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resnet152-cifar10-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/model.safetensors

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resnet152-cifar10-batch_size_256_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
+```
+

resnet152-cifar10-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/config.json

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+{
+  "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"
+}

resnet152-cifar10-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json

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+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}

resnet152-cifar10-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/model.safetensors

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resnet152-cifar10-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/model.safetensors

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resnet152-cifar10-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 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: 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
+```
+

resnet152-cifar10-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/config.json

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+{
+  "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"
+}

resnet152-cifar10-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
+  }
+}

resnet152-cifar10-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 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
+```
+

resnet152-cifar10-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/config.json

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+{
+  "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"
+}

resnet152-cifar10-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json

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+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}

resnet152-cifar10-batch_size_64_lr_0.01_training_data_ratio_0.8-3000/model.safetensors

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resnet152-cifar100-batch_size_128_lr_0.01_training_data_ratio_0.5-1000/model.safetensors

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resnet152-cifar100-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/model.safetensors

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resnet152-cifar100-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/model.safetensors

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resnet152-cifar100-batch_size_256_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 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: 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: 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
+```
+

resnet152-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/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"
+}

resnet152-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
+  }
+}

resnet152-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/model.safetensors

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+size 234125152

resnet152-cifar100-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 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: 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: 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
+```
+

resnet152-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/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"
+}

resnet152-cifar100-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
+  }
+}

resnet152-cifar100-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 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: 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
+```
+

resnet152-cifar100-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/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"
+}

resnet152-cifar100-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json

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+{
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+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
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+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}

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resnet152-cifar100-batch_size_64_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 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: 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
+```
+

resnet152-cifar100-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/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"
+}

resnet152-cifar100-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json

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+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}

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resnet152-dtd-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/model.safetensors

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resnet152-dtd-batch_size_256_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: 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
+```
+

resnet152-dtd-batch_size_256_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"
+}

resnet152-dtd-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/preprocessor_config.json

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+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}

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resnet152-dtd-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/model.safetensors

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resnet152-dtd-batch_size_64_lr_0.01_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: 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: 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
+```
+

resnet152-dtd-batch_size_64_lr_0.01_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"
+}

resnet152-dtd-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
+  }
+}

resnet152-dtd-batch_size_64_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 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: 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: 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
+```
+

resnet152-dtd-batch_size_64_lr_0.01_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"
+}

resnet152-dtd-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
+  }
+}

resnet152-emnist_letters-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:905c4dd7b87cc169ff9f26cd13e8e3726983892962ca9a1028a2f036b9ae7800
+size 233518560

resnet152-emnist_letters-batch_size_128_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 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: 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
+```
+

resnet152-emnist_letters-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/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"
+}