012": 166,
+    "Nissan 240SX Coupe 1998": 170,
+    "Nissan Juke Hatchback 2012": 169,
+    "Nissan Leaf Hatchback 2012": 167,
+    "Nissan NV Passenger Van 2012": 168,
+    "Plymouth Neon Coupe 1999": 171,
+    "Porsche Panamera Sedan 2012": 172,
+    "Ram C/V Cargo Van Minivan 2012": 173,
+    "Rolls-Royce Ghost Sedan 2012": 175,
+    "Rolls-Royce Phantom Drophead Coupe Convertible 2012": 174,
+    "Rolls-Royce Phantom Sedan 2012": 176,
+    "Scion xD Hatchback 2012": 177,
+    "Spyker C8 Convertible 2009": 178,
+    "Spyker C8 Coupe 2009": 179,
+    "Suzuki Aerio Sedan 2007": 180,
+    "Suzuki Kizashi Sedan 2012": 181,
+    "Suzuki SX4 Hatchback 2012": 182,
+    "Suzuki SX4 Sedan 2012": 183,
+    "Tesla Model S Sedan 2012": 184,
+    "Toyota 4Runner SUV 2012": 188,
+    "Toyota Camry Sedan 2012": 186,
+    "Toyota Corolla Sedan 2012": 187,
+    "Toyota Sequoia SUV 2012": 185,
+    "Volkswagen Beetle Hatchback 2012": 191,
+    "Volkswagen Golf Hatchback 1991": 190,
+    "Volkswagen Golf Hatchback 2012": 189,
+    "Volvo 240 Sedan 1993": 193,
+    "Volvo C30 Hatchback 2012": 192,
+    "Volvo XC90 SUV 2007": 194,
+    "smart fortwo Convertible 2012": 195
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-stanford-cars-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet50-stanford-cars-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-stanford-cars-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/README.md b/resnet50-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..69bbbc1753f865cfb0b8d68571cc0e178b05505d
--- /dev/null
+++ b/resnet50-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stanford-cars.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: stanford-cars
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: train
+type: transformers
+val_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: test
+```
+
diff --git a/resnet50-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/config.json b/resnet50-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..4ab8a7f592f8381989e1ca00e428926f91d8a1a5
--- /dev/null
+++ b/resnet50-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/config.json
@@ -0,0 +1,435 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "AM General Hummer SUV 2000",
+    "1": "Acura RL Sedan 2012",
+    "2": "Acura TL Sedan 2012",
+    "3": "Acura TL Type-S 2008",
+    "4": "Acura TSX Sedan 2012",
+    "5": "Acura Integra Type R 2001",
+    "6": "Acura ZDX Hatchback 2012",
+    "7": "Aston Martin V8 Vantage Convertible 2012",
+    "8": "Aston Martin V8 Vantage Coupe 2012",
+    "9": "Aston Martin Virage Convertible 2012",
+    "10": "Aston Martin Virage Coupe 2012",
+    "11": "Audi RS 4 Convertible 2008",
+    "12": "Audi A5 Coupe 2012",
+    "13": "Audi TTS Coupe 2012",
+    "14": "Audi R8 Coupe 2012",
+    "15": "Audi V8 Sedan 1994",
+    "16": "Audi 100 Sedan 1994",
+    "17": "Audi 100 Wagon 1994",
+    "18": "Audi TT Hatchback 2011",
+    "19": "Audi S6 Sedan 2011",
+    "20": "Audi S5 Convertible 2012",
+    "21": "Audi S5 Coupe 2012",
+    "22": "Audi S4 Sedan 2012",
+    "23": "Audi S4 Sedan 2007",
+    "24": "Audi TT RS Coupe 2012",
+    "25": "BMW ActiveHybrid 5 Sedan 2012",
+    "26": "BMW 1 Series Convertible 2012",
+    "27": "BMW 1 Series Coupe 2012",
+    "28": "BMW 3 Series Sedan 2012",
+    "29": "BMW 3 Series Wagon 2012",
+    "30": "BMW 6 Series Convertible 2007",
+    "31": "BMW X5 SUV 2007",
+    "32": "BMW X6 SUV 2012",
+    "33": "BMW M3 Coupe 2012",
+    "34": "BMW M5 Sedan 2010",
+    "35": "BMW M6 Convertible 2010",
+    "36": "BMW X3 SUV 2012",
+    "37": "BMW Z4 Convertible 2012",
+    "38": "Bentley Continental Supersports Conv. Convertible 2012",
+    "39": "Bentley Arnage Sedan 2009",
+    "40": "Bentley Mulsanne Sedan 2011",
+    "41": "Bentley Continental GT Coupe 2012",
+    "42": "Bentley Continental GT Coupe 2007",
+    "43": "Bentley Continental Flying Spur Sedan 2007",
+    "44": "Bugatti Veyron 16.4 Convertible 2009",
+    "45": "Bugatti Veyron 16.4 Coupe 2009",
+    "46": "Buick Regal GS 2012",
+    "47": "Buick Rainier SUV 2007",
+    "48": "Buick Verano Sedan 2012",
+    "49": "Buick Enclave SUV 2012",
+    "50": "Cadillac CTS-V Sedan 2012",
+    "51": "Cadillac SRX SUV 2012",
+    "52": "Cadillac Escalade EXT Crew Cab 2007",
+    "53": "Chevrolet Silverado 1500 Hybrid Crew Cab 2012",
+    "54": "Chevrolet Corvette Convertible 2012",
+    "55": "Chevrolet Corvette ZR1 2012",
+    "56": "Chevrolet Corvette Ron Fellows Edition Z06 2007",
+    "57": "Chevrolet Traverse SUV 2012",
+    "58": "Chevrolet Camaro Convertible 2012",
+    "59": "Chevrolet HHR SS 2010",
+    "60": "Chevrolet Impala Sedan 2007",
+    "61": "Chevrolet Tahoe Hybrid SUV 2012",
+    "62": "Chevrolet Sonic Sedan 2012",
+    "63": "Chevrolet Express Cargo Van 2007",
+    "64": "Chevrolet Avalanche Crew Cab 2012",
+    "65": "Chevrolet Cobalt SS 2010",
+    "66": "Chevrolet Malibu Hybrid Sedan 2010",
+    "67": "Chevrolet TrailBlazer SS 2009",
+    "68": "Chevrolet Silverado 2500HD Regular Cab 2012",
+    "69": "Chevrolet Silverado 1500 Classic Extended Cab 2007",
+    "70": "Chevrolet Express Van 2007",
+    "71": "Chevrolet Monte Carlo Coupe 2007",
+    "72": "Chevrolet Malibu Sedan 2007",
+    "73": "Chevrolet Silverado 1500 Extended Cab 2012",
+    "74": "Chevrolet Silverado 1500 Regular Cab 2012",
+    "75": "Chrysler Aspen SUV 2009",
+    "76": "Chrysler Sebring Convertible 2010",
+    "77": "Chrysler Town and Country Minivan 2012",
+    "78": "Chrysler 300 SRT-8 2010",
+    "79": "Chrysler Crossfire Convertible 2008",
+    "80": "Chrysler PT Cruiser Convertible 2008",
+    "81": "Daewoo Nubira Wagon 2002",
+    "82": "Dodge Caliber Wagon 2012",
+    "83": "Dodge Caliber Wagon 2007",
+    "84": "Dodge Caravan Minivan 1997",
+    "85": "Dodge Ram Pickup 3500 Crew Cab 2010",
+    "86": "Dodge Ram Pickup 3500 Quad Cab 2009",
+    "87": "Dodge Sprinter Cargo Van 2009",
+    "88": "Dodge Journey SUV 2012",
+    "89": "Dodge Dakota Crew Cab 2010",
+    "90": "Dodge Dakota Club Cab 2007",
+    "91": "Dodge Magnum Wagon 2008",
+    "92": "Dodge Challenger SRT8 2011",
+    "93": "Dodge Durango SUV 2012",
+    "94": "Dodge Durango SUV 2007",
+    "95": "Dodge Charger Sedan 2012",
+    "96": "Dodge Charger SRT-8 2009",
+    "97": "Eagle Talon Hatchback 1998",
+    "98": "FIAT 500 Abarth 2012",
+    "99": "FIAT 500 Convertible 2012",
+    "100": "Ferrari FF Coupe 2012",
+    "101": "Ferrari California Convertible 2012",
+    "102": "Ferrari 458 Italia Convertible 2012",
+    "103": "Ferrari 458 Italia Coupe 2012",
+    "104": "Fisker Karma Sedan 2012",
+    "105": "Ford F-450 Super Duty Crew Cab 2012",
+    "106": "Ford Mustang Convertible 2007",
+    "107": "Ford Freestar Minivan 2007",
+    "108": "Ford Expedition EL SUV 2009",
+    "109": "Ford Edge SUV 2012",
+    "110": "Ford Ranger SuperCab 2011",
+    "111": "Ford GT Coupe 2006",
+    "112": "Ford F-150 Regular Cab 2012",
+    "113": "Ford F-150 Regular Cab 2007",
+    "114": "Ford Focus Sedan 2007",
+    "115": "Ford E-Series Wagon Van 2012",
+    "116": "Ford Fiesta Sedan 2012",
+    "117": "GMC Terrain SUV 2012",
+    "118": "GMC Savana Van 2012",
+    "119": "GMC Yukon Hybrid SUV 2012",
+    "120": "GMC Acadia SUV 2012",
+    "121": "GMC Canyon Extended Cab 2012",
+    "122": "Geo Metro Convertible 1993",
+    "123": "HUMMER H3T Crew Cab 2010",
+    "124": "HUMMER H2 SUT Crew Cab 2009",
+    "125": "Honda Odyssey Minivan 2012",
+    "126": "Honda Odyssey Minivan 2007",
+    "127": "Honda Accord Coupe 2012",
+    "128": "Honda Accord Sedan 2012",
+    "129": "Hyundai Veloster Hatchback 2012",
+    "130": "Hyundai Santa Fe SUV 2012",
+    "131": "Hyundai Tucson SUV 2012",
+    "132": "Hyundai Veracruz SUV 2012",
+    "133": "Hyundai Sonata Hybrid Sedan 2012",
+    "134": "Hyundai Elantra Sedan 2007",
+    "135": "Hyundai Accent Sedan 2012",
+    "136": "Hyundai Genesis Sedan 2012",
+    "137": "Hyundai Sonata Sedan 2012",
+    "138": "Hyundai Elantra Touring Hatchback 2012",
+    "139": "Hyundai Azera Sedan 2012",
+    "140": "Infiniti G Coupe IPL 2012",
+    "141": "Infiniti QX56 SUV 2011",
+    "142": "Isuzu Ascender SUV 2008",
+    "143": "Jaguar XK XKR 2012",
+    "144": "Jeep Patriot SUV 2012",
+    "145": "Jeep Wrangler SUV 2012",
+    "146": "Jeep Liberty SUV 2012",
+    "147": "Jeep Grand Cherokee SUV 2012",
+    "148": "Jeep Compass SUV 2012",
+    "149": "Lamborghini Reventon Coupe 2008",
+    "150": "Lamborghini Aventador Coupe 2012",
+    "151": "Lamborghini Gallardo LP 570-4 Superleggera 2012",
+    "152": "Lamborghini Diablo Coupe 2001",
+    "153": "Land Rover Range Rover SUV 2012",
+    "154": "Land Rover LR2 SUV 2012",
+    "155": "Lincoln Town Car Sedan 2011",
+    "156": "MINI Cooper Roadster Convertible 2012",
+    "157": "Maybach Landaulet Convertible 2012",
+    "158": "Mazda Tribute SUV 2011",
+    "159": "McLaren MP4-12C Coupe 2012",
+    "160": "Mercedes-Benz 300-Class Convertible 1993",
+    "161": "Mercedes-Benz C-Class Sedan 2012",
+    "162": "Mercedes-Benz SL-Class Coupe 2009",
+    "163": "Mercedes-Benz E-Class Sedan 2012",
+    "164": "Mercedes-Benz S-Class Sedan 2012",
+    "165": "Mercedes-Benz Sprinter Van 2012",
+    "166": "Mitsubishi Lancer Sedan 2012",
+    "167": "Nissan Leaf Hatchback 2012",
+    "168": "Nissan NV Passenger Van 2012",
+    "169": "Nissan Juke Hatchback 2012",
+    "170": "Nissan 240SX Coupe 1998",
+    "171": "Plymouth Neon Coupe 1999",
+    "172": "Porsche Panamera Sedan 2012",
+    "173": "Ram C/V Cargo Van Minivan 2012",
+    "174": "Rolls-Royce Phantom Drophead Coupe Convertible 2012",
+    "175": "Rolls-Royce Ghost Sedan 2012",
+    "176": "Rolls-Royce Phantom Sedan 2012",
+    "177": "Scion xD Hatchback 2012",
+    "178": "Spyker C8 Convertible 2009",
+    "179": "Spyker C8 Coupe 2009",
+    "180": "Suzuki Aerio Sedan 2007",
+    "181": "Suzuki Kizashi Sedan 2012",
+    "182": "Suzuki SX4 Hatchback 2012",
+    "183": "Suzuki SX4 Sedan 2012",
+    "184": "Tesla Model S Sedan 2012",
+    "185": "Toyota Sequoia SUV 2012",
+    "186": "Toyota Camry Sedan 2012",
+    "187": "Toyota Corolla Sedan 2012",
+    "188": "Toyota 4Runner SUV 2012",
+    "189": "Volkswagen Golf Hatchback 2012",
+    "190": "Volkswagen Golf Hatchback 1991",
+    "191": "Volkswagen Beetle Hatchback 2012",
+    "192": "Volvo C30 Hatchback 2012",
+    "193": "Volvo 240 Sedan 1993",
+    "194": "Volvo XC90 SUV 2007",
+    "195": "smart fortwo Convertible 2012"
+  },
+  "label2id": {
+    "AM General Hummer SUV 2000": 0,
+    "Acura Integra Type R 2001": 5,
+    "Acura RL Sedan 2012": 1,
+    "Acura TL Sedan 2012": 2,
+    "Acura TL Type-S 2008": 3,
+    "Acura TSX Sedan 2012": 4,
+    "Acura ZDX Hatchback 2012": 6,
+    "Aston Martin V8 Vantage Convertible 2012": 7,
+    "Aston Martin V8 Vantage Coupe 2012": 8,
+    "Aston Martin Virage Convertible 2012": 9,
+    "Aston Martin Virage Coupe 2012": 10,
+    "Audi 100 Sedan 1994": 16,
+    "Audi 100 Wagon 1994": 17,
+    "Audi A5 Coupe 2012": 12,
+    "Audi R8 Coupe 2012": 14,
+    "Audi RS 4 Convertible 2008": 11,
+    "Audi S4 Sedan 2007": 23,
+    "Audi S4 Sedan 2012": 22,
+    "Audi S5 Convertible 2012": 20,
+    "Audi S5 Coupe 2012": 21,
+    "Audi S6 Sedan 2011": 19,
+    "Audi TT Hatchback 2011": 18,
+    "Audi TT RS Coupe 2012": 24,
+    "Audi TTS Coupe 2012": 13,
+    "Audi V8 Sedan 1994": 15,
+    "BMW 1 Series Convertible 2012": 26,
+    "BMW 1 Series Coupe 2012": 27,
+    "BMW 3 Series Sedan 2012": 28,
+    "BMW 3 Series Wagon 2012": 29,
+    "BMW 6 Series Convertible 2007": 30,
+    "BMW ActiveHybrid 5 Sedan 2012": 25,
+    "BMW M3 Coupe 2012": 33,
+    "BMW M5 Sedan 2010": 34,
+    "BMW M6 Convertible 2010": 35,
+    "BMW X3 SUV 2012": 36,
+    "BMW X5 SUV 2007": 31,
+    "BMW X6 SUV 2012": 32,
+    "BMW Z4 Convertible 2012": 37,
+    "Bentley Arnage Sedan 2009": 39,
+    "Bentley Continental Flying Spur Sedan 2007": 43,
+    "Bentley Continental GT Coupe 2007": 42,
+    "Bentley Continental GT Coupe 2012": 41,
+    "Bentley Continental Supersports Conv. Convertible 2012": 38,
+    "Bentley Mulsanne Sedan 2011": 40,
+    "Bugatti Veyron 16.4 Convertible 2009": 44,
+    "Bugatti Veyron 16.4 Coupe 2009": 45,
+    "Buick Enclave SUV 2012": 49,
+    "Buick Rainier SUV 2007": 47,
+    "Buick Regal GS 2012": 46,
+    "Buick Verano Sedan 2012": 48,
+    "Cadillac CTS-V Sedan 2012": 50,
+    "Cadillac Escalade EXT Crew Cab 2007": 52,
+    "Cadillac SRX SUV 2012": 51,
+    "Chevrolet Avalanche Crew Cab 2012": 64,
+    "Chevrolet Camaro Convertible 2012": 58,
+    "Chevrolet Cobalt SS 2010": 65,
+    "Chevrolet Corvette Convertible 2012": 54,
+    "Chevrolet Corvette Ron Fellows Edition Z06 2007": 56,
+    "Chevrolet Corvette ZR1 2012": 55,
+    "Chevrolet Express Cargo Van 2007": 63,
+    "Chevrolet Express Van 2007": 70,
+    "Chevrolet HHR SS 2010": 59,
+    "Chevrolet Impala Sedan 2007": 60,
+    "Chevrolet Malibu Hybrid Sedan 2010": 66,
+    "Chevrolet Malibu Sedan 2007": 72,
+    "Chevrolet Monte Carlo Coupe 2007": 71,
+    "Chevrolet Silverado 1500 Classic Extended Cab 2007": 69,
+    "Chevrolet Silverado 1500 Extended Cab 2012": 73,
+    "Chevrolet Silverado 1500 Hybrid Crew Cab 2012": 53,
+    "Chevrolet Silverado 1500 Regular Cab 2012": 74,
+    "Chevrolet Silverado 2500HD Regular Cab 2012": 68,
+    "Chevrolet Sonic Sedan 2012": 62,
+    "Chevrolet Tahoe Hybrid SUV 2012": 61,
+    "Chevrolet TrailBlazer SS 2009": 67,
+    "Chevrolet Traverse SUV 2012": 57,
+    "Chrysler 300 SRT-8 2010": 78,
+    "Chrysler Aspen SUV 2009": 75,
+    "Chrysler Crossfire Convertible 2008": 79,
+    "Chrysler PT Cruiser Convertible 2008": 80,
+    "Chrysler Sebring Convertible 2010": 76,
+    "Chrysler Town and Country Minivan 2012": 77,
+    "Daewoo Nubira Wagon 2002": 81,
+    "Dodge Caliber Wagon 2007": 83,
+    "Dodge Caliber Wagon 2012": 82,
+    "Dodge Caravan Minivan 1997": 84,
+    "Dodge Challenger SRT8 2011": 92,
+    "Dodge Charger SRT-8 2009": 96,
+    "Dodge Charger Sedan 2012": 95,
+    "Dodge Dakota Club Cab 2007": 90,
+    "Dodge Dakota Crew Cab 2010": 89,
+    "Dodge Durango SUV 2007": 94,
+    "Dodge Durango SUV 2012": 93,
+    "Dodge Journey SUV 2012": 88,
+    "Dodge Magnum Wagon 2008": 91,
+    "Dodge Ram Pickup 3500 Crew Cab 2010": 85,
+    "Dodge Ram Pickup 3500 Quad Cab 2009": 86,
+    "Dodge Sprinter Cargo Van 2009": 87,
+    "Eagle Talon Hatchback 1998": 97,
+    "FIAT 500 Abarth 2012": 98,
+    "FIAT 500 Convertible 2012": 99,
+    "Ferrari 458 Italia Convertible 2012": 102,
+    "Ferrari 458 Italia Coupe 2012": 103,
+    "Ferrari California Convertible 2012": 101,
+    "Ferrari FF Coupe 2012": 100,
+    "Fisker Karma Sedan 2012": 104,
+    "Ford E-Series Wagon Van 2012": 115,
+    "Ford Edge SUV 2012": 109,
+    "Ford Expedition EL SUV 2009": 108,
+    "Ford F-150 Regular Cab 2007": 113,
+    "Ford F-150 Regular Cab 2012": 112,
+    "Ford F-450 Super Duty Crew Cab 2012": 105,
+    "Ford Fiesta Sedan 2012": 116,
+    "Ford Focus Sedan 2007": 114,
+    "Ford Freestar Minivan 2007": 107,
+    "Ford GT Coupe 2006": 111,
+    "Ford Mustang Convertible 2007": 106,
+    "Ford Ranger SuperCab 2011": 110,
+    "GMC Acadia SUV 2012": 120,
+    "GMC Canyon Extended Cab 2012": 121,
+    "GMC Savana Van 2012": 118,
+    "GMC Terrain SUV 2012": 117,
+    "GMC Yukon Hybrid SUV 2012": 119,
+    "Geo Metro Convertible 1993": 122,
+    "HUMMER H2 SUT Crew Cab 2009": 124,
+    "HUMMER H3T Crew Cab 2010": 123,
+    "Honda Accord Coupe 2012": 127,
+    "Honda Accord Sedan 2012": 128,
+    "Honda Odyssey Minivan 2007": 126,
+    "Honda Odyssey Minivan 2012": 125,
+    "Hyundai Accent Sedan 2012": 135,
+    "Hyundai Azera Sedan 2012": 139,
+    "Hyundai Elantra Sedan 2007": 134,
+    "Hyundai Elantra Touring Hatchback 2012": 138,
+    "Hyundai Genesis Sedan 2012": 136,
+    "Hyundai Santa Fe SUV 2012": 130,
+    "Hyundai Sonata Hybrid Sedan 2012": 133,
+    "Hyundai Sonata Sedan 2012": 137,
+    "Hyundai Tucson SUV 2012": 131,
+    "Hyundai Veloster Hatchback 2012": 129,
+    "Hyundai Veracruz SUV 2012": 132,
+    "Infiniti G Coupe IPL 2012": 140,
+    "Infiniti QX56 SUV 2011": 141,
+    "Isuzu Ascender SUV 2008": 142,
+    "Jaguar XK XKR 2012": 143,
+    "Jeep Compass SUV 2012": 148,
+    "Jeep Grand Cherokee SUV 2012": 147,
+    "Jeep Liberty SUV 2012": 146,
+    "Jeep Patriot SUV 2012": 144,
+    "Jeep Wrangler SUV 2012": 145,
+    "Lamborghini Aventador Coupe 2012": 150,
+    "Lamborghini Diablo Coupe 2001": 152,
+    "Lamborghini Gallardo LP 570-4 Superleggera 2012": 151,
+    "Lamborghini Reventon Coupe 2008": 149,
+    "Land Rover LR2 SUV 2012": 154,
+    "Land Rover Range Rover SUV 2012": 153,
+    "Lincoln Town Car Sedan 2011": 155,
+    "MINI Cooper Roadster Convertible 2012": 156,
+    "Maybach Landaulet Convertible 2012": 157,
+    "Mazda Tribute SUV 2011": 158,
+    "McLaren MP4-12C Coupe 2012": 159,
+    "Mercedes-Benz 300-Class Convertible 1993": 160,
+    "Mercedes-Benz C-Class Sedan 2012": 161,
+    "Mercedes-Benz E-Class Sedan 2012": 163,
+    "Mercedes-Benz S-Class Sedan 2012": 164,
+    "Mercedes-Benz SL-Class Coupe 2009": 162,
+    "Mercedes-Benz Sprinter Van 2012": 165,
+    "Mitsubishi Lancer Sedan 2012": 166,
+    "Nissan 240SX Coupe 1998": 170,
+    "Nissan Juke Hatchback 2012": 169,
+    "Nissan Leaf Hatchback 2012": 167,
+    "Nissan NV Passenger Van 2012": 168,
+    "Plymouth Neon Coupe 1999": 171,
+    "Porsche Panamera Sedan 2012": 172,
+    "Ram C/V Cargo Van Minivan 2012": 173,
+    "Rolls-Royce Ghost Sedan 2012": 175,
+    "Rolls-Royce Phantom Drophead Coupe Convertible 2012": 174,
+    "Rolls-Royce Phantom Sedan 2012": 176,
+    "Scion xD Hatchback 2012": 177,
+    "Spyker C8 Convertible 2009": 178,
+    "Spyker C8 Coupe 2009": 179,
+    "Suzuki Aerio Sedan 2007": 180,
+    "Suzuki Kizashi Sedan 2012": 181,
+    "Suzuki SX4 Hatchback 2012": 182,
+    "Suzuki SX4 Sedan 2012": 183,
+    "Tesla Model S Sedan 2012": 184,
+    "Toyota 4Runner SUV 2012": 188,
+    "Toyota Camry Sedan 2012": 186,
+    "Toyota Corolla Sedan 2012": 187,
+    "Toyota Sequoia SUV 2012": 185,
+    "Volkswagen Beetle Hatchback 2012": 191,
+    "Volkswagen Golf Hatchback 1991": 190,
+    "Volkswagen Golf Hatchback 2012": 189,
+    "Volvo 240 Sedan 1993": 193,
+    "Volvo C30 Hatchback 2012": 192,
+    "Volvo XC90 SUV 2007": 194,
+    "smart fortwo Convertible 2012": 195
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet50-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-stanford-cars-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-stanford-cars-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/README.md b/resnet50-stanford-cars-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..dced98ddf6d13b5a98fa92070f10efc433f507e2
--- /dev/null
+++ b/resnet50-stanford-cars-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stanford-cars.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: stanford-cars
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: train
+type: transformers
+val_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: test
+```
+
diff --git a/resnet50-stanford-cars-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/config.json b/resnet50-stanford-cars-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..4ab8a7f592f8381989e1ca00e428926f91d8a1a5
--- /dev/null
+++ b/resnet50-stanford-cars-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/config.json
@@ -0,0 +1,435 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "AM General Hummer SUV 2000",
+    "1": "Acura RL Sedan 2012",
+    "2": "Acura TL Sedan 2012",
+    "3": "Acura TL Type-S 2008",
+    "4": "Acura TSX Sedan 2012",
+    "5": "Acura Integra Type R 2001",
+    "6": "Acura ZDX Hatchback 2012",
+    "7": "Aston Martin V8 Vantage Convertible 2012",
+    "8": "Aston Martin V8 Vantage Coupe 2012",
+    "9": "Aston Martin Virage Convertible 2012",
+    "10": "Aston Martin Virage Coupe 2012",
+    "11": "Audi RS 4 Convertible 2008",
+    "12": "Audi A5 Coupe 2012",
+    "13": "Audi TTS Coupe 2012",
+    "14": "Audi R8 Coupe 2012",
+    "15": "Audi V8 Sedan 1994",
+    "16": "Audi 100 Sedan 1994",
+    "17": "Audi 100 Wagon 1994",
+    "18": "Audi TT Hatchback 2011",
+    "19": "Audi S6 Sedan 2011",
+    "20": "Audi S5 Convertible 2012",
+    "21": "Audi S5 Coupe 2012",
+    "22": "Audi S4 Sedan 2012",
+    "23": "Audi S4 Sedan 2007",
+    "24": "Audi TT RS Coupe 2012",
+    "25": "BMW ActiveHybrid 5 Sedan 2012",
+    "26": "BMW 1 Series Convertible 2012",
+    "27": "BMW 1 Series Coupe 2012",
+    "28": "BMW 3 Series Sedan 2012",
+    "29": "BMW 3 Series Wagon 2012",
+    "30": "BMW 6 Series Convertible 2007",
+    "31": "BMW X5 SUV 2007",
+    "32": "BMW X6 SUV 2012",
+    "33": "BMW M3 Coupe 2012",
+    "34": "BMW M5 Sedan 2010",
+    "35": "BMW M6 Convertible 2010",
+    "36": "BMW X3 SUV 2012",
+    "37": "BMW Z4 Convertible 2012",
+    "38": "Bentley Continental Supersports Conv. Convertible 2012",
+    "39": "Bentley Arnage Sedan 2009",
+    "40": "Bentley Mulsanne Sedan 2011",
+    "41": "Bentley Continental GT Coupe 2012",
+    "42": "Bentley Continental GT Coupe 2007",
+    "43": "Bentley Continental Flying Spur Sedan 2007",
+    "44": "Bugatti Veyron 16.4 Convertible 2009",
+    "45": "Bugatti Veyron 16.4 Coupe 2009",
+    "46": "Buick Regal GS 2012",
+    "47": "Buick Rainier SUV 2007",
+    "48": "Buick Verano Sedan 2012",
+    "49": "Buick Enclave SUV 2012",
+    "50": "Cadillac CTS-V Sedan 2012",
+    "51": "Cadillac SRX SUV 2012",
+    "52": "Cadillac Escalade EXT Crew Cab 2007",
+    "53": "Chevrolet Silverado 1500 Hybrid Crew Cab 2012",
+    "54": "Chevrolet Corvette Convertible 2012",
+    "55": "Chevrolet Corvette ZR1 2012",
+    "56": "Chevrolet Corvette Ron Fellows Edition Z06 2007",
+    "57": "Chevrolet Traverse SUV 2012",
+    "58": "Chevrolet Camaro Convertible 2012",
+    "59": "Chevrolet HHR SS 2010",
+    "60": "Chevrolet Impala Sedan 2007",
+    "61": "Chevrolet Tahoe Hybrid SUV 2012",
+    "62": "Chevrolet Sonic Sedan 2012",
+    "63": "Chevrolet Express Cargo Van 2007",
+    "64": "Chevrolet Avalanche Crew Cab 2012",
+    "65": "Chevrolet Cobalt SS 2010",
+    "66": "Chevrolet Malibu Hybrid Sedan 2010",
+    "67": "Chevrolet TrailBlazer SS 2009",
+    "68": "Chevrolet Silverado 2500HD Regular Cab 2012",
+    "69": "Chevrolet Silverado 1500 Classic Extended Cab 2007",
+    "70": "Chevrolet Express Van 2007",
+    "71": "Chevrolet Monte Carlo Coupe 2007",
+    "72": "Chevrolet Malibu Sedan 2007",
+    "73": "Chevrolet Silverado 1500 Extended Cab 2012",
