diff --git a/resnet152-cifar10-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/model.safetensors b/resnet152-cifar10-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..d48f7ef7ff96ca5b33134e785e7a489111230bd1 --- /dev/null +++ b/resnet152-cifar10-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f35a1570bffc474f337e313720d683f2ebcf056bce90092b4cd5b29a8991414c +size 233387400 diff --git a/resnet152-cifar10-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/README.md b/resnet152-cifar10-batch_size_256_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_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 +``` + diff --git a/resnet152-cifar10-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/config.json b/resnet152-cifar10-batch_size_256_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_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": "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_256_lr_0.001_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet152-cifar10-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-cifar10-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-cifar10-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/model.safetensors b/resnet152-cifar10-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..faad4229cad93f6e7050b20123f7f56a71581f6f --- /dev/null +++ b/resnet152-cifar10-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:adb318a35e3b325f2f76d1212be89aefd23175f9286f4664209b6dba9408e33e +size 233387400 diff --git a/resnet152-cifar10-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/model.safetensors b/resnet152-cifar10-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..6b9cc67d145f09dc70b4472ebfdb3806980e519d --- /dev/null +++ b/resnet152-cifar10-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b1ed2e154399932fe39ab7ef4efbc61f214b0b101f1b2809ccea1ba02e5a4602 +size 233387400 diff --git a/resnet152-cifar10-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/README.md b/resnet152-cifar10-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..ca6ed2f4a1229d21291d93f1934e7160c23f89f2 --- /dev/null +++ b/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 +``` + diff --git a/resnet152-cifar10-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/config.json b/resnet152-cifar10-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..fae9a9cc3053b5936d45ecae91b1a2edabf051ba --- /dev/null +++ b/resnet152-cifar10-batch_size_256_lr_0.01_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": "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_256_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet152-cifar10-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-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 + } +} diff --git a/resnet152-cifar10-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/README.md b/resnet152-cifar10-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..72bfaf0c9130293671dad3e4879026607b340bb2 --- /dev/null +++ b/resnet152-cifar10-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/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 +``` + diff --git a/resnet152-cifar10-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/config.json b/resnet152-cifar10-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..fae9a9cc3053b5936d45ecae91b1a2edabf051ba --- /dev/null +++ b/resnet152-cifar10-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/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_0.001_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet152-cifar10-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-cifar10-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 + } +} 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--- /dev/null +++ b/resnet152-cifar100-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6e71d30b530ef6249015b8ea50458313828a9c4476ba402f60eb5343114b0979 +size 234125152 diff --git a/resnet152-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/README.md b/resnet152-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..ca1f6fd793cdacdce2a07c1ad61b6d41039d1911 --- /dev/null +++ b/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 +``` + diff --git a/resnet152-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/config.json b/resnet152-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..acbad7473b8e84235773c84b96dc29cdb56af499 --- /dev/null +++ b/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" +} diff --git a/resnet152-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet152-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/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 + } +} diff --git a/resnet152-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/model.safetensors b/resnet152-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..72e89a90f3357d61f6c245b50df3c7dab8452ef1 --- /dev/null +++ b/resnet152-cifar100-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5a3f5f880f0621374a0052c1704175c34e33562dd9bf4d9ca220c5d50000a4fa +size 234125152 diff --git a/resnet152-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/README.md b/resnet152-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..7b77afbfd8ecd32f5a55ecb1d9ccd8b10b008a51 --- /dev/null +++ b/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 +``` + diff --git a/resnet152-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/config.json b/resnet152-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..acbad7473b8e84235773c84b96dc29cdb56af499 --- /dev/null +++ b/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" +} diff --git a/resnet152-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet152-cifar100-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-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 + } +} diff --git a/resnet152-cifar100-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/README.md b/resnet152-cifar100-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..d36a31c9d49067d719654c2e53df892e5937ecfd --- /dev/null +++ b/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 +``` + diff --git a/resnet152-cifar100-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/config.json b/resnet152-cifar100-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..acbad7473b8e84235773c84b96dc29cdb56af499 --- /dev/null +++ b/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, + 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0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d --- /dev/null +++ b/resnet152-cifar100-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-cifar100-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/model.safetensors b/resnet152-cifar100-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..23410cb4923736ae5d83edf7a61f257328ff91cc --- /dev/null +++ b/resnet152-cifar100-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/model.safetensors @@ -0,0 +1,3 @@ +version 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b/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 +``` + diff --git a/resnet152-cifar100-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/config.json b/resnet152-cifar100-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..acbad7473b8e84235773c84b96dc29cdb56af499 --- /dev/null +++ b/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, + 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], + "out_indices": [ + 4 + ], + "stage_names": [ + "stem", + "stage1", + "stage2", + "stage3", + "stage4" + ], + "transformers_version": "4.56.1" +} diff --git a/resnet152-cifar100-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet152-cifar100-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/resnet152-cifar100-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 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0000000000000000000000000000000000000000..ab836500fae41907cdfebdd0d04470b6a783c43e --- /dev/null +++ b/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 +``` + diff --git a/resnet152-dtd-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/config.json b/resnet152-dtd-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..6cee8e06ce13fa5525fb8517c300e637bc05dba7 --- 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0000000000000000000000000000000000000000..0ee5ee64e2a405d62c2e4d719465425119be698d --- /dev/null +++ b/resnet152-dtd-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:152682eaa37ad1660e80e12e8aecfe387c57198cebad30cae5a8b3a1a18d9394 +size 233690692 diff --git a/resnet152-dtd-batch_size_64_lr_0.01_training_data_ratio_0.5-1000/README.md b/resnet152-dtd-batch_size_64_lr_0.01_training_data_ratio_0.5-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..d5e595d40df5bd6dd145ccb3d4e7c1c2a4109333 --- /dev/null +++ b/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 +``` + diff --git a/resnet152-dtd-batch_size_64_lr_0.01_training_data_ratio_0.5-1000/config.json b/resnet152-dtd-batch_size_64_lr_0.01_training_data_ratio_0.5-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..6cee8e06ce13fa5525fb8517c300e637bc05dba7 --- /dev/null +++ b/resnet152-dtd-batch_size_64_lr_0.01_training_data_ratio_0.5-1000/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_64_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet152-dtd-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/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 + } +} diff --git a/resnet152-dtd-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/README.md b/resnet152-dtd-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..d1c4c91ae60b4ba1e26340ad5de621e49a087b0a --- /dev/null +++ b/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 +``` + diff --git a/resnet152-dtd-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/config.json b/resnet152-dtd-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..6cee8e06ce13fa5525fb8517c300e637bc05dba7 --- /dev/null +++ b/resnet152-dtd-batch_size_64_lr_0.01_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" +} diff --git a/resnet152-dtd-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet152-dtd-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-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 + } +} diff --git a/resnet152-emnist_letters-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/model.safetensors b/resnet152-emnist_letters-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..160c1bb4f9dc4952421ca6570994b86294b3a2e3 --- /dev/null +++ b/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 diff --git a/resnet152-emnist_letters-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/README.md b/resnet152-emnist_letters-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..e17abb653ed828213156a2e5a92064b7a03c230a --- /dev/null +++ b/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 +``` + diff --git a/resnet152-emnist_letters-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/config.json b/resnet152-emnist_letters-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..1de185c4a239f93470f739721235a30bac76536e --- /dev/null +++ b/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" +} diff --git a/resnet152-emnist_letters-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet152-emnist_letters-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/resnet152-emnist_letters-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/resnet152-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/model.safetensors b/resnet152-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..1d833b73d71d375e0865500170063b2e962775f0 --- /dev/null +++ b/resnet152-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8542f86cc82ff0c55d5168f69e2e930775a3ce68508b79b44f860931a2a6ae55 +size 233518560 diff --git a/resnet152-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/README.md b/resnet152-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..23f9da3793e10a9a7f04843d819f52d8e4cf991a --- /dev/null +++ b/resnet152-emnist_letters-batch_size_128_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 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: 0.8 +``` + +### 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: 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_0.8-1000/config.json b/resnet152-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..1de185c4a239f93470f739721235a30bac76536e --- /dev/null +++ b/resnet152-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/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_128_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet152-emnist_letters-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-emnist_letters-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-emnist_letters-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/README.md b/resnet152-emnist_letters-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..aac0ffadb1caa859a408899a50fc5b769ff82da0 --- /dev/null +++ b/resnet152-emnist_letters-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/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: 0.001 + 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_0.5-3000/config.json b/resnet152-emnist_letters-batch_size_256_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_256_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_256_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet152-emnist_letters-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-emnist_letters-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-emnist_letters-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/README.md b/resnet152-emnist_letters-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..02313618783563afaaec96f9d06cd255f69a45b6 --- /dev/null +++ b/resnet152-emnist_letters-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 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: 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_0.005_training_data_ratio_0.5-1000/config.json b/resnet152-emnist_letters-batch_size_256_lr_0.005_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_0.005_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_0.005_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet152-emnist_letters-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-emnist_letters-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-emnist_letters-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/model.safetensors b/resnet152-emnist_letters-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..09709ec39266cba2709ee25ab391465de8df9fa9 --- /dev/null +++ b/resnet152-emnist_letters-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:523f8a8dc4e70c0dd0de4c8de7f100a41bffeea405aeaf12769682d593e65fb8 +size 233518560 diff --git a/resnet152-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/README.md b/resnet152-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..6d7c6c6580386f4065b0ddd101b334236acbf370 --- /dev/null +++ b/resnet152-emnist_letters-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 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-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_1.0-3000/config.json b/resnet152-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..1de185c4a239f93470f739721235a30bac76536e --- /dev/null +++ b/resnet152-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_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_64_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json 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0000000000000000000000000000000000000000..e6ec1931f0e33ee759cfa090e075b584208d7f9c --- /dev/null +++ b/resnet152-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e0f1a095cce08ae00b489b614fb03c82fbe73b0c1dd31562e573efc7a553e9f9 +size 233518560 diff --git a/resnet152-eurosat-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/model.safetensors b/resnet152-eurosat-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..4f4e31aa254412a2ea097ad5c5e8048ead26fc2e --- /dev/null +++ b/resnet152-eurosat-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:61ae290608b0466c93d5a1a54eda9d65f5e7a17b8bc1e14071f419affcc2f23b +size 233387400 diff --git a/resnet152-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/README.md b/resnet152-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..07809faa476d6f3477a65626153fa0529173ba30 --- /dev/null +++ b/resnet152-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/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: 0.5 +``` + +### 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_0.5-3000/config.json b/resnet152-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..3fbee75f8255e01f77ec81c2c941301ad8f54ddc --- /dev/null +++ b/resnet152-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/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_128_lr_0.005_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet152-eurosat-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/resnet152-eurosat-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/resnet152-eurosat-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/model.safetensors b/resnet152-eurosat-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..a0522751104dd55bada59bc83352fbb53b1a05df --- /dev/null +++ b/resnet152-eurosat-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:1e5a0ee23c9b68ff47cba107a85588a16f2dde7e8c6b7b7e4f9bdd40a1374100 +size 233387400 diff --git a/resnet152-eurosat-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/README.md b/resnet152-eurosat-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..569a114177a73d6e4ccaaf831e2b40ff50aded04 --- /dev/null +++ b/resnet152-eurosat-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 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: 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: 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_0.01_training_data_ratio_0.5-4000/config.json b/resnet152-eurosat-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..3fbee75f8255e01f77ec81c2c941301ad8f54ddc --- /dev/null +++ b/resnet152-eurosat-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": "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_0.01_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet152-eurosat-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-eurosat-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-eurosat-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/model.safetensors b/resnet152-eurosat-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..67234a030ccb1aa8c235e65841d88e6808c77acd --- /dev/null +++ b/resnet152-eurosat-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:08636100208b3581a74865e505b3cf225bceaecca10745f20a73c5ca4129bf7b +size 233387400 diff --git a/resnet152-eurosat-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/README.md b/resnet152-eurosat-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..cd32e6580ed6913724aeb8f31abdd12698cfb680 --- /dev/null +++ b/resnet152-eurosat-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/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: 0.001 + 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_0.8-3000/config.json b/resnet152-eurosat-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..3fbee75f8255e01f77ec81c2c941301ad8f54ddc --- /dev/null +++ b/resnet152-eurosat-batch_size_256_lr_0.001_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": "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_0.8-3000/preprocessor_config.json b/resnet152-eurosat-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-eurosat-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-eurosat-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/README.md b/resnet152-eurosat-batch_size_256_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_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 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_256_lr_0.005_training_data_ratio_0.5-2000/config.json b/resnet152-eurosat-batch_size_256_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_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": "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_0.5-2000/preprocessor_config.json b/resnet152-eurosat-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-eurosat-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-eurosat-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/model.safetensors b/resnet152-eurosat-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..d97a3a8713f8e4f2eb2d0c14161f7734c0427246 --- /dev/null +++ b/resnet152-eurosat-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:156f272c8b3f70c1f50cd1c10c81221efd9e7f4894cea5567c9337d264134d89 +size 233387400 diff --git a/resnet152-eurosat-batch_size_64_lr_0.01_training_data_ratio_0.5-1000/model.safetensors b/resnet152-eurosat-batch_size_64_lr_0.01_training_data_ratio_0.5-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..ae5080a2f44dacf52ce8d32ef4787591a5df4a40 --- /dev/null +++ b/resnet152-eurosat-batch_size_64_lr_0.01_training_data_ratio_0.5-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:1881eead634ec803732dbec3575531b65806a287d2387bb18e00210d37deb2f5 +size 233387400 diff --git a/resnet152-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md b/resnet152-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..28e809522ae13f7ffb4e29d142c1bc527780a400 --- /dev/null +++ b/resnet152-fashion_mnist-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 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-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_0.005_training_data_ratio_0.8-3000/config.json b/resnet152-fashion_mnist-batch_size_128_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_128_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_128_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet152-fashion_mnist-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-fashion_mnist-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-fashion_mnist-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/README.md b/resnet152-fashion_mnist-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..658f60ec0cd49f24d7d4c2d0f7b52a8010166efb --- /dev/null +++ b/resnet152-fashion_mnist-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 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: 0.5 +``` + +### 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: 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_0.01_training_data_ratio_0.5-3000/config.json b/resnet152-fashion_mnist-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..99626e1d853a8525a84a8d4ca7c121c77c398eed --- /dev/null +++ b/resnet152-fashion_mnist-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": "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_0.01_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet152-fashion_mnist-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-fashion_mnist-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-fashion_mnist-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/README.md b/resnet152-fashion_mnist-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..9061a712d50d4cdb64fe974649fc0bf547b8916b --- /dev/null +++ b/resnet152-fashion_mnist-batch_size_128_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 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_128_lr_0.01_training_data_ratio_0.8-3000/config.json