+    "74": "Chevrolet Silverado 1500 Regular Cab 2012",
+    "75": "Chrysler Aspen SUV 2009",
+    "76": "Chrysler Sebring Convertible 2010",
+    "77": "Chrysler Town and Country Minivan 2012",
+    "78": "Chrysler 300 SRT-8 2010",
+    "79": "Chrysler Crossfire Convertible 2008",
+    "80": "Chrysler PT Cruiser Convertible 2008",
+    "81": "Daewoo Nubira Wagon 2002",
+    "82": "Dodge Caliber Wagon 2012",
+    "83": "Dodge Caliber Wagon 2007",
+    "84": "Dodge Caravan Minivan 1997",
+    "85": "Dodge Ram Pickup 3500 Crew Cab 2010",
+    "86": "Dodge Ram Pickup 3500 Quad Cab 2009",
+    "87": "Dodge Sprinter Cargo Van 2009",
+    "88": "Dodge Journey SUV 2012",
+    "89": "Dodge Dakota Crew Cab 2010",
+    "90": "Dodge Dakota Club Cab 2007",
+    "91": "Dodge Magnum Wagon 2008",
+    "92": "Dodge Challenger SRT8 2011",
+    "93": "Dodge Durango SUV 2012",
+    "94": "Dodge Durango SUV 2007",
+    "95": "Dodge Charger Sedan 2012",
+    "96": "Dodge Charger SRT-8 2009",
+    "97": "Eagle Talon Hatchback 1998",
+    "98": "FIAT 500 Abarth 2012",
+    "99": "FIAT 500 Convertible 2012",
+    "100": "Ferrari FF Coupe 2012",
+    "101": "Ferrari California Convertible 2012",
+    "102": "Ferrari 458 Italia Convertible 2012",
+    "103": "Ferrari 458 Italia Coupe 2012",
+    "104": "Fisker Karma Sedan 2012",
+    "105": "Ford F-450 Super Duty Crew Cab 2012",
+    "106": "Ford Mustang Convertible 2007",
+    "107": "Ford Freestar Minivan 2007",
+    "108": "Ford Expedition EL SUV 2009",
+    "109": "Ford Edge SUV 2012",
+    "110": "Ford Ranger SuperCab 2011",
+    "111": "Ford GT Coupe 2006",
+    "112": "Ford F-150 Regular Cab 2012",
+    "113": "Ford F-150 Regular Cab 2007",
+    "114": "Ford Focus Sedan 2007",
+    "115": "Ford E-Series Wagon Van 2012",
+    "116": "Ford Fiesta Sedan 2012",
+    "117": "GMC Terrain SUV 2012",
+    "118": "GMC Savana Van 2012",
+    "119": "GMC Yukon Hybrid SUV 2012",
+    "120": "GMC Acadia SUV 2012",
+    "121": "GMC Canyon Extended Cab 2012",
+    "122": "Geo Metro Convertible 1993",
+    "123": "HUMMER H3T Crew Cab 2010",
+    "124": "HUMMER H2 SUT Crew Cab 2009",
+    "125": "Honda Odyssey Minivan 2012",
+    "126": "Honda Odyssey Minivan 2007",
+    "127": "Honda Accord Coupe 2012",
+    "128": "Honda Accord Sedan 2012",
+    "129": "Hyundai Veloster Hatchback 2012",
+    "130": "Hyundai Santa Fe SUV 2012",
+    "131": "Hyundai Tucson SUV 2012",
+    "132": "Hyundai Veracruz SUV 2012",
+    "133": "Hyundai Sonata Hybrid Sedan 2012",
+    "134": "Hyundai Elantra Sedan 2007",
+    "135": "Hyundai Accent Sedan 2012",
+    "136": "Hyundai Genesis Sedan 2012",
+    "137": "Hyundai Sonata Sedan 2012",
+    "138": "Hyundai Elantra Touring Hatchback 2012",
+    "139": "Hyundai Azera Sedan 2012",
+    "140": "Infiniti G Coupe IPL 2012",
+    "141": "Infiniti QX56 SUV 2011",
+    "142": "Isuzu Ascender SUV 2008",
+    "143": "Jaguar XK XKR 2012",
+    "144": "Jeep Patriot SUV 2012",
+    "145": "Jeep Wrangler SUV 2012",
+    "146": "Jeep Liberty SUV 2012",
+    "147": "Jeep Grand Cherokee SUV 2012",
+    "148": "Jeep Compass SUV 2012",
+    "149": "Lamborghini Reventon Coupe 2008",
+    "150": "Lamborghini Aventador Coupe 2012",
+    "151": "Lamborghini Gallardo LP 570-4 Superleggera 2012",
+    "152": "Lamborghini Diablo Coupe 2001",
+    "153": "Land Rover Range Rover SUV 2012",
+    "154": "Land Rover LR2 SUV 2012",
+    "155": "Lincoln Town Car Sedan 2011",
+    "156": "MINI Cooper Roadster Convertible 2012",
+    "157": "Maybach Landaulet Convertible 2012",
+    "158": "Mazda Tribute SUV 2011",
+    "159": "McLaren MP4-12C Coupe 2012",
+    "160": "Mercedes-Benz 300-Class Convertible 1993",
+    "161": "Mercedes-Benz C-Class Sedan 2012",
+    "162": "Mercedes-Benz SL-Class Coupe 2009",
+    "163": "Mercedes-Benz E-Class Sedan 2012",
+    "164": "Mercedes-Benz S-Class Sedan 2012",
+    "165": "Mercedes-Benz Sprinter Van 2012",
+    "166": "Mitsubishi Lancer Sedan 2012",
+    "167": "Nissan Leaf Hatchback 2012",
+    "168": "Nissan NV Passenger Van 2012",
+    "169": "Nissan Juke Hatchback 2012",
+    "170": "Nissan 240SX Coupe 1998",
+    "171": "Plymouth Neon Coupe 1999",
+    "172": "Porsche Panamera Sedan 2012",
+    "173": "Ram C/V Cargo Van Minivan 2012",
+    "174": "Rolls-Royce Phantom Drophead Coupe Convertible 2012",
+    "175": "Rolls-Royce Ghost Sedan 2012",
+    "176": "Rolls-Royce Phantom Sedan 2012",
+    "177": "Scion xD Hatchback 2012",
+    "178": "Spyker C8 Convertible 2009",
+    "179": "Spyker C8 Coupe 2009",
+    "180": "Suzuki Aerio Sedan 2007",
+    "181": "Suzuki Kizashi Sedan 2012",
+    "182": "Suzuki SX4 Hatchback 2012",
+    "183": "Suzuki SX4 Sedan 2012",
+    "184": "Tesla Model S Sedan 2012",
+    "185": "Toyota Sequoia SUV 2012",
+    "186": "Toyota Camry Sedan 2012",
+    "187": "Toyota Corolla Sedan 2012",
+    "188": "Toyota 4Runner SUV 2012",
+    "189": "Volkswagen Golf Hatchback 2012",
+    "190": "Volkswagen Golf Hatchback 1991",
+    "191": "Volkswagen Beetle Hatchback 2012",
+    "192": "Volvo C30 Hatchback 2012",
+    "193": "Volvo 240 Sedan 1993",
+    "194": "Volvo XC90 SUV 2007",
+    "195": "smart fortwo Convertible 2012"
+  },
+  "label2id": {
+    "AM General Hummer SUV 2000": 0,
+    "Acura Integra Type R 2001": 5,
+    "Acura RL Sedan 2012": 1,
+    "Acura TL Sedan 2012": 2,
+    "Acura TL Type-S 2008": 3,
+    "Acura TSX Sedan 2012": 4,
+    "Acura ZDX Hatchback 2012": 6,
+    "Aston Martin V8 Vantage Convertible 2012": 7,
+    "Aston Martin V8 Vantage Coupe 2012": 8,
+    "Aston Martin Virage Convertible 2012": 9,
+    "Aston Martin Virage Coupe 2012": 10,
+    "Audi 100 Sedan 1994": 16,
+    "Audi 100 Wagon 1994": 17,
+    "Audi A5 Coupe 2012": 12,
+    "Audi R8 Coupe 2012": 14,
+    "Audi RS 4 Convertible 2008": 11,
+    "Audi S4 Sedan 2007": 23,
+    "Audi S4 Sedan 2012": 22,
+    "Audi S5 Convertible 2012": 20,
+    "Audi S5 Coupe 2012": 21,
+    "Audi S6 Sedan 2011": 19,
+    "Audi TT Hatchback 2011": 18,
+    "Audi TT RS Coupe 2012": 24,
+    "Audi TTS Coupe 2012": 13,
+    "Audi V8 Sedan 1994": 15,
+    "BMW 1 Series Convertible 2012": 26,
+    "BMW 1 Series Coupe 2012": 27,
+    "BMW 3 Series Sedan 2012": 28,
+    "BMW 3 Series Wagon 2012": 29,
+    "BMW 6 Series Convertible 2007": 30,
+    "BMW ActiveHybrid 5 Sedan 2012": 25,
+    "BMW M3 Coupe 2012": 33,
+    "BMW M5 Sedan 2010": 34,
+    "BMW M6 Convertible 2010": 35,
+    "BMW X3 SUV 2012": 36,
+    "BMW X5 SUV 2007": 31,
+    "BMW X6 SUV 2012": 32,
+    "BMW Z4 Convertible 2012": 37,
+    "Bentley Arnage Sedan 2009": 39,
+    "Bentley Continental Flying Spur Sedan 2007": 43,
+    "Bentley Continental GT Coupe 2007": 42,
+    "Bentley Continental GT Coupe 2012": 41,
+    "Bentley Continental Supersports Conv. Convertible 2012": 38,
+    "Bentley Mulsanne Sedan 2011": 40,
+    "Bugatti Veyron 16.4 Convertible 2009": 44,
+    "Bugatti Veyron 16.4 Coupe 2009": 45,
+    "Buick Enclave SUV 2012": 49,
+    "Buick Rainier SUV 2007": 47,
+    "Buick Regal GS 2012": 46,
+    "Buick Verano Sedan 2012": 48,
+    "Cadillac CTS-V Sedan 2012": 50,
+    "Cadillac Escalade EXT Crew Cab 2007": 52,
+    "Cadillac SRX SUV 2012": 51,
+    "Chevrolet Avalanche Crew Cab 2012": 64,
+    "Chevrolet Camaro Convertible 2012": 58,
+    "Chevrolet Cobalt SS 2010": 65,
+    "Chevrolet Corvette Convertible 2012": 54,
+    "Chevrolet Corvette Ron Fellows Edition Z06 2007": 56,
+    "Chevrolet Corvette ZR1 2012": 55,
+    "Chevrolet Express Cargo Van 2007": 63,
+    "Chevrolet Express Van 2007": 70,
+    "Chevrolet HHR SS 2010": 59,
+    "Chevrolet Impala Sedan 2007": 60,
+    "Chevrolet Malibu Hybrid Sedan 2010": 66,
+    "Chevrolet Malibu Sedan 2007": 72,
+    "Chevrolet Monte Carlo Coupe 2007": 71,
+    "Chevrolet Silverado 1500 Classic Extended Cab 2007": 69,
+    "Chevrolet Silverado 1500 Extended Cab 2012": 73,
+    "Chevrolet Silverado 1500 Hybrid Crew Cab 2012": 53,
+    "Chevrolet Silverado 1500 Regular Cab 2012": 74,
+    "Chevrolet Silverado 2500HD Regular Cab 2012": 68,
+    "Chevrolet Sonic Sedan 2012": 62,
+    "Chevrolet Tahoe Hybrid SUV 2012": 61,
+    "Chevrolet TrailBlazer SS 2009": 67,
+    "Chevrolet Traverse SUV 2012": 57,
+    "Chrysler 300 SRT-8 2010": 78,
+    "Chrysler Aspen SUV 2009": 75,
+    "Chrysler Crossfire Convertible 2008": 79,
+    "Chrysler PT Cruiser Convertible 2008": 80,
+    "Chrysler Sebring Convertible 2010": 76,
+    "Chrysler Town and Country Minivan 2012": 77,
+    "Daewoo Nubira Wagon 2002": 81,
+    "Dodge Caliber Wagon 2007": 83,
+    "Dodge Caliber Wagon 2012": 82,
+    "Dodge Caravan Minivan 1997": 84,
+    "Dodge Challenger SRT8 2011": 92,
+    "Dodge Charger SRT-8 2009": 96,
+    "Dodge Charger Sedan 2012": 95,
+    "Dodge Dakota Club Cab 2007": 90,
+    "Dodge Dakota Crew Cab 2010": 89,
+    "Dodge Durango SUV 2007": 94,
+    "Dodge Durango SUV 2012": 93,
+    "Dodge Journey SUV 2012": 88,
+    "Dodge Magnum Wagon 2008": 91,
+    "Dodge Ram Pickup 3500 Crew Cab 2010": 85,
+    "Dodge Ram Pickup 3500 Quad Cab 2009": 86,
+    "Dodge Sprinter Cargo Van 2009": 87,
+    "Eagle Talon Hatchback 1998": 97,
+    "FIAT 500 Abarth 2012": 98,
+    "FIAT 500 Convertible 2012": 99,
+    "Ferrari 458 Italia Convertible 2012": 102,
+    "Ferrari 458 Italia Coupe 2012": 103,
+    "Ferrari California Convertible 2012": 101,
+    "Ferrari FF Coupe 2012": 100,
+    "Fisker Karma Sedan 2012": 104,
+    "Ford E-Series Wagon Van 2012": 115,
+    "Ford Edge SUV 2012": 109,
+    "Ford Expedition EL SUV 2009": 108,
+    "Ford F-150 Regular Cab 2007": 113,
+    "Ford F-150 Regular Cab 2012": 112,
+    "Ford F-450 Super Duty Crew Cab 2012": 105,
+    "Ford Fiesta Sedan 2012": 116,
+    "Ford Focus Sedan 2007": 114,
+    "Ford Freestar Minivan 2007": 107,
+    "Ford GT Coupe 2006": 111,
+    "Ford Mustang Convertible 2007": 106,
+    "Ford Ranger SuperCab 2011": 110,
+    "GMC Acadia SUV 2012": 120,
+    "GMC Canyon Extended Cab 2012": 121,
+    "GMC Savana Van 2012": 118,
+    "GMC Terrain SUV 2012": 117,
+    "GMC Yukon Hybrid SUV 2012": 119,
+    "Geo Metro Convertible 1993": 122,
+    "HUMMER H2 SUT Crew Cab 2009": 124,
+    "HUMMER H3T Crew Cab 2010": 123,
+    "Honda Accord Coupe 2012": 127,
+    "Honda Accord Sedan 2012": 128,
+    "Honda Odyssey Minivan 2007": 126,
+    "Honda Odyssey Minivan 2012": 125,
+    "Hyundai Accent Sedan 2012": 135,
+    "Hyundai Azera Sedan 2012": 139,
+    "Hyundai Elantra Sedan 2007": 134,
+    "Hyundai Elantra Touring Hatchback 2012": 138,
+    "Hyundai Genesis Sedan 2012": 136,
+    "Hyundai Santa Fe SUV 2012": 130,
+    "Hyundai Sonata Hybrid Sedan 2012": 133,
+    "Hyundai Sonata Sedan 2012": 137,
+    "Hyundai Tucson SUV 2012": 131,
+    "Hyundai Veloster Hatchback 2012": 129,
+    "Hyundai Veracruz SUV 2012": 132,
+    "Infiniti G Coupe IPL 2012": 140,
+    "Infiniti QX56 SUV 2011": 141,
+    "Isuzu Ascender SUV 2008": 142,
+    "Jaguar XK XKR 2012": 143,
+    "Jeep Compass SUV 2012": 148,
+    "Jeep Grand Cherokee SUV 2012": 147,
+    "Jeep Liberty SUV 2012": 146,
+    "Jeep Patriot SUV 2012": 144,
+    "Jeep Wrangler SUV 2012": 145,
+    "Lamborghini Aventador Coupe 2012": 150,
+    "Lamborghini Diablo Coupe 2001": 152,
+    "Lamborghini Gallardo LP 570-4 Superleggera 2012": 151,
+    "Lamborghini Reventon Coupe 2008": 149,
+    "Land Rover LR2 SUV 2012": 154,
+    "Land Rover Range Rover SUV 2012": 153,
+    "Lincoln Town Car Sedan 2011": 155,
+    "MINI Cooper Roadster Convertible 2012": 156,
+    "Maybach Landaulet Convertible 2012": 157,
+    "Mazda Tribute SUV 2011": 158,
+    "McLaren MP4-12C Coupe 2012": 159,
+    "Mercedes-Benz 300-Class Convertible 1993": 160,
+    "Mercedes-Benz C-Class Sedan 2012": 161,
+    "Mercedes-Benz E-Class Sedan 2012": 163,
+    "Mercedes-Benz S-Class Sedan 2012": 164,
+    "Mercedes-Benz SL-Class Coupe 2009": 162,
+    "Mercedes-Benz Sprinter Van 2012": 165,
+    "Mitsubishi Lancer Sedan 2012": 166,
+    "Nissan 240SX Coupe 1998": 170,
+    "Nissan Juke Hatchback 2012": 169,
+    "Nissan Leaf Hatchback 2012": 167,
+    "Nissan NV Passenger Van 2012": 168,
+    "Plymouth Neon Coupe 1999": 171,
+    "Porsche Panamera Sedan 2012": 172,
+    "Ram C/V Cargo Van Minivan 2012": 173,
+    "Rolls-Royce Ghost Sedan 2012": 175,
+    "Rolls-Royce Phantom Drophead Coupe Convertible 2012": 174,
+    "Rolls-Royce Phantom Sedan 2012": 176,
+    "Scion xD Hatchback 2012": 177,
+    "Spyker C8 Convertible 2009": 178,
+    "Spyker C8 Coupe 2009": 179,
+    "Suzuki Aerio Sedan 2007": 180,
+    "Suzuki Kizashi Sedan 2012": 181,
+    "Suzuki SX4 Hatchback 2012": 182,
+    "Suzuki SX4 Sedan 2012": 183,
+    "Tesla Model S Sedan 2012": 184,
+    "Toyota 4Runner SUV 2012": 188,
+    "Toyota Camry Sedan 2012": 186,
+    "Toyota Corolla Sedan 2012": 187,
+    "Toyota Sequoia SUV 2012": 185,
+    "Volkswagen Beetle Hatchback 2012": 191,
+    "Volkswagen Golf Hatchback 1991": 190,
+    "Volkswagen Golf Hatchback 2012": 189,
+    "Volvo 240 Sedan 1993": 193,
+    "Volvo C30 Hatchback 2012": 192,
+    "Volvo XC90 SUV 2007": 194,
+    "smart fortwo Convertible 2012": 195
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-stanford-cars-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet50-stanford-cars-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-stanford-cars-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/README.md b/resnet50-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..9822ff62b64e2e6063f102f5682a419f7e6b58fc
--- /dev/null
+++ b/resnet50-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stanford-cars.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: stanford-cars
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: train
+type: transformers
+val_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: test
+```
+
diff --git a/resnet50-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/config.json b/resnet50-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..4ab8a7f592f8381989e1ca00e428926f91d8a1a5
--- /dev/null
+++ b/resnet50-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,435 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "AM General Hummer SUV 2000",
+    "1": "Acura RL Sedan 2012",
+    "2": "Acura TL Sedan 2012",
+    "3": "Acura TL Type-S 2008",
+    "4": "Acura TSX Sedan 2012",
+    "5": "Acura Integra Type R 2001",
+    "6": "Acura ZDX Hatchback 2012",
+    "7": "Aston Martin V8 Vantage Convertible 2012",
+    "8": "Aston Martin V8 Vantage Coupe 2012",
+    "9": "Aston Martin Virage Convertible 2012",
+    "10": "Aston Martin Virage Coupe 2012",
+    "11": "Audi RS 4 Convertible 2008",
+    "12": "Audi A5 Coupe 2012",
+    "13": "Audi TTS Coupe 2012",
+    "14": "Audi R8 Coupe 2012",
+    "15": "Audi V8 Sedan 1994",
+    "16": "Audi 100 Sedan 1994",
+    "17": "Audi 100 Wagon 1994",
+    "18": "Audi TT Hatchback 2011",
+    "19": "Audi S6 Sedan 2011",
+    "20": "Audi S5 Convertible 2012",
+    "21": "Audi S5 Coupe 2012",
+    "22": "Audi S4 Sedan 2012",
+    "23": "Audi S4 Sedan 2007",
+    "24": "Audi TT RS Coupe 2012",
+    "25": "BMW ActiveHybrid 5 Sedan 2012",
+    "26": "BMW 1 Series Convertible 2012",
+    "27": "BMW 1 Series Coupe 2012",
+    "28": "BMW 3 Series Sedan 2012",
+    "29": "BMW 3 Series Wagon 2012",
+    "30": "BMW 6 Series Convertible 2007",
+    "31": "BMW X5 SUV 2007",
+    "32": "BMW X6 SUV 2012",
+    "33": "BMW M3 Coupe 2012",
+    "34": "BMW M5 Sedan 2010",
+    "35": "BMW M6 Convertible 2010",
+    "36": "BMW X3 SUV 2012",
+    "37": "BMW Z4 Convertible 2012",
+    "38": "Bentley Continental Supersports Conv. Convertible 2012",
+    "39": "Bentley Arnage Sedan 2009",
+    "40": "Bentley Mulsanne Sedan 2011",
+    "41": "Bentley Continental GT Coupe 2012",
+    "42": "Bentley Continental GT Coupe 2007",
+    "43": "Bentley Continental Flying Spur Sedan 2007",
+    "44": "Bugatti Veyron 16.4 Convertible 2009",
+    "45": "Bugatti Veyron 16.4 Coupe 2009",
+    "46": "Buick Regal GS 2012",
+    "47": "Buick Rainier SUV 2007",
+    "48": "Buick Verano Sedan 2012",
+    "49": "Buick Enclave SUV 2012",
+    "50": "Cadillac CTS-V Sedan 2012",
+    "51": "Cadillac SRX SUV 2012",
+    "52": "Cadillac Escalade EXT Crew Cab 2007",
+    "53": "Chevrolet Silverado 1500 Hybrid Crew Cab 2012",
+    "54": "Chevrolet Corvette Convertible 2012",
+    "55": "Chevrolet Corvette ZR1 2012",
+    "56": "Chevrolet Corvette Ron Fellows Edition Z06 2007",
+    "57": "Chevrolet Traverse SUV 2012",
+    "58": "Chevrolet Camaro Convertible 2012",
+    "59": "Chevrolet HHR SS 2010",
+    "60": "Chevrolet Impala Sedan 2007",
+    "61": "Chevrolet Tahoe Hybrid SUV 2012",
+    "62": "Chevrolet Sonic Sedan 2012",
+    "63": "Chevrolet Express Cargo Van 2007",
+    "64": "Chevrolet Avalanche Crew Cab 2012",
+    "65": "Chevrolet Cobalt SS 2010",
+    "66": "Chevrolet Malibu Hybrid Sedan 2010",
+    "67": "Chevrolet TrailBlazer SS 2009",
+    "68": "Chevrolet Silverado 2500HD Regular Cab 2012",
+    "69": "Chevrolet Silverado 1500 Classic Extended Cab 2007",
+    "70": "Chevrolet Express Van 2007",
+    "71": "Chevrolet Monte Carlo Coupe 2007",
+    "72": "Chevrolet Malibu Sedan 2007",
+    "73": "Chevrolet Silverado 1500 Extended Cab 2012",
+    "74": "Chevrolet Silverado 1500 Regular Cab 2012",
+    "75": "Chrysler Aspen SUV 2009",
+    "76": "Chrysler Sebring Convertible 2010",
+    "77": "Chrysler Town and Country Minivan 2012",
+    "78": "Chrysler 300 SRT-8 2010",
+    "79": "Chrysler Crossfire Convertible 2008",
+    "80": "Chrysler PT Cruiser Convertible 2008",
+    "81": "Daewoo Nubira Wagon 2002",
+    "82": "Dodge Caliber Wagon 2012",
+    "83": "Dodge Caliber Wagon 2007",
+    "84": "Dodge Caravan Minivan 1997",
+    "85": "Dodge Ram Pickup 3500 Crew Cab 2010",
+    "86": "Dodge Ram Pickup 3500 Quad Cab 2009",
+    "87": "Dodge Sprinter Cargo Van 2009",
+    "88": "Dodge Journey SUV 2012",
+    "89": "Dodge Dakota Crew Cab 2010",
+    "90": "Dodge Dakota Club Cab 2007",
+    "91": "Dodge Magnum Wagon 2008",
+    "92": "Dodge Challenger SRT8 2011",
+    "93": "Dodge Durango SUV 2012",
+    "94": "Dodge Durango SUV 2007",
+    "95": "Dodge Charger Sedan 2012",
+    "96": "Dodge Charger SRT-8 2009",
+    "97": "Eagle Talon Hatchback 1998",
+    "98": "FIAT 500 Abarth 2012",
+    "99": "FIAT 500 Convertible 2012",
+    "100": "Ferrari FF Coupe 2012",
+    "101": "Ferrari California Convertible 2012",
+    "102": "Ferrari 458 Italia Convertible 2012",
+    "103": "Ferrari 458 Italia Coupe 2012",
+    "104": "Fisker Karma Sedan 2012",
+    "105": "Ford F-450 Super Duty Crew Cab 2012",
+    "106": "Ford Mustang Convertible 2007",
+    "107": "Ford Freestar Minivan 2007",
+    "108": "Ford Expedition EL SUV 2009",
+    "109": "Ford Edge SUV 2012",
+    "110": "Ford Ranger SuperCab 2011",
+    "111": "Ford GT Coupe 2006",
+    "112": "Ford F-150 Regular Cab 2012",
+    "113": "Ford F-150 Regular Cab 2007",
+    "114": "Ford Focus Sedan 2007",
+    "115": "Ford E-Series Wagon Van 2012",
+    "116": "Ford Fiesta Sedan 2012",
+    "117": "GMC Terrain SUV 2012",
+    "118": "GMC Savana Van 2012",
+    "119": "GMC Yukon Hybrid SUV 2012",
+    "120": "GMC Acadia SUV 2012",
+    "121": "GMC Canyon Extended Cab 2012",
+    "122": "Geo Metro Convertible 1993",
+    "123": "HUMMER H3T Crew Cab 2010",
+    "124": "HUMMER H2 SUT Crew Cab 2009",
+    "125": "Honda Odyssey Minivan 2012",
+    "126": "Honda Odyssey Minivan 2007",
+    "127": "Honda Accord Coupe 2012",
+    "128": "Honda Accord Sedan 2012",
+    "129": "Hyundai Veloster Hatchback 2012",
+    "130": "Hyundai Santa Fe SUV 2012",
+    "131": "Hyundai Tucson SUV 2012",
+    "132": "Hyundai Veracruz SUV 2012",
+    "133": "Hyundai Sonata Hybrid Sedan 2012",
+    "134": "Hyundai Elantra Sedan 2007",
+    "135": "Hyundai Accent Sedan 2012",
+    "136": "Hyundai Genesis Sedan 2012",
+    "137": "Hyundai Sonata Sedan 2012",
+    "138": "Hyundai Elantra Touring Hatchback 2012",
+    "139": "Hyundai Azera Sedan 2012",
+    "140": "Infiniti G Coupe IPL 2012",
+    "141": "Infiniti QX56 SUV 2011",
+    "142": "Isuzu Ascender SUV 2008",
+    "143": "Jaguar XK XKR 2012",
+    "144": "Jeep Patriot SUV 2012",
+    "145": "Jeep Wrangler SUV 2012",
+    "146": "Jeep Liberty SUV 2012",
+    "147": "Jeep Grand Cherokee SUV 2012",
+    "148": "Jeep Compass SUV 2012",
+    "149": "Lamborghini Reventon Coupe 2008",
+    "150": "Lamborghini Aventador Coupe 2012",
+    "151": "Lamborghini Gallardo LP 570-4 Superleggera 2012",
+    "152": "Lamborghini Diablo Coupe 2001",
+    "153": "Land Rover Range Rover SUV 2012",
+    "154": "Land Rover LR2 SUV 2012",
+    "155": "Lincoln Town Car Sedan 2011",
+    "156": "MINI Cooper Roadster Convertible 2012",
+    "157": "Maybach Landaulet Convertible 2012",
+    "158": "Mazda Tribute SUV 2011",
+    "159": "McLaren MP4-12C Coupe 2012",
+    "160": "Mercedes-Benz 300-Class Convertible 1993",
+    "161": "Mercedes-Benz C-Class Sedan 2012",
+    "162": "Mercedes-Benz SL-Class Coupe 2009",
+    "163": "Mercedes-Benz E-Class Sedan 2012",
+    "164": "Mercedes-Benz S-Class Sedan 2012",
+    "165": "Mercedes-Benz Sprinter Van 2012",
+    "166": "Mitsubishi Lancer Sedan 2012",
+    "167": "Nissan Leaf Hatchback 2012",
+    "168": "Nissan NV Passenger Van 2012",
+    "169": "Nissan Juke Hatchback 2012",
+    "170": "Nissan 240SX Coupe 1998",
+    "171": "Plymouth Neon Coupe 1999",
+    "172": "Porsche Panamera Sedan 2012",
+    "173": "Ram C/V Cargo Van Minivan 2012",
+    "174": "Rolls-Royce Phantom Drophead Coupe Convertible 2012",
+    "175": "Rolls-Royce Ghost Sedan 2012",
+    "176": "Rolls-Royce Phantom Sedan 2012",
+    "177": "Scion xD Hatchback 2012",
+    "178": "Spyker C8 Convertible 2009",
+    "179": "Spyker C8 Coupe 2009",
+    "180": "Suzuki Aerio Sedan 2007",
+    "181": "Suzuki Kizashi Sedan 2012",
+    "182": "Suzuki SX4 Hatchback 2012",
+    "183": "Suzuki SX4 Sedan 2012",
+    "184": "Tesla Model S Sedan 2012",
+    "185": "Toyota Sequoia SUV 2012",
+    "186": "Toyota Camry Sedan 2012",
+    "187": "Toyota Corolla Sedan 2012",
+    "188": "Toyota 4Runner SUV 2012",
+    "189": "Volkswagen Golf Hatchback 2012",
+    "190": "Volkswagen Golf Hatchback 1991",
+    "191": "Volkswagen Beetle Hatchback 2012",
+    "192": "Volvo C30 Hatchback 2012",
+    "193": "Volvo 240 Sedan 1993",
+    "194": "Volvo XC90 SUV 2007",
+    "195": "smart fortwo Convertible 2012"
+  },
+  "label2id": {
+    "AM General Hummer SUV 2000": 0,
+    "Acura Integra Type R 2001": 5,
+    "Acura RL Sedan 2012": 1,
+    "Acura TL Sedan 2012": 2,
+    "Acura TL Type-S 2008": 3,
+    "Acura TSX Sedan 2012": 4,
+    "Acura ZDX Hatchback 2012": 6,
+    "Aston Martin V8 Vantage Convertible 2012": 7,
+    "Aston Martin V8 Vantage Coupe 2012": 8,
+    "Aston Martin Virage Convertible 2012": 9,
+    "Aston Martin Virage Coupe 2012": 10,
+    "Audi 100 Sedan 1994": 16,
+    "Audi 100 Wagon 1994": 17,
+    "Audi A5 Coupe 2012": 12,
+    "Audi R8 Coupe 2012": 14,
+    "Audi RS 4 Convertible 2008": 11,
+    "Audi S4 Sedan 2007": 23,
+    "Audi S4 Sedan 2012": 22,
+    "Audi S5 Convertible 2012": 20,
+    "Audi S5 Coupe 2012": 21,
+    "Audi S6 Sedan 2011": 19,
+    "Audi TT Hatchback 2011": 18,
+    "Audi TT RS Coupe 2012": 24,
+    "Audi TTS Coupe 2012": 13,
+    "Audi V8 Sedan 1994": 15,
+    "BMW 1 Series Convertible 2012": 26,
+    "BMW 1 Series Coupe 2012": 27,
+    "BMW 3 Series Sedan 2012": 28,
+    "BMW 3 Series Wagon 2012": 29,
+    "BMW 6 Series Convertible 2007": 30,
+    "BMW ActiveHybrid 5 Sedan 2012": 25,
+    "BMW M3 Coupe 2012": 33,
+    "BMW M5 Sedan 2010": 34,
+    "BMW M6 Convertible 2010": 35,
+    "BMW X3 SUV 2012": 36,
+    "BMW X5 SUV 2007": 31,
+    "BMW X6 SUV 2012": 32,
+    "BMW Z4 Convertible 2012": 37,
+    "Bentley Arnage Sedan 2009": 39,
+    "Bentley Continental Flying Spur Sedan 2007": 43,
+    "Bentley Continental GT Coupe 2007": 42,
+    "Bentley Continental GT Coupe 2012": 41,
+    "Bentley Continental Supersports Conv. Convertible 2012": 38,
+    "Bentley Mulsanne Sedan 2011": 40,
+    "Bugatti Veyron 16.4 Convertible 2009": 44,
+    "Bugatti Veyron 16.4 Coupe 2009": 45,
+    "Buick Enclave SUV 2012": 49,
+    "Buick Rainier SUV 2007": 47,
+    "Buick Regal GS 2012": 46,
+    "Buick Verano Sedan 2012": 48,
+    "Cadillac CTS-V Sedan 2012": 50,
+    "Cadillac Escalade EXT Crew Cab 2007": 52,
+    "Cadillac SRX SUV 2012": 51,
+    "Chevrolet Avalanche Crew Cab 2012": 64,
+    "Chevrolet Camaro Convertible 2012": 58,
+    "Chevrolet Cobalt SS 2010": 65,
+    "Chevrolet Corvette Convertible 2012": 54,
+    "Chevrolet Corvette Ron Fellows Edition Z06 2007": 56,
+    "Chevrolet Corvette ZR1 2012": 55,
+    "Chevrolet Express Cargo Van 2007": 63,
+    "Chevrolet Express Van 2007": 70,
+    "Chevrolet HHR SS 2010": 59,
+    "Chevrolet Impala Sedan 2007": 60,
+    "Chevrolet Malibu Hybrid Sedan 2010": 66,
+    "Chevrolet Malibu Sedan 2007": 72,
+    "Chevrolet Monte Carlo Coupe 2007": 71,
+    "Chevrolet Silverado 1500 Classic Extended Cab 2007": 69,
+    "Chevrolet Silverado 1500 Extended Cab 2012": 73,
+    "Chevrolet Silverado 1500 Hybrid Crew Cab 2012": 53,
+    "Chevrolet Silverado 1500 Regular Cab 2012": 74,
+    "Chevrolet Silverado 2500HD Regular Cab 2012": 68,
+    "Chevrolet Sonic Sedan 2012": 62,
+    "Chevrolet Tahoe Hybrid SUV 2012": 61,
+    "Chevrolet TrailBlazer SS 2009": 67,
+    "Chevrolet Traverse SUV 2012": 57,
+    "Chrysler 300 SRT-8 2010": 78,
+    "Chrysler Aspen SUV 2009": 75,
+    "Chrysler Crossfire Convertible 2008": 79,
+    "Chrysler PT Cruiser Convertible 2008": 80,
+    "Chrysler Sebring Convertible 2010": 76,
+    "Chrysler Town and Country Minivan 2012": 77,
+    "Daewoo Nubira Wagon 2002": 81,
+    "Dodge Caliber Wagon 2007": 83,
+    "Dodge Caliber Wagon 2012": 82,
+    "Dodge Caravan Minivan 1997": 84,
+    "Dodge Challenger SRT8 2011": 92,
+    "Dodge Charger SRT-8 2009": 96,
+    "Dodge Charger Sedan 2012": 95,
+    "Dodge Dakota Club Cab 2007": 90,
+    "Dodge Dakota Crew Cab 2010": 89,
+    "Dodge Durango SUV 2007": 94,
+    "Dodge Durango SUV 2012": 93,
+    "Dodge Journey SUV 2012": 88,
+    "Dodge Magnum Wagon 2008": 91,
+    "Dodge Ram Pickup 3500 Crew Cab 2010": 85,
+    "Dodge Ram Pickup 3500 Quad Cab 2009": 86,
+    "Dodge Sprinter Cargo Van 2009": 87,
+    "Eagle Talon Hatchback 1998": 97,
+    "FIAT 500 Abarth 2012": 98,
+    "FIAT 500 Convertible 2012": 99,
+    "Ferrari 458 Italia Convertible 2012": 102,
+    "Ferrari 458 Italia Coupe 2012": 103,
+    "Ferrari California Convertible 2012": 101,
+    "Ferrari FF Coupe 2012": 100,
+    "Fisker Karma Sedan 2012": 104,
+    "Ford E-Series Wagon Van 2012": 115,
+    "Ford Edge SUV 2012": 109,
+    "Ford Expedition EL SUV 2009": 108,
+    "Ford F-150 Regular Cab 2007": 113,
+    "Ford F-150 Regular Cab 2012": 112,
+    "Ford F-450 Super Duty Crew Cab 2012": 105,
+    "Ford Fiesta Sedan 2012": 116,
+    "Ford Focus Sedan 2007": 114,
+    "Ford Freestar Minivan 2007": 107,
+    "Ford GT Coupe 2006": 111,
+    "Ford Mustang Convertible 2007": 106,
+    "Ford Ranger SuperCab 2011": 110,
+    "GMC Acadia SUV 2012": 120,
+    "GMC Canyon Extended Cab 2012": 121,
+    "GMC Savana Van 2012": 118,
+    "GMC Terrain SUV 2012": 117,
+    "GMC Yukon Hybrid SUV 2012": 119,
+    "Geo Metro Convertible 1993": 122,
+    "HUMMER H2 SUT Crew Cab 2009": 124,
+    "HUMMER H3T Crew Cab 2010": 123,
+    "Honda Accord Coupe 2012": 127,
+    "Honda Accord Sedan 2012": 128,
+    "Honda Odyssey Minivan 2007": 126,
+    "Honda Odyssey Minivan 2012": 125,
+    "Hyundai Accent Sedan 2012": 135,
+    "Hyundai Azera Sedan 2012": 139,
+    "Hyundai Elantra Sedan 2007": 134,
+    "Hyundai Elantra Touring Hatchback 2012": 138,
+    "Hyundai Genesis Sedan 2012": 136,
+    "Hyundai Santa Fe SUV 2012": 130,
+    "Hyundai Sonata Hybrid Sedan 2012": 133,
+    "Hyundai Sonata Sedan 2012": 137,
+    "Hyundai Tucson SUV 2012": 131,
+    "Hyundai Veloster Hatchback 2012": 129,
+    "Hyundai Veracruz SUV 2012": 132,
+    "Infiniti G Coupe IPL 2012": 140,
+    "Infiniti QX56 SUV 2011": 141,
+    "Isuzu Ascender SUV 2008": 142,
+    "Jaguar XK XKR 2012": 143,
+    "Jeep Compass SUV 2012": 148,
+    "Jeep Grand Cherokee SUV 2012": 147,
+    "Jeep Liberty SUV 2012": 146,
+    "Jeep Patriot SUV 2012": 144,
+    "Jeep Wrangler SUV 2012": 145,
+    "Lamborghini Aventador Coupe 2012": 150,
+    "Lamborghini Diablo Coupe 2001": 152,
+    "Lamborghini Gallardo LP 570-4 Superleggera 2012": 151,
+    "Lamborghini Reventon Coupe 2008": 149,
+    "Land Rover LR2 SUV 2012": 154,
+    "Land Rover Range Rover SUV 2012": 153,
+    "Lincoln Town Car Sedan 2011": 155,
+    "MINI Cooper Roadster Convertible 2012": 156,
+    "Maybach Landaulet Convertible 2012": 157,
+    "Mazda Tribute SUV 2011": 158,
+    "McLaren MP4-12C Coupe 2012": 159,
+    "Mercedes-Benz 300-Class Convertible 1993": 160,
+    "Mercedes-Benz C-Class Sedan 2012": 161,
+    "Mercedes-Benz E-Class Sedan 2012": 163,
+    "Mercedes-Benz S-Class Sedan 2012": 164,
+    "Mercedes-Benz SL-Class Coupe 2009": 162,
+    "Mercedes-Benz Sprinter Van 2012": 165,
+    "Mitsubishi Lancer Sedan 2012": 166,
+    "Nissan 240SX Coupe 1998": 170,
+    "Nissan Juke Hatchback 2012": 169,
+    "Nissan Leaf Hatchback 2012": 167,
+    "Nissan NV Passenger Van 2012": 168,
+    "Plymouth Neon Coupe 1999": 171,
+    "Porsche Panamera Sedan 2012": 172,
+    "Ram C/V Cargo Van Minivan 2012": 173,
+    "Rolls-Royce Ghost Sedan 2012": 175,
+    "Rolls-Royce Phantom Drophead Coupe Convertible 2012": 174,
+    "Rolls-Royce Phantom Sedan 2012": 176,
+    "Scion xD Hatchback 2012": 177,
+    "Spyker C8 Convertible 2009": 178,
+    "Spyker C8 Coupe 2009": 179,
+    "Suzuki Aerio Sedan 2007": 180,
+    "Suzuki Kizashi Sedan 2012": 181,
+    "Suzuki SX4 Hatchback 2012": 182,
+    "Suzuki SX4 Sedan 2012": 183,
+    "Tesla Model S Sedan 2012": 184,
+    "Toyota 4Runner SUV 2012": 188,
+    "Toyota Camry Sedan 2012": 186,
+    "Toyota Corolla Sedan 2012": 187,
+    "Toyota Sequoia SUV 2012": 185,
+    "Volkswagen Beetle Hatchback 2012": 191,
+    "Volkswagen Golf Hatchback 1991": 190,
+    "Volkswagen Golf Hatchback 2012": 189,
+    "Volvo 240 Sedan 1993": 193,
+    "Volvo C30 Hatchback 2012": 192,
+    "Volvo XC90 SUV 2007": 194,
+    "smart fortwo Convertible 2012": 195
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet50-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/README.md b/resnet50-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..1d41ff1eefe8d004c956ec563427ad21faf9e8ff
--- /dev/null
+++ b/resnet50-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stanford-cars.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: stanford-cars
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: train
+type: transformers
+val_datasets:
+  stanford-cars:
+    _target_: datasets.load_dataset
+    path: tanganke/stanford_cars
+    split: test
+```
+
diff --git a/resnet50-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/config.json b/resnet50-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..4ab8a7f592f8381989e1ca00e428926f91d8a1a5
--- /dev/null
+++ b/resnet50-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,435 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "AM General Hummer SUV 2000",
+    "1": "Acura RL Sedan 2012",
+    "2": "Acura TL Sedan 2012",
+    "3": "Acura TL Type-S 2008",
+    "4": "Acura TSX Sedan 2012",
+    "5": "Acura Integra Type R 2001",
+    "6": "Acura ZDX Hatchback 2012",
+    "7": "Aston Martin V8 Vantage Convertible 2012",
+    "8": "Aston Martin V8 Vantage Coupe 2012",
+    "9": "Aston Martin Virage Convertible 2012",
+    "10": "Aston Martin Virage Coupe 2012",
+    "11": "Audi RS 4 Convertible 2008",
+    "12": "Audi A5 Coupe 2012",
+    "13": "Audi TTS Coupe 2012",
+    "14": "Audi R8 Coupe 2012",
+    "15": "Audi V8 Sedan 1994",
+    "16": "Audi 100 Sedan 1994",
+    "17": "Audi 100 Wagon 1994",
+    "18": "Audi TT Hatchback 2011",
+    "19": "Audi S6 Sedan 2011",
+    "20": "Audi S5 Convertible 2012",
+    "21": "Audi S5 Coupe 2012",
+    "22": "Audi S4 Sedan 2012",
+    "23": "Audi S4 Sedan 2007",
+    "24": "Audi TT RS Coupe 2012",
+    "25": "BMW ActiveHybrid 5 Sedan 2012",
+    "26": "BMW 1 Series Convertible 2012",
+    "27": "BMW 1 Series Coupe 2012",
+    "28": "BMW 3 Series Sedan 2012",
+    "29": "BMW 3 Series Wagon 2012",
+    "30": "BMW 6 Series Convertible 2007",
+    "31": "BMW X5 SUV 2007",
+    "32": "BMW X6 SUV 2012",
+    "33": "BMW M3 Coupe 2012",
+    "34": "BMW M5 Sedan 2010",
+    "35": "BMW M6 Convertible 2010",
+    "36": "BMW X3 SUV 2012",
+    "37": "BMW Z4 Convertible 2012",
+    "38": "Bentley Continental Supersports Conv. Convertible 2012",
+    "39": "Bentley Arnage Sedan 2009",
+    "40": "Bentley Mulsanne Sedan 2011",
+    "41": "Bentley Continental GT Coupe 2012",
+    "42": "Bentley Continental GT Coupe 2007",
+    "43": "Bentley Continental Flying Spur Sedan 2007",
+    "44": "Bugatti Veyron 16.4 Convertible 2009",
+    "45": "Bugatti Veyron 16.4 Coupe 2009",
+    "46": "Buick Regal GS 2012",
+    "47": "Buick Rainier SUV 2007",
+    "48": "Buick Verano Sedan 2012",
+    "49": "Buick Enclave SUV 2012",
+    "50": "Cadillac CTS-V Sedan 2012",
+    "51": "Cadillac SRX SUV 2012",
+    "52": "Cadillac Escalade EXT Crew Cab 2007",
+    "53": "Chevrolet Silverado 1500 Hybrid Crew Cab 2012",
+    "54": "Chevrolet Corvette Convertible 2012",
+    "55": "Chevrolet Corvette ZR1 2012",
+    "56": "Chevrolet Corvette Ron Fellows Edition Z06 2007",
+    "57": "Chevrolet Traverse SUV 2012",
+    "58": "Chevrolet Camaro Convertible 2012",
+    "59": "Chevrolet HHR SS 2010",
+    "60": "Chevrolet Impala Sedan 2007",
+    "61": "Chevrolet Tahoe Hybrid SUV 2012",
+    "62": "Chevrolet Sonic Sedan 2012",
+    "63": "Chevrolet Express Cargo Van 2007",
+    "64": "Chevrolet Avalanche Crew Cab 2012",
+    "65": "Chevrolet Cobalt SS 2010",
+    "66": "Chevrolet Malibu Hybrid Sedan 2010",
+    "67": "Chevrolet TrailBlazer SS 2009",
+    "68": "Chevrolet Silverado 2500HD Regular Cab 2012",
+    "69": "Chevrolet Silverado 1500 Classic Extended Cab 2007",
+    "70": "Chevrolet Express Van 2007",
+    "71": "Chevrolet Monte Carlo Coupe 2007",
+    "72": "Chevrolet Malibu Sedan 2007",
+    "73": "Chevrolet Silverado 1500 Extended Cab 2012",
+    "74": "Chevrolet Silverado 1500 Regular Cab 2012",
+    "75": "Chrysler Aspen SUV 2009",
+    "76": "Chrysler Sebring Convertible 2010",
+    "77": "Chrysler Town and Country Minivan 2012",
+    "78": "Chrysler 300 SRT-8 2010",
+    "79": "Chrysler Crossfire Convertible 2008",
+    "80": "Chrysler PT Cruiser Convertible 2008",
+    "81": "Daewoo Nubira Wagon 2002",
+    "82": "Dodge Caliber Wagon 2012",
+    "83": "Dodge Caliber Wagon 2007",
+    "84": "Dodge Caravan Minivan 1997",
+    "85": "Dodge Ram Pickup 3500 Crew Cab 2010",
+    "86": "Dodge Ram Pickup 3500 Quad Cab 2009",
+    "87": "Dodge Sprinter Cargo Van 2009",
+    "88": "Dodge Journey SUV 2012",
+    "89": "Dodge Dakota Crew Cab 2010",
+    "90": "Dodge Dakota Club Cab 2007",
+    "91": "Dodge Magnum Wagon 2008",
+    "92": "Dodge Challenger SRT8 2011",
+    "93": "Dodge Durango SUV 2012",
+    "94": "Dodge Durango SUV 2007",
+    "95": "Dodge Charger Sedan 2012",
+    "96": "Dodge Charger SRT-8 2009",
+    "97": "Eagle Talon Hatchback 1998",
+    "98": "FIAT 500 Abarth 2012",
+    "99": "FIAT 500 Convertible 2012",
+    "100": "Ferrari FF Coupe 2012",
+    "101": "Ferrari California Convertible 2012",
+    "102": "Ferrari 458 Italia Convertible 2012",
+    "103": "Ferrari 458 Italia Coupe 2012",
+    "104": "Fisker Karma Sedan 2012",
+    "105": "Ford F-450 Super Duty Crew Cab 2012",
+    "106": "Ford Mustang Convertible 2007",
+    "107": "Ford Freestar Minivan 2007",
+    "108": "Ford Expedition EL SUV 2009",
+    "109": "Ford Edge SUV 2012",
+    "110": "Ford Ranger SuperCab 2011",
+    "111": "Ford GT Coupe 2006",
+    "112": "Ford F-150 Regular Cab 2012",
+    "113": "Ford F-150 Regular Cab 2007",
+    "114": "Ford Focus Sedan 2007",
+    "115": "Ford E-Series Wagon Van 2012",
+    "116": "Ford Fiesta Sedan 2012",
+    "117": "GMC Terrain SUV 2012",
+    "118": "GMC Savana Van 2012",
+    "119": "GMC Yukon Hybrid SUV 2012",
+    "120": "GMC Acadia SUV 2012",
+    "121": "GMC Canyon Extended Cab 2012",
+    "122": "Geo Metro Convertible 1993",
+    "123": "HUMMER H3T Crew Cab 2010",
+    "124": "HUMMER H2 SUT Crew Cab 2009",
+    "125": "Honda Odyssey Minivan 2012",
+    "126": "Honda Odyssey Minivan 2007",
+    "127": "Honda Accord Coupe 2012",
+    "128": "Honda Accord Sedan 2012",
+    "129": "Hyundai Veloster Hatchback 2012",
+    "130": "Hyundai Santa Fe SUV 2012",
+    "131": "Hyundai Tucson SUV 2012",
+    "132": "Hyundai Veracruz SUV 2012",
+    "133": "Hyundai Sonata Hybrid Sedan 2012",
+    "134": "Hyundai Elantra Sedan 2007",
+    "135": "Hyundai Accent Sedan 2012",
+    "136": "Hyundai Genesis Sedan 2012",
+    "137": "Hyundai Sonata Sedan 2012",
+    "138": "Hyundai Elantra Touring Hatchback 2012",
+    "139": "Hyundai Azera Sedan 2012",
+    "140": "Infiniti G Coupe IPL 2012",
+    "141": "Infiniti QX56 SUV 2011",
+    "142": "Isuzu Ascender SUV 2008",
+    "143": "Jaguar XK XKR 2012",
+    "144": "Jeep Patriot SUV 2012",
+    "145": "Jeep Wrangler SUV 2012",
+    "146": "Jeep Liberty SUV 2012",
+    "147": "Jeep Grand Cherokee SUV 2012",
+    "148": "Jeep Compass SUV 2012",
+    "149": "Lamborghini Reventon Coupe 2008",
+    "150": "Lamborghini Aventador Coupe 2012",
+    "151": "Lamborghini Gallardo LP 570-4 Superleggera 2012",
+    "152": "Lamborghini Diablo Coupe 2001",
+    "153": "Land Rover Range Rover SUV 2012",
+    "154": "Land Rover LR2 SUV 2012",
+    "155": "Lincoln Town Car Sedan 2011",
+    "156": "MINI Cooper Roadster Convertible 2012",
+    "157": "Maybach Landaulet Convertible 2012",
+    "158": "Mazda Tribute SUV 2011",
+    "159": "McLaren MP4-12C Coupe 2012",
+    "160": "Mercedes-Benz 300-Class Convertible 1993",
+    "161": "Mercedes-Benz C-Class Sedan 2012",
+    "162": "Mercedes-Benz SL-Class Coupe 2009",
+    "163": "Mercedes-Benz E-Class Sedan 2012",
+    "164": "Mercedes-Benz S-Class Sedan 2012",
+    "165": "Mercedes-Benz Sprinter Van 2012",
+    "166": "Mitsubishi Lancer Sedan 2012",
+    "167": "Nissan Leaf Hatchback 2012",
+    "168": "Nissan NV Passenger Van 2012",
+    "169": "Nissan Juke Hatchback 2012",
+    "170": "Nissan 240SX Coupe 1998",
+    "171": "Plymouth Neon Coupe 1999",
+    "172": "Porsche Panamera Sedan 2012",
+    "173": "Ram C/V Cargo Van Minivan 2012",
+    "174": "Rolls-Royce Phantom Drophead Coupe Convertible 2012",
+    "175": "Rolls-Royce Ghost Sedan 2012",
+    "176": "Rolls-Royce Phantom Sedan 2012",
+    "177": "Scion xD Hatchback 2012",
+    "178": "Spyker C8 Convertible 2009",
+    "179": "Spyker C8 Coupe 2009",
+    "180": "Suzuki Aerio Sedan 2007",
+    "181": "Suzuki Kizashi Sedan 2012",
+    "182": "Suzuki SX4 Hatchback 2012",
+    "183": "Suzuki SX4 Sedan 2012",
+    "184": "Tesla Model S Sedan 2012",
+    "185": "Toyota Sequoia SUV 2012",
+    "186": "Toyota Camry Sedan 2012",
+    "187": "Toyota Corolla Sedan 2012",
+    "188": "Toyota 4Runner SUV 2012",
+    "189": "Volkswagen Golf Hatchback 2012",
+    "190": "Volkswagen Golf Hatchback 1991",
+    "191": "Volkswagen Beetle Hatchback 2012",
+    "192": "Volvo C30 Hatchback 2012",
+    "193": "Volvo 240 Sedan 1993",
+    "194": "Volvo XC90 SUV 2007",
+    "195": "smart fortwo Convertible 2012"
+  },
+  "label2id": {
+    "AM General Hummer SUV 2000": 0,
+    "Acura Integra Type R 2001": 5,
+    "Acura RL Sedan 2012": 1,
+    "Acura TL Sedan 2012": 2,
+    "Acura TL Type-S 2008": 3,
+    "Acura TSX Sedan 2012": 4,
+    "Acura ZDX Hatchback 2012": 6,
+    "Aston Martin V8 Vantage Convertible 2012": 7,
+    "Aston Martin V8 Vantage Coupe 2012": 8,
+    "Aston Martin Virage Convertible 2012": 9,
+    "Aston Martin Virage Coupe 2012": 10,
+    "Audi 100 Sedan 1994": 16,
+    "Audi 100 Wagon 1994": 17,
+    "Audi A5 Coupe 2012": 12,
+    "Audi R8 Coupe 2012": 14,
+    "Audi RS 4 Convertible 2008": 11,
+    "Audi S4 Sedan 2007": 23,
+    "Audi S4 Sedan 2012": 22,
+    "Audi S5 Convertible 2012": 20,
+    "Audi S5 Coupe 2012": 21,
+    "Audi S6 Sedan 2011": 19,
+    "Audi TT Hatchback 2011": 18,
+    "Audi TT RS Coupe 2012": 24,
+    "Audi TTS Coupe 2012": 13,
+    "Audi V8 Sedan 1994": 15,
+    "BMW 1 Series Convertible 2012": 26,
+    "BMW 1 Series Coupe 2012": 27,
+    "BMW 3 Series Sedan 2012": 28,
+    "BMW 3 Series Wagon 2012": 29,
+    "BMW 6 Series Convertible 2007": 30,
+    "BMW ActiveHybrid 5 Sedan 2012": 25,
+    "BMW M3 Coupe 2012": 33,
+    "BMW M5 Sedan 2010": 34,
+    "BMW M6 Convertible 2010": 35,
+    "BMW X3 SUV 2012": 36,
+    "BMW X5 SUV 2007": 31,
+    "BMW X6 SUV 2012": 32,
+    "BMW Z4 Convertible 2012": 37,
+    "Bentley Arnage Sedan 2009": 39,
+    "Bentley Continental Flying Spur Sedan 2007": 43,
+    "Bentley Continental GT Coupe 2007": 42,
+    "Bentley Continental GT Coupe 2012": 41,
+    "Bentley Continental Supersports Conv. Convertible 2012": 38,
+    "Bentley Mulsanne Sedan 2011": 40,
+    "Bugatti Veyron 16.4 Convertible 2009": 44,
+    "Bugatti Veyron 16.4 Coupe 2009": 45,
+    "Buick Enclave SUV 2012": 49,
+    "Buick Rainier SUV 2007": 47,
+    "Buick Regal GS 2012": 46,
+    "Buick Verano Sedan 2012": 48,
+    "Cadillac CTS-V Sedan 2012": 50,
+    "Cadillac Escalade EXT Crew Cab 2007": 52,
+    "Cadillac SRX SUV 2012": 51,
+    "Chevrolet Avalanche Crew Cab 2012": 64,
+    "Chevrolet Camaro Convertible 2012": 58,
+    "Chevrolet Cobalt SS 2010": 65,
+    "Chevrolet Corvette Convertible 2012": 54,
+    "Chevrolet Corvette Ron Fellows Edition Z06 2007": 56,
+    "Chevrolet Corvette ZR1 2012": 55,
+    "Chevrolet Express Cargo Van 2007": 63,
+    "Chevrolet Express Van 2007": 70,
+    "Chevrolet HHR SS 2010": 59,
+    "Chevrolet Impala Sedan 2007": 60,
+    "Chevrolet Malibu Hybrid Sedan 2010": 66,
+    "Chevrolet Malibu Sedan 2007": 72,
+    "Chevrolet Monte Carlo Coupe 2007": 71,
+    "Chevrolet Silverado 1500 Classic Extended Cab 2007": 69,
+    "Chevrolet Silverado 1500 Extended Cab 2012": 73,
+    "Chevrolet Silverado 1500 Hybrid Crew Cab 2012": 53,
+    "Chevrolet Silverado 1500 Regular Cab 2012": 74,
+    "Chevrolet Silverado 2500HD Regular Cab 2012": 68,
+    "Chevrolet Sonic Sedan 2012": 62,
+    "Chevrolet Tahoe Hybrid SUV 2012": 61,
+    "Chevrolet TrailBlazer SS 2009": 67,
+    "Chevrolet Traverse SUV 2012": 57,
+    "Chrysler 300 SRT-8 2010": 78,
+    "Chrysler Aspen SUV 2009": 75,
+    "Chrysler Crossfire Convertible 2008": 79,
+    "Chrysler PT Cruiser Convertible 2008": 80,
+    "Chrysler Sebring Convertible 2010": 76,
+    "Chrysler Town and Country Minivan 2012": 77,
+    "Daewoo Nubira Wagon 2002": 81,
+    "Dodge Caliber Wagon 2007": 83,
+    "Dodge Caliber Wagon 2012": 82,
+    "Dodge Caravan Minivan 1997": 84,
+    "Dodge Challenger SRT8 2011": 92,
+    "Dodge Charger SRT-8 2009": 96,
+    "Dodge Charger Sedan 2012": 95,
+    "Dodge Dakota Club Cab 2007": 90,
+    "Dodge Dakota Crew Cab 2010": 89,
+    "Dodge Durango SUV 2007": 94,
+    "Dodge Durango SUV 2012": 93,
+    "Dodge Journey SUV 2012": 88,
+    "Dodge Magnum Wagon 2008": 91,
+    "Dodge Ram Pickup 3500 Crew Cab 2010": 85,
+    "Dodge Ram Pickup 3500 Quad Cab 2009": 86,
+    "Dodge Sprinter Cargo Van 2009": 87,
+    "Eagle Talon Hatchback 1998": 97,
+    "FIAT 500 Abarth 2012": 98,
+    "FIAT 500 Convertible 2012": 99,
+    "Ferrari 458 Italia Convertible 2012": 102,
+    "Ferrari 458 Italia Coupe 2012": 103,
+    "Ferrari California Convertible 2012": 101,
+    "Ferrari FF Coupe 2012": 100,
+    "Fisker Karma Sedan 2012": 104,
+    "Ford E-Series Wagon Van 2012": 115,
+    "Ford Edge SUV 2012": 109,
+    "Ford Expedition EL SUV 2009": 108,
+    "Ford F-150 Regular Cab 2007": 113,
+    "Ford F-150 Regular Cab 2012": 112,
+    "Ford F-450 Super Duty Crew Cab 2012": 105,
+    "Ford Fiesta Sedan 2012": 116,
+    "Ford Focus Sedan 2007": 114,
+    "Ford Freestar Minivan 2007": 107,
+    "Ford GT Coupe 2006": 111,
+    "Ford Mustang Convertible 2007": 106,
+    "Ford Ranger SuperCab 2011": 110,
+    "GMC Acadia SUV 2012": 120,
+    "GMC Canyon Extended Cab 2012": 121,
+    "GMC Savana Van 2012": 118,
+    "GMC Terrain SUV 2012": 117,
+    "GMC Yukon Hybrid SUV 2012": 119,
+    "Geo Metro Convertible 1993": 122,
+    "HUMMER H2 SUT Crew Cab 2009": 124,
+    "HUMMER H3T Crew Cab 2010": 123,
+    "Honda Accord Coupe 2012": 127,
+    "Honda Accord Sedan 2012": 128,
+    "Honda Odyssey Minivan 2007": 126,
+    "Honda Odyssey Minivan 2012": 125,
+    "Hyundai Accent Sedan 2012": 135,
+    "Hyundai Azera Sedan 2012": 139,
+    "Hyundai Elantra Sedan 2007": 134,
+    "Hyundai Elantra Touring Hatchback 2012": 138,
+    "Hyundai Genesis Sedan 2012": 136,
+    "Hyundai Santa Fe SUV 2012": 130,
+    "Hyundai Sonata Hybrid Sedan 2012": 133,
+    "Hyundai Sonata Sedan 2012": 137,
+    "Hyundai Tucson SUV 2012": 131,
+    "Hyundai Veloster Hatchback 2012": 129,
+    "Hyundai Veracruz SUV 2012": 132,