b/resnet152-fashion_mnist-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..99626e1d853a8525a84a8d4ca7c121c77c398eed --- /dev/null +++ b/resnet152-fashion_mnist-batch_size_128_lr_0.01_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 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a/resnet152-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/README.md b/resnet152-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..7596fe6c48bbbee9e41c1831b0c593c744f4f709 --- /dev/null +++ b/resnet152-fashion_mnist-batch_size_256_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 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: 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_0.001_training_data_ratio_0.8-4000/config.json b/resnet152-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..99626e1d853a8525a84a8d4ca7c121c77c398eed --- /dev/null +++ b/resnet152-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/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_0.001_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet152-fashion_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/resnet152-fashion_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/resnet152-fashion_mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/model.safetensors b/resnet152-fashion_mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..e349bf1929fda67e0bed323f66f83154ec1b57c3 --- /dev/null +++ b/resnet152-fashion_mnist-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:595a4224833c531c1a559c85ddb40d18b3971e033bc0101758fef72da5838766 +size 233387400 diff --git a/resnet152-fashion_mnist-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/model.safetensors b/resnet152-fashion_mnist-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..247fc51ec528259ec5741b9a23605839ea59e13d --- /dev/null +++ b/resnet152-fashion_mnist-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8ce7429f1324ab13435b8581ffd91d2cc46d3c788910d48c6b2e100c611ab767 +size 233387400 diff --git a/resnet152-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/README.md b/resnet152-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..f1e66447ce310afe593146f1c7b6fa05294e6f28 --- /dev/null +++ b/resnet152-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/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: 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_0.8-4000/config.json b/resnet152-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..99626e1d853a8525a84a8d4ca7c121c77c398eed --- /dev/null +++ b/resnet152-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/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_64_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet152-fashion_mnist-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-fashion_mnist-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-fashion_mnist-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/model.safetensors b/resnet152-fashion_mnist-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..aac4164e9c1030e62f4e3c75dc0d96250eae445a --- /dev/null +++ b/resnet152-fashion_mnist-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0e009cdb6fbe272b724fffc24420feda194443e18db1fb6d04f7a1ef78a99dfa +size 233387400 diff --git a/resnet152-fashion_mnist-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/README.md b/resnet152-fashion_mnist-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..775ffd0655c4fff153728780ccf95c4eff4690b3 --- /dev/null +++ b/resnet152-fashion_mnist-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 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: 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_0.01_training_data_ratio_1.0-3000/config.json b/resnet152-fashion_mnist-batch_size_64_lr_0.01_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_0.01_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_0.01_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet152-fashion_mnist-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-fashion_mnist-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-fer2013-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/model.safetensors b/resnet152-fer2013-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..9d41379afd56ec69a45fbb33455f7b38fff2f1c7 --- /dev/null +++ b/resnet152-fer2013-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e8ab2d2310ebfb29bdcb9698a47bad4b3614b822d03f5b885df7b7f55ce82f21 +size 233362804 diff --git a/resnet152-fer2013-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/README.md b/resnet152-fer2013-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..8c31e1a06cefd5563fd7661649c307512566fc1e --- /dev/null +++ b/resnet152-fer2013-batch_size_128_lr_0.005_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: 0.005 + 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: 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_0.5-1000/config.json b/resnet152-fer2013-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..874518c652ec15eb6e18b82397e47e4f485a6af7 --- /dev/null +++ b/resnet152-fer2013-batch_size_128_lr_0.005_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_0.005_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet152-fer2013-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-fer2013-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-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/model.safetensors b/resnet152-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..482efdf663591eae1647ef42637efbbbe0907661 --- /dev/null +++ b/resnet152-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c4e3af541461347124ebcc1ba06b0813ea242851ddffb9449f20649291aa4fc2 +size 233362804 diff --git a/resnet152-fer2013-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/README.md b/resnet152-fer2013-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..0531e70dbb175deec0c95d1bc16859b016775905 --- /dev/null +++ b/resnet152-fer2013-batch_size_256_lr_0.001_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: 0.001 + 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: 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_256_lr_0.001_training_data_ratio_0.8-2000/config.json b/resnet152-fer2013-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..874518c652ec15eb6e18b82397e47e4f485a6af7 --- /dev/null +++ b/resnet152-fer2013-batch_size_256_lr_0.001_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_256_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet152-fer2013-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-fer2013-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-fer2013-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/README.md b/resnet152-fer2013-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..c58bd1eff106dce667f2fbff903eac28203ed6a7 --- /dev/null +++ b/resnet152-fer2013-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/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: 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_256_lr_0.005_training_data_ratio_1.0-2000/config.json b/resnet152-fer2013-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..874518c652ec15eb6e18b82397e47e4f485a6af7 --- /dev/null +++ b/resnet152-fer2013-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/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_256_lr_0.005_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet152-fer2013-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/resnet152-fer2013-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/resnet152-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/model.safetensors b/resnet152-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..51be13d4ab7ff135134a6f0eea0bce4a30f17a44 --- /dev/null +++ b/resnet152-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:97fb31e29d2501e250437e1948d59fa05051bea9e2915d2dfd58d2b16e23836c +size 233362804 diff --git a/resnet152-food101-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/README.md b/resnet152-food101-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..e9970144d9215f140e6a55cfa0852d5a1ff30a6e --- /dev/null +++ b/resnet152-food101-batch_size_128_lr_0.005_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 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: 0.5 +``` + +### 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: 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_0.5-3000/config.json b/resnet152-food101-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..002738700083d19b6f2089a9c2d0959b8ee2b0bb --- /dev/null +++ b/resnet152-food101-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/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_0.5-3000/preprocessor_config.json b/resnet152-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/resnet152-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/resnet152-food101-batch_size_128_lr_0.005_training_data_ratio_1.0-4000/README.md b/resnet152-food101-batch_size_128_lr_0.005_training_data_ratio_1.0-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..d48302a436f74a903d847ba02c3a3ef8b2c62632 --- /dev/null +++ b/resnet152-food101-batch_size_128_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 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: 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_128_lr_0.005_training_data_ratio_1.0-4000/config.json b/resnet152-food101-batch_size_128_lr_0.005_training_data_ratio_1.0-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..002738700083d19b6f2089a9c2d0959b8ee2b0bb --- /dev/null +++ b/resnet152-food101-batch_size_128_lr_0.005_training_data_ratio_1.0-4000/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_128_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet152-food101-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/resnet152-food101-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/resnet152-food101-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/README.md b/resnet152-food101-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..fea64bc208b7c9b2b8086b8e62c0181f27cedaa0 --- /dev/null +++ b/resnet152-food101-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 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: 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_256_lr_0.001_training_data_ratio_0.8-3000/config.json b/resnet152-food101-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..002738700083d19b6f2089a9c2d0959b8ee2b0bb --- /dev/null +++ b/resnet152-food101-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/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_0.001_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet152-food101-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-food101-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-food101-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/model.safetensors b/resnet152-food101-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..99f2ab2e093192d6bb0718e1fa6cbc3195aaf013 --- /dev/null +++ b/resnet152-food101-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:71a614aaa4f74fc54b6d25eb3f69186faf924a7fc485ab8bfe6bd2271226d150 +size 234133348 diff --git a/resnet152-food101-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/model.safetensors b/resnet152-food101-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..6e76e390c7a44939f45b291c4b201d94b64d43da --- /dev/null +++ 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index 0000000000000000000000000000000000000000..9ab1489f45bacaf906716c2e6da559084101d402 --- /dev/null +++ b/resnet152-food101-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 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: 0.01 + 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: 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_0.01_training_data_ratio_0.8-2000/config.json b/resnet152-food101-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..002738700083d19b6f2089a9c2d0959b8ee2b0bb --- /dev/null +++ b/resnet152-food101-batch_size_256_lr_0.01_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_256_lr_0.01_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet152-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/resnet152-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/resnet152-food101-batch_size_256_lr_0.01_training_data_ratio_0.8-3000/README.md b/resnet152-food101-batch_size_256_lr_0.01_training_data_ratio_0.8-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..9ab1489f45bacaf906716c2e6da559084101d402 --- /dev/null +++ b/resnet152-food101-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 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: 0.01 + 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: 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_0.01_training_data_ratio_0.8-3000/config.json b/resnet152-food101-batch_size_256_lr_0.01_training_data_ratio_0.8-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..002738700083d19b6f2089a9c2d0959b8ee2b0bb --- /dev/null +++ b/resnet152-food101-batch_size_256_lr_0.01_training_data_ratio_0.8-3000/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_0.01_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet152-food101-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-food101-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-food101-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/model.safetensors b/resnet152-food101-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..1dc5ac4afdf7d9b060a5b1c58fff0ac59dcc07ab --- /dev/null +++ b/resnet152-food101-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ac5a8343294d5254c50fd90ad3bfdde70ed5c2611fc1840d556e19e2d2af4377 +size 234133348 diff --git a/resnet152-food101-batch_size_64_lr_0.001_training_data_ratio_0.8-4000/model.safetensors b/resnet152-food101-batch_size_64_lr_0.001_training_data_ratio_0.8-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..208c3520f9959d8131eef0c762e4dd9dff78bac1 --- /dev/null +++ b/resnet152-food101-batch_size_64_lr_0.001_training_data_ratio_0.8-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0f3fae53b93c787ab3d1016c97d9b77d8b084d26b96e00c5394e9a72ef551b77 +size 234133348 diff --git a/resnet152-food101-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/model.safetensors b/resnet152-food101-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..c8b40246da86f3191ab54150aeb17f5d09b8830f --- /dev/null +++ b/resnet152-food101-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:53c394a24ca0d4f5b86bc513132900a9921e812ff0ef91a61c56e7e19fca934c +size 234133348 diff --git a/resnet152-food101-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/README.md b/resnet152-food101-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..eff0b63f6ce839c33dc4ccfd14eb0b0d686fb1d5 --- /dev/null +++ b/resnet152-food101-batch_size_64_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 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: 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: 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_0.01_training_data_ratio_0.5-4000/config.json b/resnet152-food101-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..002738700083d19b6f2089a9c2d0959b8ee2b0bb --- /dev/null +++ b/resnet152-food101-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/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_0.01_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet152-food101-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/resnet152-food101-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/resnet152-gtsrb-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/README.md b/resnet152-gtsrb-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..46c42244cbd378d072fde177b21d95a79d9e4e21 --- /dev/null +++ b/resnet152-gtsrb-batch_size_128_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: 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_128_lr_0.001_training_data_ratio_1.0-3000/config.json b/resnet152-gtsrb-batch_size_128_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_128_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_128_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet152-gtsrb-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/resnet152-gtsrb-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/resnet152-gtsrb-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/model.safetensors b/resnet152-gtsrb-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..9613bc0592b1f51509446391655595f4808966fd --- /dev/null +++ b/resnet152-gtsrb-batch_size_256_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:e54421bea6bf8a05052499da89e4617d83df16ca9b07dacf62cdae93d1b37191 +size 233657900 diff --git a/resnet152-gtsrb-batch_size_256_lr_0.005_training_data_ratio_0.5-3000/README.md b/resnet152-gtsrb-batch_size_256_lr_0.005_training_data_ratio_0.5-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..a45db27f3eae0c7d3e930e96280a1cce1a987ddf --- /dev/null +++ b/resnet152-gtsrb-batch_size_256_lr_0.005_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: 0.005 + 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_256_lr_0.005_training_data_ratio_0.5-3000/config.json b/resnet152-gtsrb-batch_size_256_lr_0.005_training_data_ratio_0.5-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..53161b832eb7e51bd11bce461528d4642c58be00 --- /dev/null +++ b/resnet152-gtsrb-batch_size_256_lr_0.005_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_0.005_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet152-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/resnet152-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/resnet152-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/README.md b/resnet152-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..16d28159ac14063a0985426b28837a4a815af4c0 --- /dev/null +++ b/resnet152-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/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: 0.01 + 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_0.5-2000/config.json b/resnet152-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..53161b832eb7e51bd11bce461528d4642c58be00 --- /dev/null +++ b/resnet152-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/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_256_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet152-gtsrb-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/resnet152-gtsrb-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/resnet152-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.8-1000/model.safetensors b/resnet152-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.8-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..4fd32f2ddf105e932be0fe7a0e2414cac1ee3919 --- /dev/null +++ b/resnet152-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.8-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:9b50813cf4b6a1a48dffa58d60191f30538c4d8cfdcb5f5760868461e83b42d2 +size 233657900 diff --git a/resnet152-gtsrb-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/README.md b/resnet152-gtsrb-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..2743dbb7b634d5308a52f8e188bb9c344fce9a19 --- /dev/null +++ b/resnet152-gtsrb-batch_size_256_lr_0.01_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 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: 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_0.01_training_data_ratio_1.0-4000/config.json b/resnet152-gtsrb-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..53161b832eb7e51bd11bce461528d4642c58be00 --- /dev/null +++ b/resnet152-gtsrb-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/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_256_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet152-gtsrb-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/resnet152-gtsrb-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/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/model.safetensors b/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..e21716c76d6ccb289e8526af6ac659cfb84d61fd --- /dev/null +++ b/resnet152-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f00de55eae09989837b5c4bddc0e64445218de859c39d17ff2ca3f8a04af9242 +size 233657900 diff --git a/resnet152-gtsrb-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/README.md b/resnet152-gtsrb-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..81405f1d312ef66784364c14f05c537cc21c349e --- /dev/null +++ b/resnet152-gtsrb-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 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: 0.8 +``` + +### 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_64_lr_0.01_training_data_ratio_0.8-4000/config.json b/resnet152-gtsrb-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..53161b832eb7e51bd11bce461528d4642c58be00 --- /dev/null +++ b/resnet152-gtsrb-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/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_64_lr_0.01_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet152-gtsrb-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-gtsrb-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-gtsrb-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/model.safetensors b/resnet152-gtsrb-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..76d80b78c2a1688d8a8f63417ff7bea8bbf7dabc --- /dev/null +++ b/resnet152-gtsrb-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:35cb7a4941adae3009a260861788fdf7c27ec8264a9a3bc9df5758d0db73a5fb +size 233657900 diff --git a/resnet152-kmnist-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/README.md b/resnet152-kmnist-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..c8d2911b27e81b370fe9e1b4cc72755b9acf7a22 --- /dev/null +++ b/resnet152-kmnist-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 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: 0.8 +``` + +### 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_128_lr_0.001_training_data_ratio_0.8-4000/config.json b/resnet152-kmnist-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..55c0a9dcaa76aba329cf2d4fb9ec5d866be9da8a --- /dev/null +++ b/resnet152-kmnist-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/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_0.001_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet152-kmnist-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-kmnist-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-kmnist-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/README.md b/resnet152-kmnist-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..464f5287ef13cd186f38f260a12a179ad0c077fb --- /dev/null +++ b/resnet152-kmnist-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 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: 0.8 +``` + +### 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_256_lr_0.005_training_data_ratio_0.8-2000/config.json b/resnet152-kmnist-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..55c0a9dcaa76aba329cf2d4fb9ec5d866be9da8a --- /dev/null +++ b/resnet152-kmnist-batch_size_256_lr_0.005_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_256_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet152-kmnist-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-kmnist-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-kmnist-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/README.md