+    "Infiniti G Coupe IPL 2012": 140,
+    "Infiniti QX56 SUV 2011": 141,
+    "Isuzu Ascender SUV 2008": 142,
+    "Jaguar XK XKR 2012": 143,
+    "Jeep Compass SUV 2012": 148,
+    "Jeep Grand Cherokee SUV 2012": 147,
+    "Jeep Liberty SUV 2012": 146,
+    "Jeep Patriot SUV 2012": 144,
+    "Jeep Wrangler SUV 2012": 145,
+    "Lamborghini Aventador Coupe 2012": 150,
+    "Lamborghini Diablo Coupe 2001": 152,
+    "Lamborghini Gallardo LP 570-4 Superleggera 2012": 151,
+    "Lamborghini Reventon Coupe 2008": 149,
+    "Land Rover LR2 SUV 2012": 154,
+    "Land Rover Range Rover SUV 2012": 153,
+    "Lincoln Town Car Sedan 2011": 155,
+    "MINI Cooper Roadster Convertible 2012": 156,
+    "Maybach Landaulet Convertible 2012": 157,
+    "Mazda Tribute SUV 2011": 158,
+    "McLaren MP4-12C Coupe 2012": 159,
+    "Mercedes-Benz 300-Class Convertible 1993": 160,
+    "Mercedes-Benz C-Class Sedan 2012": 161,
+    "Mercedes-Benz E-Class Sedan 2012": 163,
+    "Mercedes-Benz S-Class Sedan 2012": 164,
+    "Mercedes-Benz SL-Class Coupe 2009": 162,
+    "Mercedes-Benz Sprinter Van 2012": 165,
+    "Mitsubishi Lancer Sedan 2012": 166,
+    "Nissan 240SX Coupe 1998": 170,
+    "Nissan Juke Hatchback 2012": 169,
+    "Nissan Leaf Hatchback 2012": 167,
+    "Nissan NV Passenger Van 2012": 168,
+    "Plymouth Neon Coupe 1999": 171,
+    "Porsche Panamera Sedan 2012": 172,
+    "Ram C/V Cargo Van Minivan 2012": 173,
+    "Rolls-Royce Ghost Sedan 2012": 175,
+    "Rolls-Royce Phantom Drophead Coupe Convertible 2012": 174,
+    "Rolls-Royce Phantom Sedan 2012": 176,
+    "Scion xD Hatchback 2012": 177,
+    "Spyker C8 Convertible 2009": 178,
+    "Spyker C8 Coupe 2009": 179,
+    "Suzuki Aerio Sedan 2007": 180,
+    "Suzuki Kizashi Sedan 2012": 181,
+    "Suzuki SX4 Hatchback 2012": 182,
+    "Suzuki SX4 Sedan 2012": 183,
+    "Tesla Model S Sedan 2012": 184,
+    "Toyota 4Runner SUV 2012": 188,
+    "Toyota Camry Sedan 2012": 186,
+    "Toyota Corolla Sedan 2012": 187,
+    "Toyota Sequoia SUV 2012": 185,
+    "Volkswagen Beetle Hatchback 2012": 191,
+    "Volkswagen Golf Hatchback 1991": 190,
+    "Volkswagen Golf Hatchback 2012": 189,
+    "Volvo 240 Sedan 1993": 193,
+    "Volvo C30 Hatchback 2012": 192,
+    "Volvo XC90 SUV 2007": 194,
+    "smart fortwo Convertible 2012": 195
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet50-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-stl10-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/README.md b/resnet50-stl10-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..8327291f1c1d152164abb591813ba4fbc6b1d731
--- /dev/null
+++ b/resnet50-stl10-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset stl10.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: stl10
+    pretrained: true
+test_datasets: null
+train_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: train
+type: transformers
+val_datasets:
+  stl10:
+    _target_: datasets.load_dataset
+    path: tanganke/stl10
+    split: test
+```
+
diff --git a/resnet50-stl10-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/config.json b/resnet50-stl10-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..589b71bb15675afba14a3d018d8e1b4a07ab7182
--- /dev/null
+++ b/resnet50-stl10-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "bird",
+    "2": "car",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "horse",
+    "7": "monkey",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": 0,
+    "bird": 1,
+    "car": 2,
+    "cat": 3,
+    "deer": 4,
+    "dog": 5,
+    "horse": 6,
+    "monkey": 7,
+    "ship": 8,
+    "truck": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-stl10-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet50-stl10-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-stl10-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-sun397-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/README.md b/resnet50-sun397-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..6be07d08e4fe76f5e3414f3a48d98cf38863e55d
--- /dev/null
+++ b/resnet50-sun397-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset sun397.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: sun397
+    pretrained: true
+test_datasets: null
+train_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: train
+type: transformers
+val_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: test
+```
+
diff --git a/resnet50-sun397-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/config.json b/resnet50-sun397-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..7b3f0b16022576c1d5cf54a17e75ff9088c89b17
--- /dev/null
+++ b/resnet50-sun397-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/config.json
@@ -0,0 +1,837 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "abbey",
+    "1": "airplane cabin",
+    "2": "airport terminal",
+    "3": "alley",
+    "4": "amphitheater",
+    "5": "amusement arcade",
+    "6": "amusement park",
+    "7": "anechoic chamber",
+    "8": "apartment building outdoor",
+    "9": "apse indoor",
+    "10": "aquarium",
+    "11": "aqueduct",
+    "12": "arch",
+    "13": "archive",
+    "14": "arrival gate outdoor",
+    "15": "art gallery",
+    "16": "art school",
+    "17": "art studio",
+    "18": "assembly line",
+    "19": "athletic field outdoor",
+    "20": "atrium public",
+    "21": "attic",
+    "22": "auditorium",
+    "23": "auto factory",
+    "24": "badlands",
+    "25": "badminton court indoor",
+    "26": "baggage claim",
+    "27": "bakery shop",
+    "28": "balcony exterior",
+    "29": "balcony interior",
+    "30": "ball pit",
+    "31": "ballroom",
+    "32": "bamboo forest",
+    "33": "banquet hall",
+    "34": "bar",
+    "35": "barn",
+    "36": "barndoor",
+    "37": "baseball field",
+    "38": "basement",
+    "39": "basilica",
+    "40": "basketball court outdoor",
+    "41": "bathroom",
+    "42": "batters box",
+    "43": "bayou",
+    "44": "bazaar indoor",
+    "45": "bazaar outdoor",
+    "46": "beach",
+    "47": "beauty salon",
+    "48": "bedroom",
+    "49": "berth",
+    "50": "biology laboratory",
+    "51": "bistro indoor",
+    "52": "boardwalk",
+    "53": "boat deck",
+    "54": "boathouse",
+    "55": "bookstore",
+    "56": "booth indoor",
+    "57": "botanical garden",
+    "58": "bow window indoor",
+    "59": "bow window outdoor",
+    "60": "bowling alley",
+    "61": "boxing ring",
+    "62": "brewery indoor",
+    "63": "bridge",
+    "64": "building facade",
+    "65": "bullring",
+    "66": "burial chamber",
+    "67": "bus interior",
+    "68": "butchers shop",
+    "69": "butte",
+    "70": "cabin outdoor",
+    "71": "cafeteria",
+    "72": "campsite",
+    "73": "campus",
+    "74": "canal natural",
+    "75": "canal urban",
+    "76": "candy store",
+    "77": "canyon",
+    "78": "car interior backseat",
+    "79": "car interior frontseat",
+    "80": "carrousel",
+    "81": "casino indoor",
+    "82": "castle",
+    "83": "catacomb",
+    "84": "cathedral indoor",
+    "85": "cathedral outdoor",
+    "86": "cavern indoor",
+    "87": "cemetery",
+    "88": "chalet",
+    "89": "cheese factory",
+    "90": "chemistry lab",
+    "91": "chicken coop indoor",
+    "92": "chicken coop outdoor",
+    "93": "childs room",
+    "94": "church indoor",
+    "95": "church outdoor",
+    "96": "classroom",
+    "97": "clean room",
+    "98": "cliff",
+    "99": "cloister indoor",
+    "100": "closet",
+    "101": "clothing store",
+    "102": "coast",
+    "103": "cockpit",
+    "104": "coffee shop",
+    "105": "computer room",
+    "106": "conference center",
+    "107": "conference room",
+    "108": "construction site",
+    "109": "control room",
+    "110": "control tower outdoor",
+    "111": "corn field",
+    "112": "corral",
+    "113": "corridor",
+    "114": "cottage garden",
+    "115": "courthouse",
+    "116": "courtroom",
+    "117": "courtyard",
+    "118": "covered bridge exterior",
+    "119": "creek",
+    "120": "crevasse",
+    "121": "crosswalk",
+    "122": "cubicle office",
+    "123": "dam",
+    "124": "delicatessen",
+    "125": "dentists office",
+    "126": "desert sand",
+    "127": "desert vegetation",
+    "128": "diner indoor",
+    "129": "diner outdoor",
+    "130": "dinette home",
+    "131": "dinette vehicle",
+    "132": "dining car",
+    "133": "dining room",
+    "134": "discotheque",
+    "135": "dock",
+    "136": "doorway outdoor",
+    "137": "dorm room",
+    "138": "driveway",
+    "139": "driving range outdoor",
+    "140": "drugstore",
+    "141": "electrical substation",
+    "142": "elevator door",
+    "143": "elevator interior",
+    "144": "elevator shaft",
+    "145": "engine room",
+    "146": "escalator indoor",
+    "147": "excavation",
+    "148": "factory indoor",
+    "149": "fairway",
+    "150": "fastfood restaurant",
+    "151": "field cultivated",
+    "152": "field wild",
+    "153": "fire escape",
+    "154": "fire station",
+    "155": "firing range indoor",
+    "156": "fishpond",
+    "157": "florist shop indoor",
+    "158": "food court",
+    "159": "forest broadleaf",
+    "160": "forest needleleaf",
+    "161": "forest path",
+    "162": "forest road",
+    "163": "formal garden",
+    "164": "fountain",
+    "165": "galley",
+    "166": "game room",
+    "167": "garage indoor",
+    "168": "garbage dump",
+    "169": "gas station",
+    "170": "gazebo exterior",
+    "171": "general store indoor",
+    "172": "general store outdoor",
+    "173": "gift shop",
+    "174": "golf course",
+    "175": "greenhouse indoor",
+    "176": "greenhouse outdoor",
+    "177": "gymnasium indoor",
+    "178": "hangar indoor",
+    "179": "hangar outdoor",
+    "180": "harbor",
+    "181": "hayfield",
+    "182": "heliport",
+    "183": "herb garden",
+    "184": "highway",
+    "185": "hill",
+    "186": "home office",
+    "187": "hospital",
+    "188": "hospital room",
+    "189": "hot spring",
+    "190": "hot tub outdoor",
+    "191": "hotel outdoor",
+    "192": "hotel room",
+    "193": "house",
+    "194": "hunting lodge outdoor",
+    "195": "ice cream parlor",
+    "196": "ice floe",
+    "197": "ice shelf",
+    "198": "ice skating rink indoor",
+    "199": "ice skating rink outdoor",
+    "200": "iceberg",
+    "201": "igloo",
+    "202": "industrial area",
+    "203": "inn outdoor",
+    "204": "islet",
+    "205": "jacuzzi indoor",
+    "206": "jail cell",
+    "207": "jail indoor",
+    "208": "jewelry shop",
+    "209": "kasbah",
+    "210": "kennel indoor",
+    "211": "kennel outdoor",
+    "212": "kindergarden classroom",
+    "213": "kitchen",
+    "214": "kitchenette",
+    "215": "labyrinth outdoor",
+    "216": "lake natural",
+    "217": "landfill",
+    "218": "landing deck",
+    "219": "laundromat",
+    "220": "lecture room",
+    "221": "library indoor",
+    "222": "library outdoor",
+    "223": "lido deck outdoor",
+    "224": "lift bridge",
+    "225": "lighthouse",
+    "226": "limousine interior",
+    "227": "living room",
+    "228": "lobby",
+    "229": "lock chamber",
+    "230": "locker room",
+    "231": "mansion",
+    "232": "manufactured home",
+    "233": "market indoor",
+    "234": "market outdoor",
+    "235": "marsh",
+    "236": "martial arts gym",
+    "237": "mausoleum",
+    "238": "medina",
+    "239": "moat water",
+    "240": "monastery outdoor",
+    "241": "mosque indoor",
+    "242": "mosque outdoor",
+    "243": "motel",
+    "244": "mountain",
+    "245": "mountain snowy",
+    "246": "movie theater indoor",
+    "247": "museum indoor",
+    "248": "music store",
+    "249": "music studio",
+    "250": "nuclear power plant outdoor",
+    "251": "nursery",
+    "252": "oast house",
+    "253": "observatory outdoor",
+    "254": "ocean",
+    "255": "office",
+    "256": "office building",
+    "257": "oil refinery outdoor",
+    "258": "oilrig",
+    "259": "operating room",
+    "260": "orchard",
+    "261": "outhouse outdoor",
+    "262": "pagoda",
+    "263": "palace",
+    "264": "pantry",
+    "265": "park",
+    "266": "parking garage indoor",
+    "267": "parking garage outdoor",
+    "268": "parking lot",
+    "269": "parlor",
+    "270": "pasture",
+    "271": "patio",
+    "272": "pavilion",
+    "273": "pharmacy",
+    "274": "phone booth",
+    "275": "physics laboratory",
+    "276": "picnic area",
+    "277": "pilothouse indoor",
+    "278": "planetarium outdoor",
+    "279": "playground",
+    "280": "playroom",
+    "281": "plaza",
+    "282": "podium indoor",
+    "283": "podium outdoor",
+    "284": "pond",
+    "285": "poolroom establishment",
+    "286": "poolroom home",
+    "287": "power plant outdoor",
+    "288": "promenade deck",
+    "289": "pub indoor",
+    "290": "pulpit",
+    "291": "putting green",
+    "292": "racecourse",
+    "293": "raceway",
+    "294": "raft",
+    "295": "railroad track",
+    "296": "rainforest",
+    "297": "reception",
+    "298": "recreation room",
+    "299": "residential neighborhood",
+    "300": "restaurant",
+    "301": "restaurant kitchen",
+    "302": "restaurant patio",
+    "303": "rice paddy",
+    "304": "riding arena",
+    "305": "river",
+    "306": "rock arch",
+    "307": "rope bridge",
+    "308": "ruin",
+    "309": "runway",
+    "310": "sandbar",
+    "311": "sandbox",
+    "312": "sauna",
+    "313": "schoolhouse",
+    "314": "sea cliff",
+    "315": "server room",
+    "316": "shed",
+    "317": "shoe shop",
+    "318": "shopfront",
+    "319": "shopping mall indoor",
+    "320": "shower",
+    "321": "skatepark",
+    "322": "ski lodge",
+    "323": "ski resort",
+    "324": "ski slope",
+    "325": "sky",
+    "326": "skyscraper",
+    "327": "slum",
+    "328": "snowfield",
+    "329": "squash court",
+    "330": "stable",
+    "331": "stadium baseball",
+    "332": "stadium football",
+    "333": "stage indoor",
+    "334": "staircase",
+    "335": "street",
+    "336": "subway interior",
+    "337": "subway station platform",
+    "338": "supermarket",
+    "339": "sushi bar",
+    "340": "swamp",
+    "341": "swimming pool indoor",
+    "342": "swimming pool outdoor",
+    "343": "synagogue indoor",
+    "344": "synagogue outdoor",
+    "345": "television studio",
+    "346": "temple east asia",
+    "347": "temple south asia",
+    "348": "tennis court indoor",
+    "349": "tennis court outdoor",
+    "350": "tent outdoor",
+    "351": "theater indoor procenium",
+    "352": "theater indoor seats",
+    "353": "thriftshop",
+    "354": "throne room",
+    "355": "ticket booth",
+    "356": "toll plaza",
+    "357": "topiary garden",
+    "358": "tower",
+    "359": "toyshop",
+    "360": "track outdoor",
+    "361": "train railway",
+    "362": "train station platform",
+    "363": "tree farm",
+    "364": "tree house",
+    "365": "trench",
+    "366": "underwater coral reef",
+    "367": "utility room",
+    "368": "valley",
+    "369": "van interior",
+    "370": "vegetable garden",
+    "371": "veranda",
+    "372": "veterinarians office",
+    "373": "viaduct",
+    "374": "videostore",
+    "375": "village",
+    "376": "vineyard",
+    "377": "volcano",
+    "378": "volleyball court indoor",
+    "379": "volleyball court outdoor",
+    "380": "waiting room",
+    "381": "warehouse indoor",
+    "382": "water tower",
+    "383": "waterfall block",
+    "384": "waterfall fan",
+    "385": "waterfall plunge",
+    "386": "watering hole",
+    "387": "wave",
+    "388": "wet bar",
+    "389": "wheat field",
+    "390": "wind farm",
+    "391": "windmill",
+    "392": "wine cellar barrel storage",
+    "393": "wine cellar bottle storage",
+    "394": "wrestling ring indoor",
+    "395": "yard",
+    "396": "youth hostel"
+  },
+  "label2id": {
+    "abbey": 0,
+    "airplane cabin": 1,
+    "airport terminal": 2,
+    "alley": 3,
+    "amphitheater": 4,
+    "amusement arcade": 5,
+    "amusement park": 6,
+    "anechoic chamber": 7,
+    "apartment building outdoor": 8,
+    "apse indoor": 9,
+    "aquarium": 10,
+    "aqueduct": 11,
+    "arch": 12,
+    "archive": 13,
+    "arrival gate outdoor": 14,
+    "art gallery": 15,
+    "art school": 16,
+    "art studio": 17,
+    "assembly line": 18,
+    "athletic field outdoor": 19,
+    "atrium public": 20,
+    "attic": 21,
+    "auditorium": 22,
+    "auto factory": 23,
+    "badlands": 24,
+    "badminton court indoor": 25,
+    "baggage claim": 26,
+    "bakery shop": 27,
+    "balcony exterior": 28,
+    "balcony interior": 29,
+    "ball pit": 30,
+    "ballroom": 31,
+    "bamboo forest": 32,
+    "banquet hall": 33,
+    "bar": 34,
+    "barn": 35,
+    "barndoor": 36,
+    "baseball field": 37,
+    "basement": 38,
+    "basilica": 39,
+    "basketball court outdoor": 40,
+    "bathroom": 41,
+    "batters box": 42,
+    "bayou": 43,
+    "bazaar indoor": 44,
+    "bazaar outdoor": 45,
+    "beach": 46,
+    "beauty salon": 47,
+    "bedroom": 48,
+    "berth": 49,
+    "biology laboratory": 50,
+    "bistro indoor": 51,
+    "boardwalk": 52,
+    "boat deck": 53,
+    "boathouse": 54,
+    "bookstore": 55,
+    "booth indoor": 56,
+    "botanical garden": 57,
+    "bow window indoor": 58,
+    "bow window outdoor": 59,
+    "bowling alley": 60,
+    "boxing ring": 61,
+    "brewery indoor": 62,
+    "bridge": 63,
+    "building facade": 64,
+    "bullring": 65,
+    "burial chamber": 66,
+    "bus interior": 67,
+    "butchers shop": 68,
+    "butte": 69,
+    "cabin outdoor": 70,
+    "cafeteria": 71,
+    "campsite": 72,
+    "campus": 73,
+    "canal natural": 74,
+    "canal urban": 75,
+    "candy store": 76,
+    "canyon": 77,
+    "car interior backseat": 78,
+    "car interior frontseat": 79,
+    "carrousel": 80,
+    "casino indoor": 81,
+    "castle": 82,
+    "catacomb": 83,
+    "cathedral indoor": 84,
+    "cathedral outdoor": 85,
+    "cavern indoor": 86,
+    "cemetery": 87,
+    "chalet": 88,
+    "cheese factory": 89,
+    "chemistry lab": 90,
+    "chicken coop indoor": 91,
+    "chicken coop outdoor": 92,
+    "childs room": 93,
+    "church indoor": 94,
+    "church outdoor": 95,
+    "classroom": 96,
+    "clean room": 97,
+    "cliff": 98,
+    "cloister indoor": 99,
+    "closet": 100,
+    "clothing store": 101,
+    "coast": 102,
+    "cockpit": 103,
+    "coffee shop": 104,
+    "computer room": 105,
+    "conference center": 106,
+    "conference room": 107,
+    "construction site": 108,
+    "control room": 109,
+    "control tower outdoor": 110,
+    "corn field": 111,
+    "corral": 112,
+    "corridor": 113,
+    "cottage garden": 114,
+    "courthouse": 115,
+    "courtroom": 116,
+    "courtyard": 117,
+    "covered bridge exterior": 118,
+    "creek": 119,
+    "crevasse": 120,
+    "crosswalk": 121,
+    "cubicle office": 122,
+    "dam": 123,
+    "delicatessen": 124,
+    "dentists office": 125,
+    "desert sand": 126,
+    "desert vegetation": 127,
+    "diner indoor": 128,
+    "diner outdoor": 129,
+    "dinette home": 130,
+    "dinette vehicle": 131,
+    "dining car": 132,
+    "dining room": 133,
+    "discotheque": 134,
+    "dock": 135,
+    "doorway outdoor": 136,
+    "dorm room": 137,
+    "driveway": 138,
+    "driving range outdoor": 139,
+    "drugstore": 140,
+    "electrical substation": 141,
+    "elevator door": 142,
+    "elevator interior": 143,
+    "elevator shaft": 144,
+    "engine room": 145,
+    "escalator indoor": 146,
+    "excavation": 147,
+    "factory indoor": 148,
+    "fairway": 149,
+    "fastfood restaurant": 150,
+    "field cultivated": 151,
+    "field wild": 152,
+    "fire escape": 153,
+    "fire station": 154,
+    "firing range indoor": 155,
+    "fishpond": 156,
+    "florist shop indoor": 157,
+    "food court": 158,
+    "forest broadleaf": 159,
+    "forest needleleaf": 160,
+    "forest path": 161,
+    "forest road": 162,
+    "formal garden": 163,
+    "fountain": 164,
+    "galley": 165,
+    "game room": 166,
+    "garage indoor": 167,
+    "garbage dump": 168,
+    "gas station": 169,
+    "gazebo exterior": 170,
+    "general store indoor": 171,
+    "general store outdoor": 172,
+    "gift shop": 173,
+    "golf course": 174,
+    "greenhouse indoor": 175,
+    "greenhouse outdoor": 176,
+    "gymnasium indoor": 177,
+    "hangar indoor": 178,
+    "hangar outdoor": 179,
+    "harbor": 180,
+    "hayfield": 181,
+    "heliport": 182,
+    "herb garden": 183,
+    "highway": 184,
+    "hill": 185,
+    "home office": 186,
+    "hospital": 187,
+    "hospital room": 188,
+    "hot spring": 189,
+    "hot tub outdoor": 190,
+    "hotel outdoor": 191,
+    "hotel room": 192,
+    "house": 193,
+    "hunting lodge outdoor": 194,
+    "ice cream parlor": 195,
+    "ice floe": 196,
+    "ice shelf": 197,
+    "ice skating rink indoor": 198,
+    "ice skating rink outdoor": 199,
+    "iceberg": 200,
+    "igloo": 201,
+    "industrial area": 202,
+    "inn outdoor": 203,
+    "islet": 204,
+    "jacuzzi indoor": 205,
+    "jail cell": 206,
+    "jail indoor": 207,
+    "jewelry shop": 208,
+    "kasbah": 209,
+    "kennel indoor": 210,
+    "kennel outdoor": 211,
+    "kindergarden classroom": 212,
+    "kitchen": 213,
+    "kitchenette": 214,
+    "labyrinth outdoor": 215,
+    "lake natural": 216,
+    "landfill": 217,
+    "landing deck": 218,
+    "laundromat": 219,
+    "lecture room": 220,
+    "library indoor": 221,
+    "library outdoor": 222,
+    "lido deck outdoor": 223,
+    "lift bridge": 224,
+    "lighthouse": 225,
+    "limousine interior": 226,
+    "living room": 227,
+    "lobby": 228,
+    "lock chamber": 229,
+    "locker room": 230,
+    "mansion": 231,
+    "manufactured home": 232,
+    "market indoor": 233,
+    "market outdoor": 234,
+    "marsh": 235,
+    "martial arts gym": 236,
+    "mausoleum": 237,
+    "medina": 238,
+    "moat water": 239,
+    "monastery outdoor": 240,
+    "mosque indoor": 241,
+    "mosque outdoor": 242,
+    "motel": 243,
+    "mountain": 244,
+    "mountain snowy": 245,
+    "movie theater indoor": 246,
+    "museum indoor": 247,
+    "music store": 248,
+    "music studio": 249,
+    "nuclear power plant outdoor": 250,
+    "nursery": 251,
+    "oast house": 252,
+    "observatory outdoor": 253,
+    "ocean": 254,
+    "office": 255,
+    "office building": 256,
+    "oil refinery outdoor": 257,
+    "oilrig": 258,
+    "operating room": 259,
+    "orchard": 260,
+    "outhouse outdoor": 261,
+    "pagoda": 262,
+    "palace": 263,
+    "pantry": 264,
+    "park": 265,
+    "parking garage indoor": 266,
+    "parking garage outdoor": 267,
+    "parking lot": 268,
+    "parlor": 269,
+    "pasture": 270,
+    "patio": 271,
+    "pavilion": 272,
+    "pharmacy": 273,
+    "phone booth": 274,
+    "physics laboratory": 275,
+    "picnic area": 276,
+    "pilothouse indoor": 277,
+    "planetarium outdoor": 278,
+    "playground": 279,
+    "playroom": 280,
+    "plaza": 281,
+    "podium indoor": 282,
+    "podium outdoor": 283,
+    "pond": 284,
+    "poolroom establishment": 285,
+    "poolroom home": 286,
+    "power plant outdoor": 287,
+    "promenade deck": 288,
+    "pub indoor": 289,
+    "pulpit": 290,
+    "putting green": 291,
+    "racecourse": 292,
+    "raceway": 293,
+    "raft": 294,
+    "railroad track": 295,
+    "rainforest": 296,
+    "reception": 297,
+    "recreation room": 298,
+    "residential neighborhood": 299,
+    "restaurant": 300,
+    "restaurant kitchen": 301,
+    "restaurant patio": 302,
+    "rice paddy": 303,
+    "riding arena": 304,
+    "river": 305,
+    "rock arch": 306,
+    "rope bridge": 307,
+    "ruin": 308,
+    "runway": 309,
+    "sandbar": 310,
+    "sandbox": 311,
+    "sauna": 312,
+    "schoolhouse": 313,
+    "sea cliff": 314,
+    "server room": 315,
+    "shed": 316,
+    "shoe shop": 317,
+    "shopfront": 318,
+    "shopping mall indoor": 319,
+    "shower": 320,
+    "skatepark": 321,
+    "ski lodge": 322,
+    "ski resort": 323,
+    "ski slope": 324,
+    "sky": 325,
+    "skyscraper": 326,
+    "slum": 327,
+    "snowfield": 328,
+    "squash court": 329,
+    "stable": 330,
+    "stadium baseball": 331,
+    "stadium football": 332,
+    "stage indoor": 333,
+    "staircase": 334,
+    "street": 335,
+    "subway interior": 336,
+    "subway station platform": 337,
+    "supermarket": 338,
+    "sushi bar": 339,
+    "swamp": 340,
+    "swimming pool indoor": 341,
+    "swimming pool outdoor": 342,
+    "synagogue indoor": 343,
+    "synagogue outdoor": 344,
+    "television studio": 345,
+    "temple east asia": 346,
+    "temple south asia": 347,
+    "tennis court indoor": 348,
+    "tennis court outdoor": 349,
+    "tent outdoor": 350,
+    "theater indoor procenium": 351,
+    "theater indoor seats": 352,
+    "thriftshop": 353,
+    "throne room": 354,
+    "ticket booth": 355,
+    "toll plaza": 356,
+    "topiary garden": 357,
+    "tower": 358,
+    "toyshop": 359,
+    "track outdoor": 360,
+    "train railway": 361,
+    "train station platform": 362,
+    "tree farm": 363,
+    "tree house": 364,
+    "trench": 365,
+    "underwater coral reef": 366,
+    "utility room": 367,
+    "valley": 368,
+    "van interior": 369,
+    "vegetable garden": 370,
+    "veranda": 371,
+    "veterinarians office": 372,
+    "viaduct": 373,
+    "videostore": 374,
+    "village": 375,
+    "vineyard": 376,
+    "volcano": 377,
+    "volleyball court indoor": 378,
+    "volleyball court outdoor": 379,
+    "waiting room": 380,
+    "warehouse indoor": 381,
+    "water tower": 382,
+    "waterfall block": 383,
+    "waterfall fan": 384,
+    "waterfall plunge": 385,
+    "watering hole": 386,
+    "wave": 387,
+    "wet bar": 388,
+    "wheat field": 389,
+    "wind farm": 390,
+    "windmill": 391,
+    "wine cellar barrel storage": 392,
+    "wine cellar bottle storage": 393,
+    "wrestling ring indoor": 394,
+    "yard": 395,
+    "youth hostel": 396
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-sun397-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet50-sun397-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-sun397-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-sun397-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/README.md b/resnet50-sun397-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..6fd8a9ef2632b995a5e7837b4cdccf4443fb23a0
--- /dev/null
+++ b/resnet50-sun397-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset sun397.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.01
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: sun397
+    pretrained: true
+test_datasets: null
+train_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: train
+type: transformers
+val_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: test
+```
+
diff --git a/resnet50-sun397-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/config.json b/resnet50-sun397-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..7b3f0b16022576c1d5cf54a17e75ff9088c89b17
--- /dev/null
+++ b/resnet50-sun397-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,837 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "abbey",
+    "1": "airplane cabin",
+    "2": "airport terminal",
+    "3": "alley",
+    "4": "amphitheater",
+    "5": "amusement arcade",
+    "6": "amusement park",
+    "7": "anechoic chamber",
+    "8": "apartment building outdoor",
+    "9": "apse indoor",
+    "10": "aquarium",
+    "11": "aqueduct",
+    "12": "arch",
+    "13": "archive",
+    "14": "arrival gate outdoor",
+    "15": "art gallery",
+    "16": "art school",
+    "17": "art studio",
+    "18": "assembly line",
+    "19": "athletic field outdoor",
+    "20": "atrium public",
+    "21": "attic",
+    "22": "auditorium",
+    "23": "auto factory",
+    "24": "badlands",
+    "25": "badminton court indoor",
+    "26": "baggage claim",
+    "27": "bakery shop",
+    "28": "balcony exterior",
+    "29": "balcony interior",
+    "30": "ball pit",
+    "31": "ballroom",
+    "32": "bamboo forest",
+    "33": "banquet hall",
+    "34": "bar",
+    "35": "barn",
+    "36": "barndoor",
+    "37": "baseball field",
+    "38": "basement",
+    "39": "basilica",
+    "40": "basketball court outdoor",
+    "41": "bathroom",
+    "42": "batters box",
+    "43": "bayou",
+    "44": "bazaar indoor",
+    "45": "bazaar outdoor",
+    "46": "beach",
+    "47": "beauty salon",
+    "48": "bedroom",
+    "49": "berth",
+    "50": "biology laboratory",
+    "51": "bistro indoor",
+    "52": "boardwalk",
+    "53": "boat deck",
+    "54": "boathouse",
+    "55": "bookstore",
+    "56": "booth indoor",
+    "57": "botanical garden",
+    "58": "bow window indoor",
+    "59": "bow window outdoor",
+    "60": "bowling alley",
+    "61": "boxing ring",
+    "62": "brewery indoor",
+    "63": "bridge",
+    "64": "building facade",
+    "65": "bullring",
+    "66": "burial chamber",
+    "67": "bus interior",
+    "68": "butchers shop",
+    "69": "butte",
+    "70": "cabin outdoor",
+    "71": "cafeteria",
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+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-sun397-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet50-sun397-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-sun397-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/README.md b/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..af479b4f3a59dac5aaeb520939f1aa00de1f6da1
--- /dev/null
+++ b/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset sun397.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: sun397
+    pretrained: true
+test_datasets: null
+train_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: train
+type: transformers
+val_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: test
+```
+
diff --git a/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/config.json b/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..7b3f0b16022576c1d5cf54a17e75ff9088c89b17
--- /dev/null
+++ b/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/config.json
@@ -0,0 +1,837 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "abbey",
+    "1": "airplane cabin",
+    "2": "airport terminal",
+    "3": "alley",
+    "4": "amphitheater",
+    "5": "amusement arcade",
+    "6": "amusement park",
+    "7": "anechoic chamber",
+    "8": "apartment building outdoor",
+    "9": "apse indoor",
+    "10": "aquarium",
+    "11": "aqueduct",
+    "12": "arch",
+    "13": "archive",
+    "14": "arrival gate outdoor",
+    "15": "art gallery",
+    "16": "art school",
+    "17": "art studio",
+    "18": "assembly line",
+    "19": "athletic field outdoor",
+    "20": "atrium public",
+    "21": "attic",
+    "22": "auditorium",
+    "23": "auto factory",
+    "24": "badlands",
+    "25": "badminton court indoor",
+    "26": "baggage claim",
+    "27": "bakery shop",
+    "28": "balcony exterior",
+    "29": "balcony interior",
+    "30": "ball pit",
+    "31": "ballroom",
+    "32": "bamboo forest",
+    "33": "banquet hall",
+    "34": "bar",
+    "35": "barn",
+    "36": "barndoor",
+    "37": "baseball field",
+    "38": "basement",
+    "39": "basilica",
+    "40": "basketball court outdoor",
+    "41": "bathroom",
+    "42": "batters box",
+    "43": "bayou",
+    "44": "bazaar indoor",
+    "45": "bazaar outdoor",
+    "46": "beach",
+    "47": "beauty salon",
+    "48": "bedroom",
+    "49": "berth",
+    "50": "biology laboratory",
+    "51": "bistro indoor",
+    "52": "boardwalk",
+    "53": "boat deck",
+    "54": "boathouse",
+    "55": "bookstore",
+    "56": "booth indoor",
+    "57": "botanical garden",
+    "58": "bow window indoor",
+    "59": "bow window outdoor",
+    "60": "bowling alley",
+    "61": "boxing ring",
+    "62": "brewery indoor",
+    "63": "bridge",
+    "64": "building facade",
+    "65": "bullring",
+    "66": "burial chamber",
+    "67": "bus interior",
+    "68": "butchers shop",
+    "69": "butte",
+    "70": "cabin outdoor",
+    "71": "cafeteria",
+    "72": "campsite",
+    "73": "campus",
+    "74": "canal natural",
+    "75": "canal urban",
+    "76": "candy store",
+    "77": "canyon",
+    "78": "car interior backseat",
+    "79": "car interior frontseat",
+    "80": "carrousel",
+    "81": "casino indoor",
+    "82": "castle",
+    "83": "catacomb",
+    "84": "cathedral indoor",
+    "85": "cathedral outdoor",
+    "86": "cavern indoor",
+    "87": "cemetery",
+    "88": "chalet",
+    "89": "cheese factory",
+    "90": "chemistry lab",
+    "91": "chicken coop indoor",
+    "92": "chicken coop outdoor",
+    "93": "childs room",
+    "94": "church indoor",
+    "95": "church outdoor",
+    "96": "classroom",
+    "97": "clean room",
+    "98": "cliff",
+    "99": "cloister indoor",
+    "100": "closet",
+    "101": "clothing store",
+    "102": "coast",
+    "103": "cockpit",
+    "104": "coffee shop",
+    "105": "computer room",
+    "106": "conference center",
+    "107": "conference room",
+    "108": "construction site",
+    "109": "control room",
+    "110": "control tower outdoor",
+    "111": "corn field",
+    "112": "corral",
+    "113": "corridor",
+    "114": "cottage garden",
+    "115": "courthouse",
+    "116": "courtroom",
+    "117": "courtyard",
+    "118": "covered bridge exterior",
+    "119": "creek",
+    "120": "crevasse",
+    "121": "crosswalk",
+    "122": "cubicle office",
+    "123": "dam",
+    "124": "delicatessen",
+    "125": "dentists office",
+    "126": "desert sand",
+    "127": "desert vegetation",
+    "128": "diner indoor",
+    "129": "diner outdoor",
+    "130": "dinette home",
+    "131": "dinette vehicle",
+    "132": "dining car",
+    "133": "dining room",
+    "134": "discotheque",
+    "135": "dock",
+    "136": "doorway outdoor",
+    "137": "dorm room",
+    "138": "driveway",
+    "139": "driving range outdoor",
+    "140": "drugstore",
+    "141": "electrical substation",
+    "142": "elevator door",
+    "143": "elevator interior",
+    "144": "elevator shaft",
+    "145": "engine room",
+    "146": "escalator indoor",
+    "147": "excavation",
+    "148": "factory indoor",
+    "149": "fairway",
+    "150": "fastfood restaurant",
+    "151": "field cultivated",
+    "152": "field wild",
+    "153": "fire escape",
+    "154": "fire station",
+    "155": "firing range indoor",
+    "156": "fishpond",
+    "157": "florist shop indoor",
+    "158": "food court",
+    "159": "forest broadleaf",
+    "160": "forest needleleaf",
+    "161": "forest path",
+    "162": "forest road",
+    "163": "formal garden",
+    "164": "fountain",
+    "165": "galley",
+    "166": "game room",
+    "167": "garage indoor",
+    "168": "garbage dump",
+    "169": "gas station",
+    "170": "gazebo exterior",
+    "171": "general store indoor",
+    "172": "general store outdoor",
+    "173": "gift shop",
+    "174": "golf course",
+    "175": "greenhouse indoor",
+    "176": "greenhouse outdoor",
+    "177": "gymnasium indoor",
+    "178": "hangar indoor",
+    "179": "hangar outdoor",
+    "180": "harbor",
+    "181": "hayfield",
+    "182": "heliport",
+    "183": "herb garden",
+    "184": "highway",
+    "185": "hill",
+    "186": "home office",
+    "187": "hospital",
+    "188": "hospital room",
+    "189": "hot spring",
+    "190": "hot tub outdoor",
+    "191": "hotel outdoor",
+    "192": "hotel room",
+    "193": "house",
+    "194": "hunting lodge outdoor",
+    "195": "ice cream parlor",
+    "196": "ice floe",
+    "197": "ice shelf",
+    "198": "ice skating rink indoor",
+    "199": "ice skating rink outdoor",
+    "200": "iceberg",
+    "201": "igloo",
+    "202": "industrial area",
+    "203": "inn outdoor",
+    "204": "islet",
+    "205": "jacuzzi indoor",
+    "206": "jail cell",
+    "207": "jail indoor",
+    "208": "jewelry shop",
+    "209": "kasbah",
+    "210": "kennel indoor",
+    "211": "kennel outdoor",
+    "212": "kindergarden classroom",
+    "213": "kitchen",
+    "214": "kitchenette",
+    "215": "labyrinth outdoor",
+    "216": "lake natural",
+    "217": "landfill",
+    "218": "landing deck",
+    "219": "laundromat",
+    "220": "lecture room",
+    "221": "library indoor",
+    "222": "library outdoor",
+    "223": "lido deck outdoor",
+    "224": "lift bridge",
+    "225": "lighthouse",
+    "226": "limousine interior",
+    "227": "living room",
+    "228": "lobby",
+    "229": "lock chamber",
+    "230": "locker room",
+    "231": "mansion",
+    "232": "manufactured home",
+    "233": "market indoor",
+    "234": "market outdoor",
+    "235": "marsh",
+    "236": "martial arts gym",
+    "237": "mausoleum",
+    "238": "medina",
+    "239": "moat water",
+    "240": "monastery outdoor",
+    "241": "mosque indoor",
+    "242": "mosque outdoor",
+    "243": "motel",
+    "244": "mountain",
+    "245": "mountain snowy",
+    "246": "movie theater indoor",
+    "247": "museum indoor",
+    "248": "music store",
+    "249": "music studio",
+    "250": "nuclear power plant outdoor",
+    "251": "nursery",
+    "252": "oast house",
+    "253": "observatory outdoor",
+    "254": "ocean",
+    "255": "office",
+    "256": "office building",
+    "257": "oil refinery outdoor",
+    "258": "oilrig",
+    "259": "operating room",
+    "260": "orchard",
+    "261": "outhouse outdoor",
+    "262": "pagoda",
+    "263": "palace",
+    "264": "pantry",
+    "265": "park",
+    "266": "parking garage indoor",
+    "267": "parking garage outdoor",
+    "268": "parking lot",
+    "269": "parlor",
+    "270": "pasture",
+    "271": "patio",
+    "272": "pavilion",
+    "273": "pharmacy",
+    "274": "phone booth",
+    "275": "physics laboratory",
+    "276": "picnic area",
+    "277": "pilothouse indoor",
+    "278": "planetarium outdoor",
+    "279": "playground",
+    "280": "playroom",
+    "281": "plaza",
+    "282": "podium indoor",
+    "283": "podium outdoor",
+    "284": "pond",
+    "285": "poolroom establishment",
+    "286": "poolroom home",
+    "287": "power plant outdoor",
+    "288": "promenade deck",
+    "289": "pub indoor",
+    "290": "pulpit",
+    "291": "putting green",
+    "292": "racecourse",
+    "293": "raceway",
+    "294": "raft",
+    "295": "railroad track",
+    "296": "rainforest",
+    "297": "reception",
+    "298": "recreation room",
+    "299": "residential neighborhood",
+    "300": "restaurant",
+    "301": "restaurant kitchen",
+    "302": "restaurant patio",
+    "303": "rice paddy",
+    "304": "riding arena",
+    "305": "river",
+    "306": "rock arch",
+    "307": "rope bridge",
+    "308": "ruin",
+    "309": "runway",
+    "310": "sandbar",
+    "311": "sandbox",
+    "312": "sauna",
+    "313": "schoolhouse",
+    "314": "sea cliff",
+    "315": "server room",
+    "316": "shed",
+    "317": "shoe shop",
+    "318": "shopfront",
+    "319": "shopping mall indoor",
+    "320": "shower",
+    "321": "skatepark",
+    "322": "ski lodge",
+    "323": "ski resort",
+    "324": "ski slope",
+    "325": "sky",
+    "326": "skyscraper",
+    "327": "slum",
+    "328": "snowfield",
+    "329": "squash court",
+    "330": "stable",
+    "331": "stadium baseball",
+    "332": "stadium football",
+    "333": "stage indoor",
+    "334": "staircase",
+    "335": "street",
+    "336": "subway interior",
+    "337": "subway station platform",
+    "338": "supermarket",
+    "339": "sushi bar",
+    "340": "swamp",
+    "341": "swimming pool indoor",
+    "342": "swimming pool outdoor",
+    "343": "synagogue indoor",
+    "344": "synagogue outdoor",
+    "345": "television studio",
+    "346": "temple east asia",
+    "347": "temple south asia",
+    "348": "tennis court indoor",
+    "349": "tennis court outdoor",
+    "350": "tent outdoor",
+    "351": "theater indoor procenium",
+    "352": "theater indoor seats",
+    "353": "thriftshop",
+    "354": "throne room",
+    "355": "ticket booth",
+    "356": "toll plaza",
+    "357": "topiary garden",
+    "358": "tower",
+    "359": "toyshop",
+    "360": "track outdoor",
+    "361": "train railway",
+    "362": "train station platform",
+    "363": "tree farm",
+    "364": "tree house",
+    "365": "trench",
+    "366": "underwater coral reef",
+    "367": "utility room",
+    "368": "valley",
+    "369": "van interior",
+    "370": "vegetable garden",
+    "371": "veranda",
+    "372": "veterinarians office",
+    "373": "viaduct",
+    "374": "videostore",
+    "375": "village",
+    "376": "vineyard",
+    "377": "volcano",
+    "378": "volleyball court indoor",
+    "379": "volleyball court outdoor",
+    "380": "waiting room",
+    "381": "warehouse indoor",
+    "382": "water tower",
+    "383": "waterfall block",
+    "384": "waterfall fan",
+    "385": "waterfall plunge",
+    "386": "watering hole",
+    "387": "wave",
+    "388": "wet bar",
+    "389": "wheat field",
+    "390": "wind farm",
+    "391": "windmill",
+    "392": "wine cellar barrel storage",
+    "393": "wine cellar bottle storage",
+    "394": "wrestling ring indoor",
+    "395": "yard",
+    "396": "youth hostel"
+  },
+  "label2id": {
+    "abbey": 0,
+    "airplane cabin": 1,
+    "airport terminal": 2,
+    "alley": 3,
+    "amphitheater": 4,
+    "amusement arcade": 5,
+    "amusement park": 6,
+    "anechoic chamber": 7,
+    "apartment building outdoor": 8,
+    "apse indoor": 9,
+    "aquarium": 10,
+    "aqueduct": 11,
+    "arch": 12,
+    "archive": 13,
+    "arrival gate outdoor": 14,
+    "art gallery": 15,
+    "art school": 16,
+    "art studio": 17,
+    "assembly line": 18,
+    "athletic field outdoor": 19,
+    "atrium public": 20,
+    "attic": 21,
+    "auditorium": 22,
+    "auto factory": 23,
+    "badlands": 24,
+    "badminton court indoor": 25,
+    "baggage claim": 26,
+    "bakery shop": 27,
+    "balcony exterior": 28,
+    "balcony interior": 29,
+    "ball pit": 30,
+    "ballroom": 31,
+    "bamboo forest": 32,
+    "banquet hall": 33,
+    "bar": 34,
+    "barn": 35,
+    "barndoor": 36,
+    "baseball field": 37,
+    "basement": 38,
+    "basilica": 39,
+    "basketball court outdoor": 40,
+    "bathroom": 41,
+    "batters box": 42,
+    "bayou": 43,
+    "bazaar indoor": 44,
+    "bazaar outdoor": 45,
+    "beach": 46,
+    "beauty salon": 47,
+    "bedroom": 48,
+    "berth": 49,
+    "biology laboratory": 50,
+    "bistro indoor": 51,
+    "boardwalk": 52,
+    "boat deck": 53,
+    "boathouse": 54,
+    "bookstore": 55,
+    "booth indoor": 56,
+    "botanical garden": 57,
+    "bow window indoor": 58,
+    "bow window outdoor": 59,
+    "bowling alley": 60,
+    "boxing ring": 61,
+    "brewery indoor": 62,
+    "bridge": 63,
+    "building facade": 64,
+    "bullring": 65,
+    "burial chamber": 66,
+    "bus interior": 67,
+    "butchers shop": 68,
+    "butte": 69,
+    "cabin outdoor": 70,
+    "cafeteria": 71,
+    "campsite": 72,
+    "campus": 73,
+    "canal natural": 74,
+    "canal urban": 75,
+    "candy store": 76,
+    "canyon": 77,
+    "car interior backseat": 78,
+    "car interior frontseat": 79,
+    "carrousel": 80,
+    "casino indoor": 81,
+    "castle": 82,
+    "catacomb": 83,
+    "cathedral indoor": 84,
+    "cathedral outdoor": 85,
+    "cavern indoor": 86,
+    "cemetery": 87,
+    "chalet": 88,
+    "cheese factory": 89,
+    "chemistry lab": 90,
+    "chicken coop indoor": 91,
+    "chicken coop outdoor": 92,
+    "childs room": 93,
+    "church indoor": 94,
+    "church outdoor": 95,
+    "classroom": 96,
+    "clean room": 97,
+    "cliff": 98,
+    "cloister indoor": 99,
+    "closet": 100,
+    "clothing store": 101,
+    "coast": 102,
+    "cockpit": 103,
+    "coffee shop": 104,
+    "computer room": 105,
+    "conference center": 106,
+    "conference room": 107,
+    "construction site": 108,
+    "control room": 109,
+    "control tower outdoor": 110,
+    "corn field": 111,
+    "corral": 112,
+    "corridor": 113,
+    "cottage garden": 114,
+    "courthouse": 115,
+    "courtroom": 116,
+    "courtyard": 117,
+    "covered bridge exterior": 118,
+    "creek": 119,
+    "crevasse": 120,
+    "crosswalk": 121,
+    "cubicle office": 122,
+    "dam": 123,
+    "delicatessen": 124,
+    "dentists office": 125,
+    "desert sand": 126,
+    "desert vegetation": 127,
+    "diner indoor": 128,
+    "diner outdoor": 129,
+    "dinette home": 130,
+    "dinette vehicle": 131,
+    "dining car": 132,
+    "dining room": 133,
+    "discotheque": 134,
+    "dock": 135,
+    "doorway outdoor": 136,
+    "dorm room": 137,
+    "driveway": 138,
+    "driving range outdoor": 139,
+    "drugstore": 140,
+    "electrical substation": 141,
+    "elevator door": 142,
+    "elevator interior": 143,
+    "elevator shaft": 144,
+    "engine room": 145,
+    "escalator indoor": 146,
+    "excavation": 147,
+    "factory indoor": 148,
+    "fairway": 149,
+    "fastfood restaurant": 150,
+    "field cultivated": 151,
+    "field wild": 152,
+    "fire escape": 153,
+    "fire station": 154,
+    "firing range indoor": 155,
+    "fishpond": 156,
+    "florist shop indoor": 157,
+    "food court": 158,
+    "forest broadleaf": 159,
+    "forest needleleaf": 160,
+    "forest path": 161,