b/resnet152-kmnist-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..60de701d251eb8ca68378e9e2a48d6c014881d9b --- /dev/null +++ b/resnet152-kmnist-batch_size_64_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 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: 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_64_lr_0.01_training_data_ratio_0.5-2000/config.json b/resnet152-kmnist-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..55c0a9dcaa76aba329cf2d4fb9ec5d866be9da8a --- /dev/null +++ b/resnet152-kmnist-batch_size_64_lr_0.01_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_64_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet152-kmnist-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/resnet152-kmnist-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/resnet152-mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/model.safetensors b/resnet152-mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..ea7310c54f6913654bbec4e0fe338dcf13b3473d --- /dev/null +++ b/resnet152-mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:494301378fd70c46091b2c935335e661fa35c825c9f1fe4928c09577a8a20fd9 +size 233387400 diff --git a/resnet152-mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/README.md b/resnet152-mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..747bc228c2a2d5f427c5c862b969a163306597c9 --- /dev/null +++ b/resnet152-mnist-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 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: 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_128_lr_0.005_training_data_ratio_1.0-1000/config.json b/resnet152-mnist-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..499ddc3e4e5dc0456a3110b1e6f22201afc1936e --- /dev/null +++ b/resnet152-mnist-batch_size_128_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": "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_128_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet152-mnist-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-mnist-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-mnist-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/model.safetensors b/resnet152-mnist-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..0a5fa3f48c473929d1062a37faa3e58a5ded6daa --- /dev/null +++ b/resnet152-mnist-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e3894476e72af4c97d37cb1d315111117fe58fe949095ac764b5754d3261e61e +size 233387400 diff --git a/resnet152-mnist-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/model.safetensors b/resnet152-mnist-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..0a5fa3f48c473929d1062a37faa3e58a5ded6daa --- /dev/null +++ b/resnet152-mnist-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e3894476e72af4c97d37cb1d315111117fe58fe949095ac764b5754d3261e61e +size 233387400 diff --git a/resnet152-mnist-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/model.safetensors b/resnet152-mnist-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..2e986fec8bd19b2abc445ec21d2e2702a2bb1c62 --- /dev/null +++ b/resnet152-mnist-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5aca706b824dbf802f43ca7621953b06dd622b94667e7e667d6ef41a78b359b9 +size 233387400 diff --git a/resnet152-mnist-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/README.md b/resnet152-mnist-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..c635e86462d7c6e67930b5e677702b52db4439bd --- /dev/null +++ b/resnet152-mnist-batch_size_256_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 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: 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_0.001_training_data_ratio_1.0-3000/config.json b/resnet152-mnist-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..499ddc3e4e5dc0456a3110b1e6f22201afc1936e --- /dev/null +++ b/resnet152-mnist-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/config.json @@ -0,0 +1,63 @@ +{ + "architectures": [ + "ResNetForImageClassification" + ], + "depths": [ + 3, + 8, + 36, + 3 + ], + "downsample_in_bottleneck": false, + 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0000000000000000000000000000000000000000..c89d3b64fc4719e7858bbbc716dc635a7f7ff9d2 --- /dev/null +++ b/resnet152-mnist-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 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-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_0.005_training_data_ratio_0.5-1000/config.json b/resnet152-mnist-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..499ddc3e4e5dc0456a3110b1e6f22201afc1936e --- /dev/null +++ b/resnet152-mnist-batch_size_64_lr_0.005_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_0.005_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet152-mnist-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-mnist-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-mnist-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/model.safetensors b/resnet152-mnist-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..3e196a020c7e2f8b4a713270a0b88418d8371e1b --- /dev/null +++ b/resnet152-mnist-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:525f42e6bde039fe142000ec41e43cc425e7b99efae91e1ecb5334d6160166d2 +size 233387400 diff --git a/resnet152-oxford-iiit-pet-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/README.md b/resnet152-oxford-iiit-pet-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..c517192d73126db1c64378d6b60e25e263b9eef6 --- /dev/null +++ b/resnet152-oxford-iiit-pet-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 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: 0.005 + 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: 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_128_lr_0.005_training_data_ratio_1.0-1000/config.json b/resnet152-oxford-iiit-pet-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..6e9072520d9ab1e64883a84e11a3a69f3f2a85ee --- /dev/null +++ b/resnet152-oxford-iiit-pet-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/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_128_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet152-oxford-iiit-pet-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-oxford-iiit-pet-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-oxford-iiit-pet-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/model.safetensors 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sha256:8e3720757f785e784dc57db57d5b4c91554e7f1d96ec846e9eba0a3e432c71ea +size 233608716 diff --git a/resnet152-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/README.md b/resnet152-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..cfcdf3c215ebb513ab70b5c13416cb341b9121f0 --- /dev/null +++ b/resnet152-oxford-iiit-pet-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 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_: 0.2.27 +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_: 0.2.27 +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_256_lr_0.005_training_data_ratio_0.5-1000/config.json b/resnet152-oxford-iiit-pet-batch_size_256_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_256_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_256_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet152-oxford-iiit-pet-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-oxford-iiit-pet-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-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_0.5-3000/model.safetensors b/resnet152-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_0.5-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..63341897c0de5a3aa4a80f81ae1777a985580185 --- /dev/null +++ b/resnet152-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_0.5-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:775da10069b88305f1f1603c4a37b943400e91cfa629eda861ec5380cb69e58b +size 233608716 diff --git a/resnet152-oxford-iiit-pet-batch_size_256_lr_0.01_training_data_ratio_0.8-3000/model.safetensors b/resnet152-oxford-iiit-pet-batch_size_256_lr_0.01_training_data_ratio_0.8-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..01400b082b95aada7a1c8fa1fb3b037c0aad15f5 --- /dev/null +++ b/resnet152-oxford-iiit-pet-batch_size_256_lr_0.01_training_data_ratio_0.8-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6caaf484fa3a68e036339b30801a2865880aa312f489fa0b9cf82a5780a88526 +size 233608716 diff --git a/resnet152-oxford-iiit-pet-batch_size_256_lr_0.01_training_data_ratio_0.8-4000/README.md b/resnet152-oxford-iiit-pet-batch_size_256_lr_0.01_training_data_ratio_0.8-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..ee0309733da757b129eea1cb2c33eaa338a52ccf --- /dev/null +++ b/resnet152-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-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: 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: 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_256_lr_0.01_training_data_ratio_0.8-4000/config.json b/resnet152-oxford-iiit-pet-batch_size_256_lr_0.01_training_data_ratio_0.8-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..6e9072520d9ab1e64883a84e11a3a69f3f2a85ee --- /dev/null +++ b/resnet152-oxford-iiit-pet-batch_size_256_lr_0.01_training_data_ratio_0.8-4000/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_256_lr_0.01_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet152-oxford-iiit-pet-batch_size_256_lr_0.01_training_data_ratio_0.8-4000/preprocessor_config.json new file mode 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sha256:7f80c51bf3a3fb0ced4493a030d0d4c7be32a39adfa4818fb4efb9b413f6f8b2 +size 233608716 diff --git a/resnet152-oxford_flowers102-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/README.md b/resnet152-oxford_flowers102-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..7d8b6519cb2e133640ceccc687a9c3eafcc2ee7b --- /dev/null +++ b/resnet152-oxford_flowers102-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 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-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_0.005_training_data_ratio_0.5-2000/config.json b/resnet152-oxford_flowers102-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..73d4c5807d169cb2e901ab29de6ec9f57efd9347 --- /dev/null +++ b/resnet152-oxford_flowers102-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/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": 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"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, + 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a/resnet152-oxford_flowers102-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/model.safetensors b/resnet152-oxford_flowers102-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..9354b99aa472c9400cee5dc4a4241a610770b823 --- /dev/null +++ b/resnet152-oxford_flowers102-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:297993f328c7c66d9add54d2936aeaaaf42be4ad3d04cc0cb42d5acd8d10d380 +size 234141544 diff --git a/resnet152-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/README.md b/resnet152-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..b5e7106279f930efdc14a290221f5508a90f7a24 --- /dev/null +++ b/resnet152-oxford_flowers102-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 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: 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_128_lr_0.01_training_data_ratio_0.5-3000/config.json b/resnet152-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..73d4c5807d169cb2e901ab29de6ec9f57efd9347 --- /dev/null +++ b/resnet152-oxford_flowers102-batch_size_128_lr_0.01_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_128_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet152-oxford_flowers102-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-oxford_flowers102-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-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/model.safetensors b/resnet152-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..41cd0e18f76448f6521529799f520ca73d8e2bd4 --- /dev/null +++ b/resnet152-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:af36f874ec81cf99316c15c1fc9ba794f7b9f2499b03caec12da57b8eefbd56c +size 234141544 diff --git a/resnet152-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/README.md b/resnet152-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..909a39c878be8aa4e71f634e7a73e5bdf2c6a578 --- /dev/null +++ b/resnet152-oxford_flowers102-batch_size_128_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 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-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_0.8-3000/config.json b/resnet152-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..73d4c5807d169cb2e901ab29de6ec9f57efd9347 --- /dev/null +++ b/resnet152-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/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", + 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+size 233321808 diff --git a/resnet152-pcam-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/README.md b/resnet152-pcam-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..9404e5e50ca1d593ba5268cff0a9f967364982af --- /dev/null +++ b/resnet152-pcam-batch_size_128_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 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-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_0.8-1000/config.json b/resnet152-pcam-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..3cb201dc7dfa380d2b50c3d20326ba2521864600 --- /dev/null +++ b/resnet152-pcam-batch_size_128_lr_0.01_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": "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_0.8-1000/preprocessor_config.json b/resnet152-pcam-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-pcam-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 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b/resnet152-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..2970f6f529145b8a673bd63972e652b92610c0b7 --- /dev/null +++ b/resnet152-rendered-sst2-batch_size_128_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 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-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_0.8-4000/config.json b/resnet152-rendered-sst2-batch_size_128_lr_0.005_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_0.005_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_0.005_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet152-rendered-sst2-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/resnet152-rendered-sst2-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/resnet152-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_1.0-4000/model.safetensors b/resnet152-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_1.0-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..1b5c781ab7b2be15354c1efa2ed509054e83d69a --- /dev/null +++ b/resnet152-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_1.0-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:64adeeb75059319a065a82b31ec1b26b8a19064312ee95cdb6b863ada200d78f +size 233321808 diff --git a/resnet152-rendered-sst2-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/README.md b/resnet152-rendered-sst2-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..66f55b732df88ab3f5ccb9fa6c6a26ed7d17d708 --- /dev/null +++ b/resnet152-rendered-sst2-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 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-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_0.001_training_data_ratio_0.5-3000/config.json b/resnet152-rendered-sst2-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..054ed535def906c22cb0ab0c6b25c9c88b195f06 --- /dev/null +++ b/resnet152-rendered-sst2-batch_size_256_lr_0.001_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": "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_0.001_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet152-rendered-sst2-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-rendered-sst2-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-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/README.md b/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..2970f6f529145b8a673bd63972e652b92610c0b7 --- /dev/null +++ b/resnet152-rendered-sst2-batch_size_256_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 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-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_0.8-4000/config.json b/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..054ed535def906c22cb0ab0c6b25c9c88b195f06 --- /dev/null +++ b/resnet152-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/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_256_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet152-rendered-sst2-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/resnet152-rendered-sst2-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/resnet152-rendered-sst2-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/model.safetensors b/resnet152-rendered-sst2-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..99dbb996bc72dacd9b9b3b91f5b64b9808366ed8 --- /dev/null +++ b/resnet152-rendered-sst2-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c3e1041cf0ec97617efa154c1157dac7528e959a7ff6b3924326c0f834c75efb +size 233321808 diff --git a/resnet152-rendered-sst2-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/README.md b/resnet152-rendered-sst2-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..fc45801bbb70938d15106054ce7869b1ac5792a0 --- /dev/null +++ b/resnet152-rendered-sst2-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 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: 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_64_lr_0.001_training_data_ratio_1.0-4000/config.json b/resnet152-rendered-sst2-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..054ed535def906c22cb0ab0c6b25c9c88b195f06 --- /dev/null +++ b/resnet152-rendered-sst2-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/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_64_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet152-rendered-sst2-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-rendered-sst2-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-rendered-sst2-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/README.md b/resnet152-rendered-sst2-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..40144cf07b1bc9a06ae5dec4d5122ac4c0a2df5e --- /dev/null +++ b/resnet152-rendered-sst2-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 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: 0.01 + 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: 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_64_lr_0.01_training_data_ratio_0.8-1000/config.json b/resnet152-rendered-sst2-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..054ed535def906c22cb0ab0c6b25c9c88b195f06 --- /dev/null +++ b/resnet152-rendered-sst2-batch_size_64_lr_0.01_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_64_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet152-rendered-sst2-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-rendered-sst2-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 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/dev/null +++ b/resnet152-resisc45-batch_size_128_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 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_1.0-1000/config.json b/resnet152-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..1ccd6b3d4942b65d4b1b5d4a4f27c0403ba41898 --- /dev/null +++ b/resnet152-resisc45-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/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_1.0-1000/preprocessor_config.json b/resnet152-resisc45-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-resisc45-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-resisc45-batch_size_256_lr_0.01_training_data_ratio_0.8-4000/README.md b/resnet152-resisc45-batch_size_256_lr_0.01_training_data_ratio_0.8-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..f32e2f09111d555a41b4ea18fafede597819bfb1 --- /dev/null +++ b/resnet152-resisc45-batch_size_256_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 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: 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_256_lr_0.01_training_data_ratio_0.8-4000/config.json b/resnet152-resisc45-batch_size_256_lr_0.01_training_data_ratio_0.8-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..1ccd6b3d4942b65d4b1b5d4a4f27c0403ba41898 --- /dev/null +++ b/resnet152-resisc45-batch_size_256_lr_0.01_training_data_ratio_0.8-4000/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_256_lr_0.01_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet152-resisc45-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/resnet152-resisc45-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/resnet152-resisc45-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/README.md b/resnet152-resisc45-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..b374d611ca3153ab650e7fdc8d8cfa5b88f09585 --- /dev/null +++ b/resnet152-resisc45-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 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: 0.001 + 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_64_lr_0.001_training_data_ratio_1.0-1000/config.json b/resnet152-resisc45-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..1ccd6b3d4942b65d4b1b5d4a4f27c0403ba41898 --- /dev/null +++ b/resnet152-resisc45-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/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_0.001_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet152-resisc45-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-resisc45-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-resisc45-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/model.safetensors b/resnet152-resisc45-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..2254a22f6b0ba7e1d7f88355ddb9323a6818a34a --- /dev/null +++ b/resnet152-resisc45-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:bd7f723a81aaa9055d0015b7316da8275637090db4b34e2bd5d71ac836ca74df +size 233674292 diff --git a/resnet152-resisc45-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/model.safetensors b/resnet152-resisc45-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..2d28db7acc47e704efd29ee8527aaef042c2498b --- /dev/null +++ b/resnet152-resisc45-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:1aa453a3baca7e439c5e51fefc7a5be629268c17d8602c5f3a766087ba7f9ae8 +size 233674292 diff --git a/resnet152-stanford-cars-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/README.md b/resnet152-stanford-cars-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..5fcd0be4c4e150ec23aef531f2d95e876d51b5d5 --- /dev/null +++ b/resnet152-stanford-cars-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/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: 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_1.0-2000/config.json b/resnet152-stanford-cars-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..1e0f59991da08604f363224d408031555ecd60f4 --- /dev/null +++ b/resnet152-stanford-cars-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/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_0.005_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet152-stanford-cars-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/resnet152-stanford-cars-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/resnet152-stanford-cars-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/model.safetensors b/resnet152-stanford-cars-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..16fcf5bcc1d5fff62d507ed70e514b259d65d5f2 --- /dev/null +++ b/resnet152-stanford-cars-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:91ab33cf8c25ce723212064649b585f648aaaa0028c0b30654aae09904b9ab21 +size 234912000 diff --git a/resnet152-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/README.md b/resnet152-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..aabeeb949b3b90c40d86375d99f41262e266f3a5 --- /dev/null +++ b/resnet152-stanford-cars-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 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: 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_256_lr_0.01_training_data_ratio_1.0-1000/config.json b/resnet152-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..1e0f59991da08604f363224d408031555ecd60f4 --- /dev/null +++ b/resnet152-stanford-cars-batch_size_256_lr_0.01_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_256_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet152-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/resnet152-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/resnet152-stanford-cars-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/README.md b/resnet152-stanford-cars-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..6095934c575acd754da2648f73fba2a70edf104c --- /dev/null +++ b/resnet152-stanford-cars-batch_size_64_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: 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: 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_64_lr_0.001_training_data_ratio_0.5-2000/config.json b/resnet152-stanford-cars-batch_size_64_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_64_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_64_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet152-stanford-cars-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/resnet152-stanford-cars-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/resnet152-stanford-cars-batch_size_64_lr_0.001_training_data_ratio_0.8-1000/model.safetensors b/resnet152-stanford-cars-batch_size_64_lr_0.001_training_data_ratio_0.8-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..bb66db01ffa80595a7945c00ac6048c34939f48b --- /dev/null +++ b/resnet152-stanford-cars-batch_size_64_lr_0.001_training_data_ratio_0.8-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:dd8271fcf748924d381b6065bdf64b57c2e22327f5cf8e6b35d24826d8d1b4e2 +size 234912000 diff --git a/resnet152-stanford-cars-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/README.md b/resnet152-stanford-cars-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..c3300aa6f55a91a1854f9da47430c0a5fb51badf --- /dev/null +++ b/resnet152-stanford-cars-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 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: 0.8 +``` + +### 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_64_lr_0.005_training_data_ratio_0.8-2000/config.json b/resnet152-stanford-cars-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..1e0f59991da08604f363224d408031555ecd60f4 --- /dev/null +++ b/resnet152-stanford-cars-batch_size_64_lr_0.005_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_64_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet152-stanford-cars-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-stanford-cars-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-stl10-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/README.md b/resnet152-stl10-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..e2de1b2d3cd45bcdb047e985f6f236f9b785d4f4 --- /dev/null +++ b/resnet152-stl10-batch_size_128_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 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: 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_0.001_training_data_ratio_1.0-3000/config.json b/resnet152-stl10-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..4e96dfc41ebe7919b6d046db75114c5d465f222d --- /dev/null +++ b/resnet152-stl10-batch_size_128_lr_0.001_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_0.001_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet152-stl10-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/resnet152-stl10-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/resnet152-stl10-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/README.md b/resnet152-stl10-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..3f7ab36c9e531817eaf53a8d12c257b8811fc03b --- /dev/null +++ b/resnet152-stl10-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/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: 0.005 + 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_0.5-1000/config.json b/resnet152-stl10-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..4e96dfc41ebe7919b6d046db75114c5d465f222d --- /dev/null +++ b/resnet152-stl10-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/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_0.005_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet152-stl10-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-stl10-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-stl10-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/README.md b/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..fdc1d0ff9dd59217e7ecdfd49a585d01b8a7df0c --- /dev/null +++ b/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/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 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_0.8-4000/config.json b/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..4e96dfc41ebe7919b6d046db75114c5d465f222d --- /dev/null +++ b/resnet152-stl10-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/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": "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_0.8-4000/preprocessor_config.json b/resnet152-stl10-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/resnet152-stl10-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/resnet152-stl10-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/model.safetensors b/resnet152-stl10-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..9cb1268e5c228f7daac9eb25dd2675511a4d9ff2 --- /dev/null +++ b/resnet152-stl10-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:9ae2aed4654211b132639bce1b8ccba0fc37c9d4c3372843712510f898e9c977 +size 233387400 diff --git a/resnet152-stl10-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/README.md b/resnet152-stl10-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..7579e51377aba6cd2fe08654745e695fca0fc45a --- /dev/null +++ b/resnet152-stl10-batch_size_256_lr_0.005_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 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: 0.8 +``` + +### 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_0.005_training_data_ratio_0.8-1000/config.json b/resnet152-stl10-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..4e96dfc41ebe7919b6d046db75114c5d465f222d --- /dev/null +++ b/resnet152-stl10-batch_size_256_lr_0.005_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": "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_0.005_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet152-stl10-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/resnet152-stl10-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/resnet152-stl10-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/README.md b/resnet152-stl10-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..a9b45d80b2a3c2041d9cca180dcf833a442ae5a0 --- /dev/null +++ b/resnet152-stl10-batch_size_256_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 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_256_lr_0.01_training_data_ratio_1.0-2000/config.json b/resnet152-stl10-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..4e96dfc41ebe7919b6d046db75114c5d465f222d --- /dev/null +++ b/resnet152-stl10-batch_size_256_lr_0.01_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_256_lr_0.01_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet152-stl10-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/resnet152-stl10-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/resnet152-stl10-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/model.safetensors b/resnet152-stl10-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..681c20e8d8993ce69e54c230171d3bddeb71bff3 --- /dev/null +++ b/resnet152-stl10-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:86a73e70a1cf3d7eddc776460abebbed7a3e896814a7fee2fa14883ee17dc929 +size 233387400 diff --git a/resnet152-stl10-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/README.md b/resnet152-stl10-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..1430458264ab55de153baeb215afe6b2393c6a08 --- /dev/null +++ b/resnet152-stl10-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 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: 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_0.001_training_data_ratio_1.0-3000/config.json b/resnet152-stl10-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..4e96dfc41ebe7919b6d046db75114c5d465f222d --- /dev/null +++ b/resnet152-stl10-batch_size_64_lr_0.001_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_64_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet152-stl10-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-stl10-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-stl10-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/model.safetensors b/resnet152-stl10-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..9a9d17309649704e18eec316baaf37206b36dc9f --- /dev/null +++ b/resnet152-stl10-batch_size_64_lr_0.01_training_data_ratio_0.5-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:bb250caa7aee8508e8e2f28b1884ff438bd5ec7dd1ada3932c333d4a1cef0c92 +size 233387400 diff --git a/resnet152-stl10-batch_size_64_lr_0.01_training_data_ratio_0.8-3000/README.md b/resnet152-stl10-batch_size_64_lr_0.01_training_data_ratio_0.8-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..949dd3aa1a34306ae2f39cebab20aacc4e3d7843 --- /dev/null +++ b/resnet152-stl10-batch_size_64_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 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: 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_64_lr_0.01_training_data_ratio_0.8-3000/config.json b/resnet152-stl10-batch_size_64_lr_0.01_training_data_ratio_0.8-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..4e96dfc41ebe7919b6d046db75114c5d465f222d --- /dev/null +++ b/resnet152-stl10-batch_size_64_lr_0.01_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_64_lr_0.01_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet152-stl10-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/resnet152-stl10-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/resnet152-sun397-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/model.safetensors b/resnet152-sun397-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..a84ac205fb4f0f10ac385a0cb9a237f62c9a38da --- /dev/null +++ b/resnet152-sun397-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e1b05e778a754dbb19a1afbcdc138a1a2ddf4f803ead2b0a87466a7150030f8b +size 236559468 diff --git a/resnet152-sun397-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/model.safetensors