+    "forest road": 162,
+    "formal garden": 163,
+    "fountain": 164,
+    "galley": 165,
+    "game room": 166,
+    "garage indoor": 167,
+    "garbage dump": 168,
+    "gas station": 169,
+    "gazebo exterior": 170,
+    "general store indoor": 171,
+    "general store outdoor": 172,
+    "gift shop": 173,
+    "golf course": 174,
+    "greenhouse indoor": 175,
+    "greenhouse outdoor": 176,
+    "gymnasium indoor": 177,
+    "hangar indoor": 178,
+    "hangar outdoor": 179,
+    "harbor": 180,
+    "hayfield": 181,
+    "heliport": 182,
+    "herb garden": 183,
+    "highway": 184,
+    "hill": 185,
+    "home office": 186,
+    "hospital": 187,
+    "hospital room": 188,
+    "hot spring": 189,
+    "hot tub outdoor": 190,
+    "hotel outdoor": 191,
+    "hotel room": 192,
+    "house": 193,
+    "hunting lodge outdoor": 194,
+    "ice cream parlor": 195,
+    "ice floe": 196,
+    "ice shelf": 197,
+    "ice skating rink indoor": 198,
+    "ice skating rink outdoor": 199,
+    "iceberg": 200,
+    "igloo": 201,
+    "industrial area": 202,
+    "inn outdoor": 203,
+    "islet": 204,
+    "jacuzzi indoor": 205,
+    "jail cell": 206,
+    "jail indoor": 207,
+    "jewelry shop": 208,
+    "kasbah": 209,
+    "kennel indoor": 210,
+    "kennel outdoor": 211,
+    "kindergarden classroom": 212,
+    "kitchen": 213,
+    "kitchenette": 214,
+    "labyrinth outdoor": 215,
+    "lake natural": 216,
+    "landfill": 217,
+    "landing deck": 218,
+    "laundromat": 219,
+    "lecture room": 220,
+    "library indoor": 221,
+    "library outdoor": 222,
+    "lido deck outdoor": 223,
+    "lift bridge": 224,
+    "lighthouse": 225,
+    "limousine interior": 226,
+    "living room": 227,
+    "lobby": 228,
+    "lock chamber": 229,
+    "locker room": 230,
+    "mansion": 231,
+    "manufactured home": 232,
+    "market indoor": 233,
+    "market outdoor": 234,
+    "marsh": 235,
+    "martial arts gym": 236,
+    "mausoleum": 237,
+    "medina": 238,
+    "moat water": 239,
+    "monastery outdoor": 240,
+    "mosque indoor": 241,
+    "mosque outdoor": 242,
+    "motel": 243,
+    "mountain": 244,
+    "mountain snowy": 245,
+    "movie theater indoor": 246,
+    "museum indoor": 247,
+    "music store": 248,
+    "music studio": 249,
+    "nuclear power plant outdoor": 250,
+    "nursery": 251,
+    "oast house": 252,
+    "observatory outdoor": 253,
+    "ocean": 254,
+    "office": 255,
+    "office building": 256,
+    "oil refinery outdoor": 257,
+    "oilrig": 258,
+    "operating room": 259,
+    "orchard": 260,
+    "outhouse outdoor": 261,
+    "pagoda": 262,
+    "palace": 263,
+    "pantry": 264,
+    "park": 265,
+    "parking garage indoor": 266,
+    "parking garage outdoor": 267,
+    "parking lot": 268,
+    "parlor": 269,
+    "pasture": 270,
+    "patio": 271,
+    "pavilion": 272,
+    "pharmacy": 273,
+    "phone booth": 274,
+    "physics laboratory": 275,
+    "picnic area": 276,
+    "pilothouse indoor": 277,
+    "planetarium outdoor": 278,
+    "playground": 279,
+    "playroom": 280,
+    "plaza": 281,
+    "podium indoor": 282,
+    "podium outdoor": 283,
+    "pond": 284,
+    "poolroom establishment": 285,
+    "poolroom home": 286,
+    "power plant outdoor": 287,
+    "promenade deck": 288,
+    "pub indoor": 289,
+    "pulpit": 290,
+    "putting green": 291,
+    "racecourse": 292,
+    "raceway": 293,
+    "raft": 294,
+    "railroad track": 295,
+    "rainforest": 296,
+    "reception": 297,
+    "recreation room": 298,
+    "residential neighborhood": 299,
+    "restaurant": 300,
+    "restaurant kitchen": 301,
+    "restaurant patio": 302,
+    "rice paddy": 303,
+    "riding arena": 304,
+    "river": 305,
+    "rock arch": 306,
+    "rope bridge": 307,
+    "ruin": 308,
+    "runway": 309,
+    "sandbar": 310,
+    "sandbox": 311,
+    "sauna": 312,
+    "schoolhouse": 313,
+    "sea cliff": 314,
+    "server room": 315,
+    "shed": 316,
+    "shoe shop": 317,
+    "shopfront": 318,
+    "shopping mall indoor": 319,
+    "shower": 320,
+    "skatepark": 321,
+    "ski lodge": 322,
+    "ski resort": 323,
+    "ski slope": 324,
+    "sky": 325,
+    "skyscraper": 326,
+    "slum": 327,
+    "snowfield": 328,
+    "squash court": 329,
+    "stable": 330,
+    "stadium baseball": 331,
+    "stadium football": 332,
+    "stage indoor": 333,
+    "staircase": 334,
+    "street": 335,
+    "subway interior": 336,
+    "subway station platform": 337,
+    "supermarket": 338,
+    "sushi bar": 339,
+    "swamp": 340,
+    "swimming pool indoor": 341,
+    "swimming pool outdoor": 342,
+    "synagogue indoor": 343,
+    "synagogue outdoor": 344,
+    "television studio": 345,
+    "temple east asia": 346,
+    "temple south asia": 347,
+    "tennis court indoor": 348,
+    "tennis court outdoor": 349,
+    "tent outdoor": 350,
+    "theater indoor procenium": 351,
+    "theater indoor seats": 352,
+    "thriftshop": 353,
+    "throne room": 354,
+    "ticket booth": 355,
+    "toll plaza": 356,
+    "topiary garden": 357,
+    "tower": 358,
+    "toyshop": 359,
+    "track outdoor": 360,
+    "train railway": 361,
+    "train station platform": 362,
+    "tree farm": 363,
+    "tree house": 364,
+    "trench": 365,
+    "underwater coral reef": 366,
+    "utility room": 367,
+    "valley": 368,
+    "van interior": 369,
+    "vegetable garden": 370,
+    "veranda": 371,
+    "veterinarians office": 372,
+    "viaduct": 373,
+    "videostore": 374,
+    "village": 375,
+    "vineyard": 376,
+    "volcano": 377,
+    "volleyball court indoor": 378,
+    "volleyball court outdoor": 379,
+    "waiting room": 380,
+    "warehouse indoor": 381,
+    "water tower": 382,
+    "waterfall block": 383,
+    "waterfall fan": 384,
+    "waterfall plunge": 385,
+    "watering hole": 386,
+    "wave": 387,
+    "wet bar": 388,
+    "wheat field": 389,
+    "wind farm": 390,
+    "windmill": 391,
+    "wine cellar barrel storage": 392,
+    "wine cellar bottle storage": 393,
+    "wrestling ring indoor": 394,
+    "yard": 395,
+    "youth hostel": 396
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/README.md b/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..2789ea2b66954b85d2f4b2089ac543c3a81efd75
--- /dev/null
+++ b/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset sun397.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: sun397
+    pretrained: true
+test_datasets: null
+train_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: train
+type: transformers
+val_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: test
+```
+
diff --git a/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/config.json b/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..7b3f0b16022576c1d5cf54a17e75ff9088c89b17
--- /dev/null
+++ b/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/config.json
@@ -0,0 +1,837 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "abbey",
+    "1": "airplane cabin",
+    "2": "airport terminal",
+    "3": "alley",
+    "4": "amphitheater",
+    "5": "amusement arcade",
+    "6": "amusement park",
+    "7": "anechoic chamber",
+    "8": "apartment building outdoor",
+    "9": "apse indoor",
+    "10": "aquarium",
+    "11": "aqueduct",
+    "12": "arch",
+    "13": "archive",
+    "14": "arrival gate outdoor",
+    "15": "art gallery",
+    "16": "art school",
+    "17": "art studio",
+    "18": "assembly line",
+    "19": "athletic field outdoor",
+    "20": "atrium public",
+    "21": "attic",
+    "22": "auditorium",
+    "23": "auto factory",
+    "24": "badlands",
+    "25": "badminton court indoor",
+    "26": "baggage claim",
+    "27": "bakery shop",
+    "28": "balcony exterior",
+    "29": "balcony interior",
+    "30": "ball pit",
+    "31": "ballroom",
+    "32": "bamboo forest",
+    "33": "banquet hall",
+    "34": "bar",
+    "35": "barn",
+    "36": "barndoor",
+    "37": "baseball field",
+    "38": "basement",
+    "39": "basilica",
+    "40": "basketball court outdoor",
+    "41": "bathroom",
+    "42": "batters box",
+    "43": "bayou",
+    "44": "bazaar indoor",
+    "45": "bazaar outdoor",
+    "46": "beach",
+    "47": "beauty salon",
+    "48": "bedroom",
+    "49": "berth",
+    "50": "biology laboratory",
+    "51": "bistro indoor",
+    "52": "boardwalk",
+    "53": "boat deck",
+    "54": "boathouse",
+    "55": "bookstore",
+    "56": "booth indoor",
+    "57": "botanical garden",
+    "58": "bow window indoor",
+    "59": "bow window outdoor",
+    "60": "bowling alley",
+    "61": "boxing ring",
+    "62": "brewery indoor",
+    "63": "bridge",
+    "64": "building facade",
+    "65": "bullring",
+    "66": "burial chamber",
+    "67": "bus interior",
+    "68": "butchers shop",
+    "69": "butte",
+    "70": "cabin outdoor",
+    "71": "cafeteria",
+    "72": "campsite",
+    "73": "campus",
+    "74": "canal natural",
+    "75": "canal urban",
+    "76": "candy store",
+    "77": "canyon",
+    "78": "car interior backseat",
+    "79": "car interior frontseat",
+    "80": "carrousel",
+    "81": "casino indoor",
+    "82": "castle",
+    "83": "catacomb",
+    "84": "cathedral indoor",
+    "85": "cathedral outdoor",
+    "86": "cavern indoor",
+    "87": "cemetery",
+    "88": "chalet",
+    "89": "cheese factory",
+    "90": "chemistry lab",
+    "91": "chicken coop indoor",
+    "92": "chicken coop outdoor",
+    "93": "childs room",
+    "94": "church indoor",
+    "95": "church outdoor",
+    "96": "classroom",
+    "97": "clean room",
+    "98": "cliff",
+    "99": "cloister indoor",
+    "100": "closet",
+    "101": "clothing store",
+    "102": "coast",
+    "103": "cockpit",
+    "104": "coffee shop",
+    "105": "computer room",
+    "106": "conference center",
+    "107": "conference room",
+    "108": "construction site",
+    "109": "control room",
+    "110": "control tower outdoor",
+    "111": "corn field",
+    "112": "corral",
+    "113": "corridor",
+    "114": "cottage garden",
+    "115": "courthouse",
+    "116": "courtroom",
+    "117": "courtyard",
+    "118": "covered bridge exterior",
+    "119": "creek",
+    "120": "crevasse",
+    "121": "crosswalk",
+    "122": "cubicle office",
+    "123": "dam",
+    "124": "delicatessen",
+    "125": "dentists office",
+    "126": "desert sand",
+    "127": "desert vegetation",
+    "128": "diner indoor",
+    "129": "diner outdoor",
+    "130": "dinette home",
+    "131": "dinette vehicle",
+    "132": "dining car",
+    "133": "dining room",
+    "134": "discotheque",
+    "135": "dock",
+    "136": "doorway outdoor",
+    "137": "dorm room",
+    "138": "driveway",
+    "139": "driving range outdoor",
+    "140": "drugstore",
+    "141": "electrical substation",
+    "142": "elevator door",
+    "143": "elevator interior",
+    "144": "elevator shaft",
+    "145": "engine room",
+    "146": "escalator indoor",
+    "147": "excavation",
+    "148": "factory indoor",
+    "149": "fairway",
+    "150": "fastfood restaurant",
+    "151": "field cultivated",
+    "152": "field wild",
+    "153": "fire escape",
+    "154": "fire station",
+    "155": "firing range indoor",
+    "156": "fishpond",
+    "157": "florist shop indoor",
+    "158": "food court",
+    "159": "forest broadleaf",
+    "160": "forest needleleaf",
+    "161": "forest path",
+    "162": "forest road",
+    "163": "formal garden",
+    "164": "fountain",
+    "165": "galley",
+    "166": "game room",
+    "167": "garage indoor",
+    "168": "garbage dump",
+    "169": "gas station",
+    "170": "gazebo exterior",
+    "171": "general store indoor",
+    "172": "general store outdoor",
+    "173": "gift shop",
+    "174": "golf course",
+    "175": "greenhouse indoor",
+    "176": "greenhouse outdoor",
+    "177": "gymnasium indoor",
+    "178": "hangar indoor",
+    "179": "hangar outdoor",
+    "180": "harbor",
+    "181": "hayfield",
+    "182": "heliport",
+    "183": "herb garden",
+    "184": "highway",
+    "185": "hill",
+    "186": "home office",
+    "187": "hospital",
+    "188": "hospital room",
+    "189": "hot spring",
+    "190": "hot tub outdoor",
+    "191": "hotel outdoor",
+    "192": "hotel room",
+    "193": "house",
+    "194": "hunting lodge outdoor",
+    "195": "ice cream parlor",
+    "196": "ice floe",
+    "197": "ice shelf",
+    "198": "ice skating rink indoor",
+    "199": "ice skating rink outdoor",
+    "200": "iceberg",
+    "201": "igloo",
+    "202": "industrial area",
+    "203": "inn outdoor",
+    "204": "islet",
+    "205": "jacuzzi indoor",
+    "206": "jail cell",
+    "207": "jail indoor",
+    "208": "jewelry shop",
+    "209": "kasbah",
+    "210": "kennel indoor",
+    "211": "kennel outdoor",
+    "212": "kindergarden classroom",
+    "213": "kitchen",
+    "214": "kitchenette",
+    "215": "labyrinth outdoor",
+    "216": "lake natural",
+    "217": "landfill",
+    "218": "landing deck",
+    "219": "laundromat",
+    "220": "lecture room",
+    "221": "library indoor",
+    "222": "library outdoor",
+    "223": "lido deck outdoor",
+    "224": "lift bridge",
+    "225": "lighthouse",
+    "226": "limousine interior",
+    "227": "living room",
+    "228": "lobby",
+    "229": "lock chamber",
+    "230": "locker room",
+    "231": "mansion",
+    "232": "manufactured home",
+    "233": "market indoor",
+    "234": "market outdoor",
+    "235": "marsh",
+    "236": "martial arts gym",
+    "237": "mausoleum",
+    "238": "medina",
+    "239": "moat water",
+    "240": "monastery outdoor",
+    "241": "mosque indoor",
+    "242": "mosque outdoor",
+    "243": "motel",
+    "244": "mountain",
+    "245": "mountain snowy",
+    "246": "movie theater indoor",
+    "247": "museum indoor",
+    "248": "music store",
+    "249": "music studio",
+    "250": "nuclear power plant outdoor",
+    "251": "nursery",
+    "252": "oast house",
+    "253": "observatory outdoor",
+    "254": "ocean",
+    "255": "office",
+    "256": "office building",
+    "257": "oil refinery outdoor",
+    "258": "oilrig",
+    "259": "operating room",
+    "260": "orchard",
+    "261": "outhouse outdoor",
+    "262": "pagoda",
+    "263": "palace",
+    "264": "pantry",
+    "265": "park",
+    "266": "parking garage indoor",
+    "267": "parking garage outdoor",
+    "268": "parking lot",
+    "269": "parlor",
+    "270": "pasture",
+    "271": "patio",
+    "272": "pavilion",
+    "273": "pharmacy",
+    "274": "phone booth",
+    "275": "physics laboratory",
+    "276": "picnic area",
+    "277": "pilothouse indoor",
+    "278": "planetarium outdoor",
+    "279": "playground",
+    "280": "playroom",
+    "281": "plaza",
+    "282": "podium indoor",
+    "283": "podium outdoor",
+    "284": "pond",
+    "285": "poolroom establishment",
+    "286": "poolroom home",
+    "287": "power plant outdoor",
+    "288": "promenade deck",
+    "289": "pub indoor",
+    "290": "pulpit",
+    "291": "putting green",
+    "292": "racecourse",
+    "293": "raceway",
+    "294": "raft",
+    "295": "railroad track",
+    "296": "rainforest",
+    "297": "reception",
+    "298": "recreation room",
+    "299": "residential neighborhood",
+    "300": "restaurant",
+    "301": "restaurant kitchen",
+    "302": "restaurant patio",
+    "303": "rice paddy",
+    "304": "riding arena",
+    "305": "river",
+    "306": "rock arch",
+    "307": "rope bridge",
+    "308": "ruin",
+    "309": "runway",
+    "310": "sandbar",
+    "311": "sandbox",
+    "312": "sauna",
+    "313": "schoolhouse",
+    "314": "sea cliff",
+    "315": "server room",
+    "316": "shed",
+    "317": "shoe shop",
+    "318": "shopfront",
+    "319": "shopping mall indoor",
+    "320": "shower",
+    "321": "skatepark",
+    "322": "ski lodge",
+    "323": "ski resort",
+    "324": "ski slope",
+    "325": "sky",
+    "326": "skyscraper",
+    "327": "slum",
+    "328": "snowfield",
+    "329": "squash court",
+    "330": "stable",
+    "331": "stadium baseball",
+    "332": "stadium football",
+    "333": "stage indoor",
+    "334": "staircase",
+    "335": "street",
+    "336": "subway interior",
+    "337": "subway station platform",
+    "338": "supermarket",
+    "339": "sushi bar",
+    "340": "swamp",
+    "341": "swimming pool indoor",
+    "342": "swimming pool outdoor",
+    "343": "synagogue indoor",
+    "344": "synagogue outdoor",
+    "345": "television studio",
+    "346": "temple east asia",
+    "347": "temple south asia",
+    "348": "tennis court indoor",
+    "349": "tennis court outdoor",
+    "350": "tent outdoor",
+    "351": "theater indoor procenium",
+    "352": "theater indoor seats",
+    "353": "thriftshop",
+    "354": "throne room",
+    "355": "ticket booth",
+    "356": "toll plaza",
+    "357": "topiary garden",
+    "358": "tower",
+    "359": "toyshop",
+    "360": "track outdoor",
+    "361": "train railway",
+    "362": "train station platform",
+    "363": "tree farm",
+    "364": "tree house",
+    "365": "trench",
+    "366": "underwater coral reef",
+    "367": "utility room",
+    "368": "valley",
+    "369": "van interior",
+    "370": "vegetable garden",
+    "371": "veranda",
+    "372": "veterinarians office",
+    "373": "viaduct",
+    "374": "videostore",
+    "375": "village",
+    "376": "vineyard",
+    "377": "volcano",
+    "378": "volleyball court indoor",
+    "379": "volleyball court outdoor",
+    "380": "waiting room",
+    "381": "warehouse indoor",
+    "382": "water tower",
+    "383": "waterfall block",
+    "384": "waterfall fan",
+    "385": "waterfall plunge",
+    "386": "watering hole",
+    "387": "wave",
+    "388": "wet bar",
+    "389": "wheat field",
+    "390": "wind farm",
+    "391": "windmill",
+    "392": "wine cellar barrel storage",
+    "393": "wine cellar bottle storage",
+    "394": "wrestling ring indoor",
+    "395": "yard",
+    "396": "youth hostel"
+  },
+  "label2id": {
+    "abbey": 0,
+    "airplane cabin": 1,
+    "airport terminal": 2,
+    "alley": 3,
+    "amphitheater": 4,
+    "amusement arcade": 5,
+    "amusement park": 6,
+    "anechoic chamber": 7,
+    "apartment building outdoor": 8,
+    "apse indoor": 9,
+    "aquarium": 10,
+    "aqueduct": 11,
+    "arch": 12,
+    "archive": 13,
+    "arrival gate outdoor": 14,
+    "art gallery": 15,
+    "art school": 16,
+    "art studio": 17,
+    "assembly line": 18,
+    "athletic field outdoor": 19,
+    "atrium public": 20,
+    "attic": 21,
+    "auditorium": 22,
+    "auto factory": 23,
+    "badlands": 24,
+    "badminton court indoor": 25,
+    "baggage claim": 26,
+    "bakery shop": 27,
+    "balcony exterior": 28,
+    "balcony interior": 29,
+    "ball pit": 30,
+    "ballroom": 31,
+    "bamboo forest": 32,
+    "banquet hall": 33,
+    "bar": 34,
+    "barn": 35,
+    "barndoor": 36,
+    "baseball field": 37,
+    "basement": 38,
+    "basilica": 39,
+    "basketball court outdoor": 40,
+    "bathroom": 41,
+    "batters box": 42,
+    "bayou": 43,
+    "bazaar indoor": 44,
+    "bazaar outdoor": 45,
+    "beach": 46,
+    "beauty salon": 47,
+    "bedroom": 48,
+    "berth": 49,
+    "biology laboratory": 50,
+    "bistro indoor": 51,
+    "boardwalk": 52,
+    "boat deck": 53,
+    "boathouse": 54,
+    "bookstore": 55,
+    "booth indoor": 56,
+    "botanical garden": 57,
+    "bow window indoor": 58,
+    "bow window outdoor": 59,
+    "bowling alley": 60,
+    "boxing ring": 61,
+    "brewery indoor": 62,
+    "bridge": 63,
+    "building facade": 64,
+    "bullring": 65,
+    "burial chamber": 66,
+    "bus interior": 67,
+    "butchers shop": 68,
+    "butte": 69,
+    "cabin outdoor": 70,
+    "cafeteria": 71,
+    "campsite": 72,
+    "campus": 73,
+    "canal natural": 74,
+    "canal urban": 75,
+    "candy store": 76,
+    "canyon": 77,
+    "car interior backseat": 78,
+    "car interior frontseat": 79,
+    "carrousel": 80,
+    "casino indoor": 81,
+    "castle": 82,
+    "catacomb": 83,
+    "cathedral indoor": 84,
+    "cathedral outdoor": 85,
+    "cavern indoor": 86,
+    "cemetery": 87,
+    "chalet": 88,
+    "cheese factory": 89,
+    "chemistry lab": 90,
+    "chicken coop indoor": 91,
+    "chicken coop outdoor": 92,
+    "childs room": 93,
+    "church indoor": 94,
+    "church outdoor": 95,
+    "classroom": 96,
+    "clean room": 97,
+    "cliff": 98,
+    "cloister indoor": 99,
+    "closet": 100,
+    "clothing store": 101,
+    "coast": 102,
+    "cockpit": 103,
+    "coffee shop": 104,
+    "computer room": 105,
+    "conference center": 106,
+    "conference room": 107,
+    "construction site": 108,
+    "control room": 109,
+    "control tower outdoor": 110,
+    "corn field": 111,
+    "corral": 112,
+    "corridor": 113,
+    "cottage garden": 114,
+    "courthouse": 115,
+    "courtroom": 116,
+    "courtyard": 117,
+    "covered bridge exterior": 118,
+    "creek": 119,
+    "crevasse": 120,
+    "crosswalk": 121,
+    "cubicle office": 122,
+    "dam": 123,
+    "delicatessen": 124,
+    "dentists office": 125,
+    "desert sand": 126,
+    "desert vegetation": 127,
+    "diner indoor": 128,
+    "diner outdoor": 129,
+    "dinette home": 130,
+    "dinette vehicle": 131,
+    "dining car": 132,
+    "dining room": 133,
+    "discotheque": 134,
+    "dock": 135,
+    "doorway outdoor": 136,
+    "dorm room": 137,
+    "driveway": 138,
+    "driving range outdoor": 139,
+    "drugstore": 140,
+    "electrical substation": 141,
+    "elevator door": 142,
+    "elevator interior": 143,
+    "elevator shaft": 144,
+    "engine room": 145,
+    "escalator indoor": 146,
+    "excavation": 147,
+    "factory indoor": 148,
+    "fairway": 149,
+    "fastfood restaurant": 150,
+    "field cultivated": 151,
+    "field wild": 152,
+    "fire escape": 153,
+    "fire station": 154,
+    "firing range indoor": 155,
+    "fishpond": 156,
+    "florist shop indoor": 157,
+    "food court": 158,
+    "forest broadleaf": 159,
+    "forest needleleaf": 160,
+    "forest path": 161,
+    "forest road": 162,
+    "formal garden": 163,
+    "fountain": 164,
+    "galley": 165,
+    "game room": 166,
+    "garage indoor": 167,
+    "garbage dump": 168,
+    "gas station": 169,
+    "gazebo exterior": 170,
+    "general store indoor": 171,
+    "general store outdoor": 172,
+    "gift shop": 173,
+    "golf course": 174,
+    "greenhouse indoor": 175,
+    "greenhouse outdoor": 176,
+    "gymnasium indoor": 177,
+    "hangar indoor": 178,
+    "hangar outdoor": 179,
+    "harbor": 180,
+    "hayfield": 181,
+    "heliport": 182,
+    "herb garden": 183,
+    "highway": 184,
+    "hill": 185,
+    "home office": 186,
+    "hospital": 187,
+    "hospital room": 188,
+    "hot spring": 189,
+    "hot tub outdoor": 190,
+    "hotel outdoor": 191,
+    "hotel room": 192,
+    "house": 193,
+    "hunting lodge outdoor": 194,
+    "ice cream parlor": 195,
+    "ice floe": 196,
+    "ice shelf": 197,
+    "ice skating rink indoor": 198,
+    "ice skating rink outdoor": 199,
+    "iceberg": 200,
+    "igloo": 201,
+    "industrial area": 202,
+    "inn outdoor": 203,
+    "islet": 204,
+    "jacuzzi indoor": 205,
+    "jail cell": 206,
+    "jail indoor": 207,
+    "jewelry shop": 208,
+    "kasbah": 209,
+    "kennel indoor": 210,
+    "kennel outdoor": 211,
+    "kindergarden classroom": 212,
+    "kitchen": 213,
+    "kitchenette": 214,
+    "labyrinth outdoor": 215,
+    "lake natural": 216,
+    "landfill": 217,
+    "landing deck": 218,
+    "laundromat": 219,
+    "lecture room": 220,
+    "library indoor": 221,
+    "library outdoor": 222,
+    "lido deck outdoor": 223,
+    "lift bridge": 224,
+    "lighthouse": 225,
+    "limousine interior": 226,
+    "living room": 227,
+    "lobby": 228,
+    "lock chamber": 229,
+    "locker room": 230,
+    "mansion": 231,
+    "manufactured home": 232,
+    "market indoor": 233,
+    "market outdoor": 234,
+    "marsh": 235,
+    "martial arts gym": 236,
+    "mausoleum": 237,
+    "medina": 238,
+    "moat water": 239,
+    "monastery outdoor": 240,
+    "mosque indoor": 241,
+    "mosque outdoor": 242,
+    "motel": 243,
+    "mountain": 244,
+    "mountain snowy": 245,
+    "movie theater indoor": 246,
+    "museum indoor": 247,
+    "music store": 248,
+    "music studio": 249,
+    "nuclear power plant outdoor": 250,
+    "nursery": 251,
+    "oast house": 252,
+    "observatory outdoor": 253,
+    "ocean": 254,
+    "office": 255,
+    "office building": 256,
+    "oil refinery outdoor": 257,
+    "oilrig": 258,
+    "operating room": 259,
+    "orchard": 260,
+    "outhouse outdoor": 261,
+    "pagoda": 262,
+    "palace": 263,
+    "pantry": 264,
+    "park": 265,
+    "parking garage indoor": 266,
+    "parking garage outdoor": 267,
+    "parking lot": 268,
+    "parlor": 269,
+    "pasture": 270,
+    "patio": 271,
+    "pavilion": 272,
+    "pharmacy": 273,
+    "phone booth": 274,
+    "physics laboratory": 275,
+    "picnic area": 276,
+    "pilothouse indoor": 277,
+    "planetarium outdoor": 278,
+    "playground": 279,
+    "playroom": 280,
+    "plaza": 281,
+    "podium indoor": 282,
+    "podium outdoor": 283,
+    "pond": 284,
+    "poolroom establishment": 285,
+    "poolroom home": 286,
+    "power plant outdoor": 287,
+    "promenade deck": 288,
+    "pub indoor": 289,
+    "pulpit": 290,
+    "putting green": 291,
+    "racecourse": 292,
+    "raceway": 293,
+    "raft": 294,
+    "railroad track": 295,
+    "rainforest": 296,
+    "reception": 297,
+    "recreation room": 298,
+    "residential neighborhood": 299,
+    "restaurant": 300,
+    "restaurant kitchen": 301,
+    "restaurant patio": 302,
+    "rice paddy": 303,
+    "riding arena": 304,
+    "river": 305,
+    "rock arch": 306,
+    "rope bridge": 307,
+    "ruin": 308,
+    "runway": 309,
+    "sandbar": 310,
+    "sandbox": 311,
+    "sauna": 312,
+    "schoolhouse": 313,
+    "sea cliff": 314,
+    "server room": 315,
+    "shed": 316,
+    "shoe shop": 317,
+    "shopfront": 318,
+    "shopping mall indoor": 319,
+    "shower": 320,
+    "skatepark": 321,
+    "ski lodge": 322,
+    "ski resort": 323,
+    "ski slope": 324,
+    "sky": 325,
+    "skyscraper": 326,
+    "slum": 327,
+    "snowfield": 328,
+    "squash court": 329,
+    "stable": 330,
+    "stadium baseball": 331,
+    "stadium football": 332,
+    "stage indoor": 333,
+    "staircase": 334,
+    "street": 335,
+    "subway interior": 336,
+    "subway station platform": 337,
+    "supermarket": 338,
+    "sushi bar": 339,
+    "swamp": 340,
+    "swimming pool indoor": 341,
+    "swimming pool outdoor": 342,
+    "synagogue indoor": 343,
+    "synagogue outdoor": 344,
+    "television studio": 345,
+    "temple east asia": 346,
+    "temple south asia": 347,
+    "tennis court indoor": 348,
+    "tennis court outdoor": 349,
+    "tent outdoor": 350,
+    "theater indoor procenium": 351,
+    "theater indoor seats": 352,
+    "thriftshop": 353,
+    "throne room": 354,
+    "ticket booth": 355,
+    "toll plaza": 356,
+    "topiary garden": 357,
+    "tower": 358,
+    "toyshop": 359,
+    "track outdoor": 360,
+    "train railway": 361,
+    "train station platform": 362,
+    "tree farm": 363,
+    "tree house": 364,
+    "trench": 365,
+    "underwater coral reef": 366,
+    "utility room": 367,
+    "valley": 368,
+    "van interior": 369,
+    "vegetable garden": 370,
+    "veranda": 371,
+    "veterinarians office": 372,
+    "viaduct": 373,
+    "videostore": 374,
+    "village": 375,
+    "vineyard": 376,
+    "volcano": 377,
+    "volleyball court indoor": 378,
+    "volleyball court outdoor": 379,
+    "waiting room": 380,
+    "warehouse indoor": 381,
+    "water tower": 382,
+    "waterfall block": 383,
+    "waterfall fan": 384,
+    "waterfall plunge": 385,
+    "watering hole": 386,
+    "wave": 387,
+    "wet bar": 388,
+    "wheat field": 389,
+    "wind farm": 390,
+    "windmill": 391,
+    "wine cellar barrel storage": 392,
+    "wine cellar bottle storage": 393,
+    "wrestling ring indoor": 394,
+    "yard": 395,
+    "youth hostel": 396
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/README.md b/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..b2ad5c3a73458198cca76ffb72012b7dbffd3cc4
--- /dev/null
+++ b/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset sun397.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: sun397
+    pretrained: true
+test_datasets: null
+train_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: train
+type: transformers
+val_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: test
+```
+
diff --git a/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/config.json b/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..7b3f0b16022576c1d5cf54a17e75ff9088c89b17
--- /dev/null
+++ b/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/config.json
@@ -0,0 +1,837 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "abbey",
+    "1": "airplane cabin",
+    "2": "airport terminal",
+    "3": "alley",
+    "4": "amphitheater",
+    "5": "amusement arcade",
+    "6": "amusement park",
+    "7": "anechoic chamber",
+    "8": "apartment building outdoor",
+    "9": "apse indoor",
+    "10": "aquarium",
+    "11": "aqueduct",
+    "12": "arch",
+    "13": "archive",
+    "14": "arrival gate outdoor",
+    "15": "art gallery",
+    "16": "art school",
+    "17": "art studio",
+    "18": "assembly line",
+    "19": "athletic field outdoor",
+    "20": "atrium public",
+    "21": "attic",
+    "22": "auditorium",
+    "23": "auto factory",
+    "24": "badlands",
+    "25": "badminton court indoor",
+    "26": "baggage claim",
+    "27": "bakery shop",
+    "28": "balcony exterior",
+    "29": "balcony interior",
+    "30": "ball pit",
+    "31": "ballroom",
+    "32": "bamboo forest",
+    "33": "banquet hall",
+    "34": "bar",
+    "35": "barn",
+    "36": "barndoor",
+    "37": "baseball field",
+    "38": "basement",
+    "39": "basilica",
+    "40": "basketball court outdoor",
+    "41": "bathroom",
+    "42": "batters box",
+    "43": "bayou",
+    "44": "bazaar indoor",
+    "45": "bazaar outdoor",
+    "46": "beach",
+    "47": "beauty salon",
+    "48": "bedroom",
+    "49": "berth",
+    "50": "biology laboratory",
+    "51": "bistro indoor",
+    "52": "boardwalk",
+    "53": "boat deck",
+    "54": "boathouse",
+    "55": "bookstore",
+    "56": "booth indoor",
+    "57": "botanical garden",
+    "58": "bow window indoor",
+    "59": "bow window outdoor",
+    "60": "bowling alley",
+    "61": "boxing ring",
+    "62": "brewery indoor",
+    "63": "bridge",
+    "64": "building facade",
+    "65": "bullring",
+    "66": "burial chamber",
+    "67": "bus interior",
+    "68": "butchers shop",
+    "69": "butte",
+    "70": "cabin outdoor",
+    "71": "cafeteria",
+    "72": "campsite",
+    "73": "campus",
+    "74": "canal natural",
+    "75": "canal urban",
+    "76": "candy store",
+    "77": "canyon",
+    "78": "car interior backseat",
+    "79": "car interior frontseat",
+    "80": "carrousel",
+    "81": "casino indoor",
+    "82": "castle",
+    "83": "catacomb",
+    "84": "cathedral indoor",
+    "85": "cathedral outdoor",
+    "86": "cavern indoor",
+    "87": "cemetery",
+    "88": "chalet",
+    "89": "cheese factory",
+    "90": "chemistry lab",
+    "91": "chicken coop indoor",
+    "92": "chicken coop outdoor",
+    "93": "childs room",
+    "94": "church indoor",
+    "95": "church outdoor",
+    "96": "classroom",
+    "97": "clean room",
+    "98": "cliff",
+    "99": "cloister indoor",
+    "100": "closet",
+    "101": "clothing store",
+    "102": "coast",
+    "103": "cockpit",
+    "104": "coffee shop",
+    "105": "computer room",
+    "106": "conference center",
+    "107": "conference room",
+    "108": "construction site",
+    "109": "control room",
+    "110": "control tower outdoor",
+    "111": "corn field",
+    "112": "corral",
+    "113": "corridor",
+    "114": "cottage garden",
+    "115": "courthouse",
+    "116": "courtroom",
+    "117": "courtyard",
+    "118": "covered bridge exterior",
+    "119": "creek",
+    "120": "crevasse",
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+    "125": "dentists office",
+    "126": "desert sand",
+    "127": "desert vegetation",
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+    "129": "diner outdoor",
+    "130": "dinette home",
+    "131": "dinette vehicle",
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+    "195": "ice cream parlor",
+    "196": "ice floe",
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+    "198": "ice skating rink indoor",
+    "199": "ice skating rink outdoor",
+    "200": "iceberg",
+    "201": "igloo",
+    "202": "industrial area",
+    "203": "inn outdoor",
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+    "205": "jacuzzi indoor",
+    "206": "jail cell",
+    "207": "jail indoor",
+    "208": "jewelry shop",
+    "209": "kasbah",
+    "210": "kennel indoor",
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+    "212": "kindergarden classroom",
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+    "215": "labyrinth outdoor",
+    "216": "lake natural",
+    "217": "landfill",
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+    "219": "laundromat",
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+    "224": "lift bridge",
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+    "238": "medina",
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+    "240": "monastery outdoor",
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+    "244": "mountain",
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+    "250": "nuclear power plant outdoor",
+    "251": "nursery",
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+    "262": "pagoda",
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+    "267": "parking garage outdoor",
+    "268": "parking lot",
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+    "274": "phone booth",
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+    "282": "podium indoor",
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+    "284": "pond",
+    "285": "poolroom establishment",
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+    "288": "promenade deck",
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+    "291": "putting green",
+    "292": "racecourse",
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+    "294": "raft",
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+    "297": "reception",
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+    "299": "residential neighborhood",
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+    "303": "rice paddy",
+    "304": "riding arena",
+    "305": "river",
+    "306": "rock arch",
+    "307": "rope bridge",
+    "308": "ruin",
+    "309": "runway",
+    "310": "sandbar",
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+    "312": "sauna",
+    "313": "schoolhouse",
+    "314": "sea cliff",
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+    "329": "squash court",
+    "330": "stable",
+    "331": "stadium baseball",
+    "332": "stadium football",
+    "333": "stage indoor",
+    "334": "staircase",
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+    "343": "synagogue indoor",
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+    "345": "television studio",
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+    "350": "tent outdoor",
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+    "358": "tower",
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+    "360": "track outdoor",
+    "361": "train railway",
+    "362": "train station platform",
+    "363": "tree farm",
+    "364": "tree house",
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+    "373": "viaduct",
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+    "375": "village",
+    "376": "vineyard",
+    "377": "volcano",
+    "378": "volleyball court indoor",
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+    "382": "water tower",
+    "383": "waterfall block",
+    "384": "waterfall fan",
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+    "386": "watering hole",
+    "387": "wave",
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+    "389": "wheat field",
+    "390": "wind farm",
+    "391": "windmill",
+    "392": "wine cellar barrel storage",
+    "393": "wine cellar bottle storage",
+    "394": "wrestling ring indoor",
+    "395": "yard",
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+  },
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+    "waterfall block": 383,
+    "waterfall fan": 384,
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+    "wheat field": 389,
+    "wind farm": 390,
+    "windmill": 391,
+    "wine cellar barrel storage": 392,
+    "wine cellar bottle storage": 393,
+    "wrestling ring indoor": 394,
+    "yard": 395,
+    "youth hostel": 396
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-sun397-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-sun397-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/README.md b/resnet50-sun397-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..88daa1b5f13afcce3ed228e0476eaa9db2e2fc50
--- /dev/null
+++ b/resnet50-sun397-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,76 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset sun397.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: sun397
+    pretrained: true
+test_datasets: null
+train_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: train
+type: transformers
+val_datasets:
+  sun397:
+    _target_: datasets.load_dataset
+    path: tanganke/sun397
+    split: test
+```
+
diff --git a/resnet50-sun397-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/config.json b/resnet50-sun397-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..7b3f0b16022576c1d5cf54a17e75ff9088c89b17
--- /dev/null
+++ b/resnet50-sun397-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,837 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "abbey",
+    "1": "airplane cabin",
+    "2": "airport terminal",
+    "3": "alley",
+    "4": "amphitheater",
+    "5": "amusement arcade",
+    "6": "amusement park",
+    "7": "anechoic chamber",
+    "8": "apartment building outdoor",
+    "9": "apse indoor",
+    "10": "aquarium",
+    "11": "aqueduct",
+    "12": "arch",
+    "13": "archive",
+    "14": "arrival gate outdoor",
+    "15": "art gallery",
+    "16": "art school",
+    "17": "art studio",
+    "18": "assembly line",
+    "19": "athletic field outdoor",
+    "20": "atrium public",
+    "21": "attic",
+    "22": "auditorium",
+    "23": "auto factory",
+    "24": "badlands",
+    "25": "badminton court indoor",
+    "26": "baggage claim",
+    "27": "bakery shop",
+    "28": "balcony exterior",
+    "29": "balcony interior",
+    "30": "ball pit",
+    "31": "ballroom",
+    "32": "bamboo forest",
+    "33": "banquet hall",
+    "34": "bar",
+    "35": "barn",
+    "36": "barndoor",
+    "37": "baseball field",
+    "38": "basement",
+    "39": "basilica",
+    "40": "basketball court outdoor",
+    "41": "bathroom",
+    "42": "batters box",
+    "43": "bayou",
+    "44": "bazaar indoor",
+    "45": "bazaar outdoor",
+    "46": "beach",
+    "47": "beauty salon",
+    "48": "bedroom",
+    "49": "berth",
+    "50": "biology laboratory",
+    "51": "bistro indoor",
+    "52": "boardwalk",
+    "53": "boat deck",
+    "54": "boathouse",
+    "55": "bookstore",
+    "56": "booth indoor",
+    "57": "botanical garden",
+    "58": "bow window indoor",
+    "59": "bow window outdoor",
+    "60": "bowling alley",
+    "61": "boxing ring",
+    "62": "brewery indoor",
+    "63": "bridge",
+    "64": "building facade",
+    "65": "bullring",
+    "66": "burial chamber",
+    "67": "bus interior",
+    "68": "butchers shop",
+    "69": "butte",
+    "70": "cabin outdoor",
+    "71": "cafeteria",
+    "72": "campsite",
+    "73": "campus",
+    "74": "canal natural",
+    "75": "canal urban",
+    "76": "candy store",
+    "77": "canyon",
+    "78": "car interior backseat",
+    "79": "car interior frontseat",
+    "80": "carrousel",
+    "81": "casino indoor",
+    "82": "castle",
+    "83": "catacomb",
+    "84": "cathedral indoor",
+    "85": "cathedral outdoor",
+    "86": "cavern indoor",
+    "87": "cemetery",
+    "88": "chalet",
+    "89": "cheese factory",
+    "90": "chemistry lab",
+    "91": "chicken coop indoor",
+    "92": "chicken coop outdoor",
+    "93": "childs room",
+    "94": "church indoor",
+    "95": "church outdoor",
+    "96": "classroom",
+    "97": "clean room",
+    "98": "cliff",
+    "99": "cloister indoor",
+    "100": "closet",
+    "101": "clothing store",
+    "102": "coast",
+    "103": "cockpit",
+    "104": "coffee shop",
+    "105": "computer room",
+    "106": "conference center",
+    "107": "conference room",
+    "108": "construction site",
+    "109": "control room",
+    "110": "control tower outdoor",
+    "111": "corn field",
+    "112": "corral",
+    "113": "corridor",
+    "114": "cottage garden",
+    "115": "courthouse",
+    "116": "courtroom",
+    "117": "courtyard",
+    "118": "covered bridge exterior",
+    "119": "creek",
+    "120": "crevasse",
+    "121": "crosswalk",
+    "122": "cubicle office",
+    "123": "dam",
+    "124": "delicatessen",
+    "125": "dentists office",
+    "126": "desert sand",
+    "127": "desert vegetation",
+    "128": "diner indoor",
+    "129": "diner outdoor",
+    "130": "dinette home",
+    "131": "dinette vehicle",
+    "132": "dining car",
+    "133": "dining room",
+    "134": "discotheque",
+    "135": "dock",
+    "136": "doorway outdoor",
+    "137": "dorm room",
+    "138": "driveway",
+    "139": "driving range outdoor",
+    "140": "drugstore",
+    "141": "electrical substation",
+    "142": "elevator door",
+    "143": "elevator interior",
+    "144": "elevator shaft",
+    "145": "engine room",
+    "146": "escalator indoor",
+    "147": "excavation",
+    "148": "factory indoor",
+    "149": "fairway",
+    "150": "fastfood restaurant",
+    "151": "field cultivated",
+    "152": "field wild",
+    "153": "fire escape",
+    "154": "fire station",
+    "155": "firing range indoor",
+    "156": "fishpond",
+    "157": "florist shop indoor",
+    "158": "food court",
+    "159": "forest broadleaf",
+    "160": "forest needleleaf",
+    "161": "forest path",
+    "162": "forest road",
+    "163": "formal garden",
+    "164": "fountain",
+    "165": "galley",
+    "166": "game room",
+    "167": "garage indoor",
+    "168": "garbage dump",
+    "169": "gas station",
+    "170": "gazebo exterior",
+    "171": "general store indoor",
+    "172": "general store outdoor",
+    "173": "gift shop",
+    "174": "golf course",
+    "175": "greenhouse indoor",
+    "176": "greenhouse outdoor",
+    "177": "gymnasium indoor",
+    "178": "hangar indoor",
+    "179": "hangar outdoor",
+    "180": "harbor",
+    "181": "hayfield",
+    "182": "heliport",
+    "183": "herb garden",
+    "184": "highway",
+    "185": "hill",
+    "186": "home office",
+    "187": "hospital",
+    "188": "hospital room",
+    "189": "hot spring",
+    "190": "hot tub outdoor",
+    "191": "hotel outdoor",
+    "192": "hotel room",
+    "193": "house",
+    "194": "hunting lodge outdoor",
+    "195": "ice cream parlor",
+    "196": "ice floe",
+    "197": "ice shelf",
+    "198": "ice skating rink indoor",
+    "199": "ice skating rink outdoor",
+    "200": "iceberg",
+    "201": "igloo",
+    "202": "industrial area",
+    "203": "inn outdoor",
+    "204": "islet",
+    "205": "jacuzzi indoor",
+    "206": "jail cell",
+    "207": "jail indoor",
+    "208": "jewelry shop",
+    "209": "kasbah",
+    "210": "kennel indoor",
+    "211": "kennel outdoor",
+    "212": "kindergarden classroom",
+    "213": "kitchen",
+    "214": "kitchenette",
+    "215": "labyrinth outdoor",
+    "216": "lake natural",
+    "217": "landfill",
+    "218": "landing deck",
+    "219": "laundromat",
+    "220": "lecture room",
+    "221": "library indoor",
+    "222": "library outdoor",
+    "223": "lido deck outdoor",
+    "224": "lift bridge",
+    "225": "lighthouse",
+    "226": "limousine interior",
+    "227": "living room",
+    "228": "lobby",
+    "229": "lock chamber",
+    "230": "locker room",
+    "231": "mansion",
+    "232": "manufactured home",
+    "233": "market indoor",
+    "234": "market outdoor",
+    "235": "marsh",
+    "236": "martial arts gym",
+    "237": "mausoleum",
+    "238": "medina",
+    "239": "moat water",
+    "240": "monastery outdoor",
+    "241": "mosque indoor",
+    "242": "mosque outdoor",
+    "243": "motel",
+    "244": "mountain",
+    "245": "mountain snowy",
+    "246": "movie theater indoor",
+    "247": "museum indoor",
+    "248": "music store",
+    "249": "music studio",
+    "250": "nuclear power plant outdoor",
+    "251": "nursery",
+    "252": "oast house",
+    "253": "observatory outdoor",
+    "254": "ocean",
+    "255": "office",
+    "256": "office building",
+    "257": "oil refinery outdoor",
+    "258": "oilrig",
+    "259": "operating room",
+    "260": "orchard",
+    "261": "outhouse outdoor",
+    "262": "pagoda",
+    "263": "palace",
+    "264": "pantry",
+    "265": "park",
+    "266": "parking garage indoor",
+    "267": "parking garage outdoor",
+    "268": "parking lot",
+    "269": "parlor",
+    "270": "pasture",
+    "271": "patio",
+    "272": "pavilion",
+    "273": "pharmacy",
+    "274": "phone booth",
+    "275": "physics laboratory",
+    "276": "picnic area",
+    "277": "pilothouse indoor",
+    "278": "planetarium outdoor",
+    "279": "playground",
+    "280": "playroom",
+    "281": "plaza",
+    "282": "podium indoor",
+    "283": "podium outdoor",
+    "284": "pond",
+    "285": "poolroom establishment",
+    "286": "poolroom home",
+    "287": "power plant outdoor",
+    "288": "promenade deck",
+    "289": "pub indoor",
+    "290": "pulpit",
+    "291": "putting green",
+    "292": "racecourse",
+    "293": "raceway",
+    "294": "raft",
+    "295": "railroad track",
+    "296": "rainforest",
+    "297": "reception",
+    "298": "recreation room",
+    "299": "residential neighborhood",
+    "300": "restaurant",
+    "301": "restaurant kitchen",
+    "302": "restaurant patio",
+    "303": "rice paddy",
+    "304": "riding arena",
+    "305": "river",
+    "306": "rock arch",
+    "307": "rope bridge",
+    "308": "ruin",
+    "309": "runway",
+    "310": "sandbar",
+    "311": "sandbox",
+    "312": "sauna",
+    "313": "schoolhouse",
+    "314": "sea cliff",
+    "315": "server room",
+    "316": "shed",
+    "317": "shoe shop",
+    "318": "shopfront",
+    "319": "shopping mall indoor",
+    "320": "shower",
+    "321": "skatepark",
+    "322": "ski lodge",
+    "323": "ski resort",
+    "324": "ski slope",
+    "325": "sky",
+    "326": "skyscraper",
+    "327": "slum",
+    "328": "snowfield",
+    "329": "squash court",
+    "330": "stable",
+    "331": "stadium baseball",
+    "332": "stadium football",
+    "333": "stage indoor",
+    "334": "staircase",
+    "335": "street",
+    "336": "subway interior",
+    "337": "subway station platform",
+    "338": "supermarket",
+    "339": "sushi bar",
+    "340": "swamp",
+    "341": "swimming pool indoor",
+    "342": "swimming pool outdoor",
+    "343": "synagogue indoor",
+    "344": "synagogue outdoor",
+    "345": "television studio",
+    "346": "temple east asia",
+    "347": "temple south asia",
+    "348": "tennis court indoor",
+    "349": "tennis court outdoor",
+    "350": "tent outdoor",
+    "351": "theater indoor procenium",
+    "352": "theater indoor seats",
+    "353": "thriftshop",
+    "354": "throne room",
+    "355": "ticket booth",
+    "356": "toll plaza",
+    "357": "topiary garden",
+    "358": "tower",
+    "359": "toyshop",
+    "360": "track outdoor",
+    "361": "train railway",
+    "362": "train station platform",
+    "363": "tree farm",
+    "364": "tree house",
+    "365": "trench",
+    "366": "underwater coral reef",
+    "367": "utility room",
+    "368": "valley",
+    "369": "van interior",
+    "370": "vegetable garden",
+    "371": "veranda",
+    "372": "veterinarians office",
+    "373": "viaduct",
+    "374": "videostore",
+    "375": "village",
+    "376": "vineyard",
+    "377": "volcano",
+    "378": "volleyball court indoor",
+    "379": "volleyball court outdoor",
+    "380": "waiting room",
+    "381": "warehouse indoor",
+    "382": "water tower",
+    "383": "waterfall block",
+    "384": "waterfall fan",
+    "385": "waterfall plunge",
+    "386": "watering hole",
+    "387": "wave",
+    "388": "wet bar",
+    "389": "wheat field",
+    "390": "wind farm",
+    "391": "windmill",
+    "392": "wine cellar barrel storage",
+    "393": "wine cellar bottle storage",
+    "394": "wrestling ring indoor",
+    "395": "yard",
+    "396": "youth hostel"
+  },
+  "label2id": {
+    "abbey": 0,
+    "airplane cabin": 1,
+    "airport terminal": 2,
+    "alley": 3,
+    "amphitheater": 4,
+    "amusement arcade": 5,
+    "amusement park": 6,
+    "anechoic chamber": 7,
+    "apartment building outdoor": 8,
+    "apse indoor": 9,
+    "aquarium": 10,
+    "aqueduct": 11,
+    "arch": 12,
+    "archive": 13,
+    "arrival gate outdoor": 14,
+    "art gallery": 15,
+    "art school": 16,
+    "art studio": 17,
+    "assembly line": 18,
+    "athletic field outdoor": 19,
+    "atrium public": 20,
+    "attic": 21,
+    "auditorium": 22,
+    "auto factory": 23,
+    "badlands": 24,
+    "badminton court indoor": 25,
+    "baggage claim": 26,
+    "bakery shop": 27,
+    "balcony exterior": 28,
+    "balcony interior": 29,
+    "ball pit": 30,
+    "ballroom": 31,
+    "bamboo forest": 32,
+    "banquet hall": 33,
+    "bar": 34,
+    "barn": 35,
+    "barndoor": 36,
+    "baseball field": 37,
+    "basement": 38,
+    "basilica": 39,
+    "basketball court outdoor": 40,
+    "bathroom": 41,
+    "batters box": 42,
+    "bayou": 43,
+    "bazaar indoor": 44,
+    "bazaar outdoor": 45,
+    "beach": 46,
+    "beauty salon": 47,
+    "bedroom": 48,
+    "berth": 49,
+    "biology laboratory": 50,
+    "bistro indoor": 51,
+    "boardwalk": 52,
+    "boat deck": 53,
+    "boathouse": 54,
+    "bookstore": 55,
+    "booth indoor": 56,
+    "botanical garden": 57,
+    "bow window indoor": 58,
+    "bow window outdoor": 59,
+    "bowling alley": 60,
+    "boxing ring": 61,
+    "brewery indoor": 62,
+    "bridge": 63,
+    "building facade": 64,
+    "bullring": 65,
+    "burial chamber": 66,
+    "bus interior": 67,
+    "butchers shop": 68,
+    "butte": 69,
+    "cabin outdoor": 70,
+    "cafeteria": 71,
+    "campsite": 72,
+    "campus": 73,
+    "canal natural": 74,
+    "canal urban": 75,
+    "candy store": 76,
+    "canyon": 77,
+    "car interior backseat": 78,
+    "car interior frontseat": 79,
+    "carrousel": 80,
+    "casino indoor": 81,
+    "castle": 82,
+    "catacomb": 83,
+    "cathedral indoor": 84,
+    "cathedral outdoor": 85,
+    "cavern indoor": 86,
+    "cemetery": 87,
+    "chalet": 88,
+    "cheese factory": 89,
+    "chemistry lab": 90,
+    "chicken coop indoor": 91,
+    "chicken coop outdoor": 92,
+    "childs room": 93,
+    "church indoor": 94,
+    "church outdoor": 95,
+    "classroom": 96,
+    "clean room": 97,
+    "cliff": 98,
+    "cloister indoor": 99,
+    "closet": 100,
+    "clothing store": 101,
+    "coast": 102,
+    "cockpit": 103,
+    "coffee shop": 104,
+    "computer room": 105,
+    "conference center": 106,
+    "conference room": 107,
+    "construction site": 108,
+    "control room": 109,
+    "control tower outdoor": 110,
+    "corn field": 111,
+    "corral": 112,
+    "corridor": 113,
+    "cottage garden": 114,
+    "courthouse": 115,
+    "courtroom": 116,
+    "courtyard": 117,
+    "covered bridge exterior": 118,
+    "creek": 119,
+    "crevasse": 120,
+    "crosswalk": 121,
+    "cubicle office": 122,
+    "dam": 123,
+    "delicatessen": 124,
+    "dentists office": 125,
+    "desert sand": 126,
+    "desert vegetation": 127,
+    "diner indoor": 128,
+    "diner outdoor": 129,
+    "dinette home": 130,
+    "dinette vehicle": 131,
+    "dining car": 132,
+    "dining room": 133,
+    "discotheque": 134,
+    "dock": 135,
+    "doorway outdoor": 136,
+    "dorm room": 137,
+    "driveway": 138,
+    "driving range outdoor": 139,
+    "drugstore": 140,
+    "electrical substation": 141,
+    "elevator door": 142,
+    "elevator interior": 143,
+    "elevator shaft": 144,
+    "engine room": 145,
+    "escalator indoor": 146,
+    "excavation": 147,
+    "factory indoor": 148,
+    "fairway": 149,
+    "fastfood restaurant": 150,
+    "field cultivated": 151,
+    "field wild": 152,
+    "fire escape": 153,
+    "fire station": 154,
+    "firing range indoor": 155,
+    "fishpond": 156,
+    "florist shop indoor": 157,
+    "food court": 158,
+    "forest broadleaf": 159,
+    "forest needleleaf": 160,
+    "forest path": 161,
+    "forest road": 162,
+    "formal garden": 163,
+    "fountain": 164,
+    "galley": 165,
+    "game room": 166,
+    "garage indoor": 167,
+    "garbage dump": 168,
+    "gas station": 169,
+    "gazebo exterior": 170,
+    "general store indoor": 171,
+    "general store outdoor": 172,
+    "gift shop": 173,
+    "golf course": 174,
+    "greenhouse indoor": 175,
+    "greenhouse outdoor": 176,
+    "gymnasium indoor": 177,
+    "hangar indoor": 178,
+    "hangar outdoor": 179,
+    "harbor": 180,
+    "hayfield": 181,
+    "heliport": 182,
+    "herb garden": 183,
+    "highway": 184,
+    "hill": 185,
+    "home office": 186,
+    "hospital": 187,
+    "hospital room": 188,
+    "hot spring": 189,
+    "hot tub outdoor": 190,
+    "hotel outdoor": 191,
+    "hotel room": 192,
+    "house": 193,
+    "hunting lodge outdoor": 194,
+    "ice cream parlor": 195,
+    "ice floe": 196,
+    "ice shelf": 197,
+    "ice skating rink indoor": 198,
+    "ice skating rink outdoor": 199,
+    "iceberg": 200,
+    "igloo": 201,
+    "industrial area": 202,
+    "inn outdoor": 203,
+    "islet": 204,
+    "jacuzzi indoor": 205,
+    "jail cell": 206,
+    "jail indoor": 207,
+    "jewelry shop": 208,
+    "kasbah": 209,
+    "kennel indoor": 210,
+    "kennel outdoor": 211,
+    "kindergarden classroom": 212,
+    "kitchen": 213,
+    "kitchenette": 214,
+    "labyrinth outdoor": 215,
+    "lake natural": 216,
+    "landfill": 217,
+    "landing deck": 218,
+    "laundromat": 219,
+    "lecture room": 220,
+    "library indoor": 221,
+    "library outdoor": 222,
+    "lido deck outdoor": 223,
+    "lift bridge": 224,
+    "lighthouse": 225,
+    "limousine interior": 226,
+    "living room": 227,
+    "lobby": 228,
+    "lock chamber": 229,
+    "locker room": 230,
+    "mansion": 231,
+    "manufactured home": 232,
+    "market indoor": 233,
+    "market outdoor": 234,
+    "marsh": 235,
+    "martial arts gym": 236,
+    "mausoleum": 237,
+    "medina": 238,
+    "moat water": 239,
+    "monastery outdoor": 240,
+    "mosque indoor": 241,
+    "mosque outdoor": 242,
+    "motel": 243,
+    "mountain": 244,
+    "mountain snowy": 245,
+    "movie theater indoor": 246,
+    "museum indoor": 247,
+    "music store": 248,
+    "music studio": 249,
+    "nuclear power plant outdoor": 250,
+    "nursery": 251,
+    "oast house": 252,
+    "observatory outdoor": 253,
+    "ocean": 254,
+    "office": 255,
+    "office building": 256,
+    "oil refinery outdoor": 257,
+    "oilrig": 258,
+    "operating room": 259,
+    "orchard": 260,
+    "outhouse outdoor": 261,
+    "pagoda": 262,
+    "palace": 263,
+    "pantry": 264,
+    "park": 265,
+    "parking garage indoor": 266,
+    "parking garage outdoor": 267,
+    "parking lot": 268,
+    "parlor": 269,
+    "pasture": 270,
+    "patio": 271,
+    "pavilion": 272,
+    "pharmacy": 273,
+    "phone booth": 274,
+    "physics laboratory": 275,
+    "picnic area": 276,
+    "pilothouse indoor": 277,
+    "planetarium outdoor": 278,
+    "playground": 279,
+    "playroom": 280,
+    "plaza": 281,
+    "podium indoor": 282,
+    "podium outdoor": 283,
+    "pond": 284,
+    "poolroom establishment": 285,
+    "poolroom home": 286,
+    "power plant outdoor": 287,
+    "promenade deck": 288,
+    "pub indoor": 289,
+    "pulpit": 290,
+    "putting green": 291,
+    "racecourse": 292,
+    "raceway": 293,
+    "raft": 294,
+    "railroad track": 295,
+    "rainforest": 296,
+    "reception": 297,
+    "recreation room": 298,
+    "residential neighborhood": 299,
+    "restaurant": 300,
+    "restaurant kitchen": 301,
+    "restaurant patio": 302,
+    "rice paddy": 303,
+    "riding arena": 304,
+    "river": 305,
+    "rock arch": 306,
+    "rope bridge": 307,
+    "ruin": 308,
+    "runway": 309,
+    "sandbar": 310,
+    "sandbox": 311,
+    "sauna": 312,
+    "schoolhouse": 313,
+    "sea cliff": 314,
+    "server room": 315,
+    "shed": 316,
+    "shoe shop": 317,
+    "shopfront": 318,
+    "shopping mall indoor": 319,
+    "shower": 320,
+    "skatepark": 321,
+    "ski lodge": 322,
+    "ski resort": 323,
+    "ski slope": 324,
+    "sky": 325,
+    "skyscraper": 326,
+    "slum": 327,
+    "snowfield": 328,
+    "squash court": 329,
+    "stable": 330,
+    "stadium baseball": 331,
+    "stadium football": 332,
+    "stage indoor": 333,
+    "staircase": 334,
+    "street": 335,
+    "subway interior": 336,
+    "subway station platform": 337,
+    "supermarket": 338,
+    "sushi bar": 339,
+    "swamp": 340,
+    "swimming pool indoor": 341,
+    "swimming pool outdoor": 342,
+    "synagogue indoor": 343,
+    "synagogue outdoor": 344,
+    "television studio": 345,
+    "temple east asia": 346,
+    "temple south asia": 347,
+    "tennis court indoor": 348,
+    "tennis court outdoor": 349,
+    "tent outdoor": 350,
+    "theater indoor procenium": 351,
+    "theater indoor seats": 352,
+    "thriftshop": 353,
+    "throne room": 354,
+    "ticket booth": 355,
+    "toll plaza": 356,
+    "topiary garden": 357,
+    "tower": 358,
+    "toyshop": 359,
+    "track outdoor": 360,
+    "train railway": 361,
+    "train station platform": 362,
+    "tree farm": 363,
+    "tree house": 364,
+    "trench": 365,
+    "underwater coral reef": 366,
+    "utility room": 367,
+    "valley": 368,
+    "van interior": 369,
+    "vegetable garden": 370,
+    "veranda": 371,
+    "veterinarians office": 372,
+    "viaduct": 373,
+    "videostore": 374,
+    "village": 375,
+    "vineyard": 376,
+    "volcano": 377,
+    "volleyball court indoor": 378,
+    "volleyball court outdoor": 379,
+    "waiting room": 380,
+    "warehouse indoor": 381,
+    "water tower": 382,
+    "waterfall block": 383,
+    "waterfall fan": 384,
+    "waterfall plunge": 385,
+    "watering hole": 386,
+    "wave": 387,
+    "wet bar": 388,
+    "wheat field": 389,
+    "wind farm": 390,
+    "windmill": 391,
+    "wine cellar barrel storage": 392,
+    "wine cellar bottle storage": 393,
+    "wrestling ring indoor": 394,
+    "yard": 395,
+    "youth hostel": 396
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-sun397-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet50-sun397-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-sun397-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-svhn-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/README.md b/resnet50-svhn-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..71cee6f5ade1a8a95203958eb5ff31b734780efd
--- /dev/null
+++ b/resnet50-svhn-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/README.md
@@ -0,0 +1,80 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset svhn.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: svhn
+    pretrained: true
+test_datasets: null
+train_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: train
+type: transformers
+val_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: test
+```
+
diff --git a/resnet50-svhn-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/config.json b/resnet50-svhn-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1edcdd247f31547feb0c0bebd29bf1cd24a4532f
--- /dev/null
+++ b/resnet50-svhn-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-svhn-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet50-svhn-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-svhn-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-svhn-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/README.md b/resnet50-svhn-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..8fe4ff2f4d7dc59cf12dc7485b850f9048d15fd0
--- /dev/null
+++ b/resnet50-svhn-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/README.md
@@ -0,0 +1,80 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset svhn.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 128
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: true
+save_top_k: -1
+training_data_ratio: 0.8
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: svhn
+    pretrained: true
+test_datasets: null
+train_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: train
+type: transformers
+val_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: test
+```
+
diff --git a/resnet50-svhn-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/config.json b/resnet50-svhn-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1edcdd247f31547feb0c0bebd29bf1cd24a4532f
--- /dev/null
+++ b/resnet50-svhn-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-svhn-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet50-svhn-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-svhn-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-svhn-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/README.md b/resnet50-svhn-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..552983ce85be0ff5e10ef87b50ccd48ab24cd243
--- /dev/null
+++ b/resnet50-svhn-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/README.md
@@ -0,0 +1,80 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset svhn.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 0.5
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: svhn
+    pretrained: true
+test_datasets: null
+train_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: train
+type: transformers
+val_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: test
+```
+
diff --git a/resnet50-svhn-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/config.json b/resnet50-svhn-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1edcdd247f31547feb0c0bebd29bf1cd24a4532f
--- /dev/null
+++ b/resnet50-svhn-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-svhn-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet50-svhn-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-svhn-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-svhn-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/README.md b/resnet50-svhn-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e6c3ddeccfa5f1e759b207917d745c8a6fde9a69
--- /dev/null
+++ b/resnet50-svhn-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,80 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset svhn.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: svhn
+    pretrained: true
+test_datasets: null
+train_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: train
+type: transformers
+val_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: test
+```
+
diff --git a/resnet50-svhn-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/config.json b/resnet50-svhn-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1edcdd247f31547feb0c0bebd29bf1cd24a4532f
--- /dev/null
+++ b/resnet50-svhn-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-svhn-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet50-svhn-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-svhn-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-svhn-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/README.md b/resnet50-svhn-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..2a9242dfc3acc91218aaac657bea1bab316539b7
--- /dev/null
+++ b/resnet50-svhn-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/README.md
@@ -0,0 +1,80 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset svhn.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 256
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.005
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: svhn
+    pretrained: true
+test_datasets: null
+train_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: train
+type: transformers
+val_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: test
+```
+
diff --git a/resnet50-svhn-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/config.json b/resnet50-svhn-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1edcdd247f31547feb0c0bebd29bf1cd24a4532f
--- /dev/null
+++ b/resnet50-svhn-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-svhn-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet50-svhn-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-svhn-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}
diff --git a/resnet50-svhn-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/README.md b/resnet50-svhn-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..7513804cb5ee335f36d451a136bcf565b8fa3bda
--- /dev/null
+++ b/resnet50-svhn-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/README.md
@@ -0,0 +1,80 @@
+---
+base_model: microsoft/resnet-50
+library_name: transformers
+tags:
+- fusion-bench
+- merge
+---
+# Deep Model Fusion
+
+Fine-tuned ResNet model on dataset svhn.
+
+## Models Merged
+
+This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
+
+The following models were included in the merge:
+
+
+
+
+## Configuration
+
+The following YAML configuration was used to produce this model:
+
+### Algorithm Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
+_usage_: null
+_version_: 0.2.25.dev0
+dataloader_kwargs:
+  batch_size: 64
+  num_workers: 8
+  pin_memory: true
+label_smoothing: 0
+lr_scheduler: null
+max_epochs: -1
+max_steps: 4000
+optimizer:
+  _target_: torch.optim.SGD
+  lr: 0.001
+  momentum: 0.9
+  weight_decay: 0.0001
+save_interval: 1000
+save_on_train_epoch_end: false
+save_top_k: -1
+training_data_ratio: 1.0
+```
+
+### Model Pool Configuration
+
+```yaml
+_recursive_: false
+_target_: fusion_bench.modelpool.resnet_for_image_classification.ResNetForImageClassificationPool
+_usage_: null
+_version_: 0.2.25.dev0
+models:
+  _pretrained_:
+    config_path: microsoft/resnet-50
+    dataset_name: svhn
+    pretrained: true
+test_datasets: null
+train_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: train
+type: transformers
+val_datasets:
+  svhn:
+    _args_:
+    - svhn
+    - cropped_digits
+    _target_: datasets.load_dataset
+    split: test
+```
+
diff --git a/resnet50-svhn-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/config.json b/resnet50-svhn-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..1edcdd247f31547feb0c0bebd29bf1cd24a4532f
--- /dev/null
+++ b/resnet50-svhn-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/config.json
@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "dtype": "float32",
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 7,
+    "8": 8,
+    "9": 9
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "4.56.1"
+}
diff --git a/resnet50-svhn-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet50-svhn-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d
--- /dev/null
+++ b/resnet50-svhn-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json
@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}