b/resnet152-sun397-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..4c9ce5a9453817ff732489fcdf10773f51c65117 --- /dev/null +++ b/resnet152-sun397-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5baf4bea5796540b9423a08849b8b3a43cced4e120158f19ad27f8b45ea5d0d2 +size 236559468 diff --git a/resnet152-sun397-batch_size_256_lr_0.001_training_data_ratio_1.0-1000/README.md b/resnet152-sun397-batch_size_256_lr_0.001_training_data_ratio_1.0-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..8d613ed9100146b1b6b945a12a7f8d2b40245a6a --- /dev/null +++ b/resnet152-sun397-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 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_256_lr_0.001_training_data_ratio_1.0-1000/config.json b/resnet152-sun397-batch_size_256_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_256_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_256_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet152-sun397-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-sun397-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-sun397-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/model.safetensors b/resnet152-sun397-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..64ac9cab9836308d4788c4303fcf5a1c8287eea9 --- /dev/null +++ b/resnet152-sun397-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:bffb9cdb26ecbccfffddb18254e770aa9d4057a6a155ce3f3459f3774af82c12 +size 236559468 diff --git a/resnet152-sun397-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/README.md b/resnet152-sun397-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..2253b0dad1d7ed6de24c4d2063670d959edee6b0 --- /dev/null +++ b/resnet152-sun397-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 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_256_lr_0.005_training_data_ratio_0.8-2000/config.json b/resnet152-sun397-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..235472e739b23ead2b88b4266434b8f42502d7ea --- /dev/null +++ b/resnet152-sun397-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/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_256_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet152-sun397-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-sun397-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 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https://git-lfs.github.com/spec/v1 +oid sha256:ddfc446cd3f5a1a175429957d6da4fd6ae610fa8aae90fad3c61fdc7e2d76ae3 +size 236559468 diff --git a/resnet152-sun397-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/README.md b/resnet152-sun397-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..d714b91c6bd849b7c24a2f02a74d0e43259b3144 --- /dev/null +++ b/resnet152-sun397-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 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: 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_256_lr_0.01_training_data_ratio_1.0-1000/config.json b/resnet152-sun397-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..235472e739b23ead2b88b4266434b8f42502d7ea --- /dev/null +++ b/resnet152-sun397-batch_size_256_lr_0.01_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, + 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b/resnet152-svhn-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/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: 0.01 + 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: 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_0.01_training_data_ratio_1.0-4000/config.json b/resnet152-svhn-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..499ddc3e4e5dc0456a3110b1e6f22201afc1936e --- /dev/null +++ b/resnet152-svhn-batch_size_256_lr_0.01_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": "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_0.01_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet152-svhn-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/resnet152-svhn-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/resnet152-svhn-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/model.safetensors b/resnet152-svhn-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..4ebae9d2476261bba060e1c4782b4184e5e60dbd --- /dev/null +++ b/resnet152-svhn-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d40f216fca7449d04248b5d2bc95852a432c6bb475b98fccfd6ace5e89c24b0e +size 233387400 diff --git a/resnet152-svhn-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/model.safetensors b/resnet152-svhn-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..b46e56dee33cbb687f625d1b21b2ab251e13c92e --- /dev/null +++ b/resnet152-svhn-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7b631f214913bb1989d3f32c5633cda6dc5e7b59f650b7ffa9a995522bd8755f +size 233387400 diff --git a/resnet152-svhn-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/model.safetensors b/resnet152-svhn-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..f5a6fcb17dcdb425b3bec5ab099e1bf205982dec --- /dev/null +++ b/resnet152-svhn-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c10823afef9f9ecce2b0b26800ba2c7552b74655d42791b5d88ffab64156d541 +size 233387400 diff --git a/resnet18-cifar10-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/README.md b/resnet18-cifar10-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..39df47a03dd1b85b13d07f650ac5b9db95496527 --- /dev/null +++ b/resnet18-cifar10-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 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: 0.005 + 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: 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_0.005_training_data_ratio_0.8-2000/config.json b/resnet18-cifar10-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..a6fd7768d9fade7e7d7df7ed5cd1e93ae4baec32 --- /dev/null +++ b/resnet18-cifar10-batch_size_128_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": "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_0.005_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet18-cifar10-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-cifar10-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-cifar10-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/README.md b/resnet18-cifar10-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..d1b8eb2af41202fbc82d56ac57da02826c1bf5bf --- /dev/null +++ b/resnet18-cifar10-batch_size_128_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 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-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_0.5-2000/config.json b/resnet18-cifar10-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..a6fd7768d9fade7e7d7df7ed5cd1e93ae4baec32 --- /dev/null +++ b/resnet18-cifar10-batch_size_128_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": "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_0.5-2000/preprocessor_config.json 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https://git-lfs.github.com/spec/v1 +oid sha256:6a1d318dfd21e1a3e27798cd0eff751ed6666803da1324a01370d13590c030b0 +size 44780752 diff --git a/resnet18-cifar10-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/README.md b/resnet18-cifar10-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..d4fc61d7064e35e0a32306c75f340c36e434e767 --- /dev/null +++ b/resnet18-cifar10-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 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: 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_64_lr_0.005_training_data_ratio_1.0-3000/config.json b/resnet18-cifar10-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..a6fd7768d9fade7e7d7df7ed5cd1e93ae4baec32 --- /dev/null +++ b/resnet18-cifar10-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/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_1.0-3000/preprocessor_config.json b/resnet18-cifar10-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-cifar10-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-cifar100-batch_size_128_lr_0.001_training_data_ratio_0.5-1000/README.md b/resnet18-cifar100-batch_size_128_lr_0.001_training_data_ratio_0.5-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..a31d091b885b5f0b1f2bc5c6728c19c5ef7810ba --- /dev/null +++ b/resnet18-cifar100-batch_size_128_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 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: 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_128_lr_0.001_training_data_ratio_0.5-1000/config.json b/resnet18-cifar100-batch_size_128_lr_0.001_training_data_ratio_0.5-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..5c3f41b9ed6c00df33ffaef448e5b6c8ac8a8d65 --- /dev/null +++ b/resnet18-cifar100-batch_size_128_lr_0.001_training_data_ratio_0.5-1000/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, 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sha256:17983fb6378791b6ddc368b48ab16275c7a4fa2ba960db0de467c99cec0ecf67 +size 44965456 diff --git a/resnet18-cifar100-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/README.md b/resnet18-cifar100-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..3fa142b2049c64c95234119ce05fa6e9e4cfa9fb --- /dev/null +++ b/resnet18-cifar100-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/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: 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_1.0-4000/config.json b/resnet18-cifar100-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..5c3f41b9ed6c00df33ffaef448e5b6c8ac8a8d65 --- /dev/null +++ b/resnet18-cifar100-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/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_256_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet18-cifar100-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-cifar100-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-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/model.safetensors b/resnet18-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..f1fea7a4fac9d735c1d854e7ab0f454dac798e04 --- /dev/null +++ b/resnet18-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b5dc5b858c61dd5f6e33f04ecee56a729b26abbf861a6f35664e2a51a55b9975 +size 44965456 diff --git a/resnet18-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/README.md b/resnet18-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..a7f40b79c93196b16faec66aef791f8d4c02aefb --- /dev/null +++ b/resnet18-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/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 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_0.8-2000/config.json b/resnet18-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..5c3f41b9ed6c00df33ffaef448e5b6c8ac8a8d65 --- /dev/null +++ b/resnet18-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/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": 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"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": 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0000000000000000000000000000000000000000..db4ab31588baa5caa3299d063f72b617be12e9b5 --- /dev/null +++ b/resnet18-dtd-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f940f06f830a3a7a72c27c987ba02afc193d889e73dc7b2aff858a490f9d83cc +size 44856700 diff --git a/resnet18-dtd-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/README.md b/resnet18-dtd-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..eb156b47429d691d2e9b9b313a3876f724e75687 --- /dev/null +++ b/resnet18-dtd-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/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 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_1.0-1000/config.json b/resnet18-dtd-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..f2ce6cd6d95d0a7c1905aabe792d0a5c4e2f515a --- /dev/null +++ b/resnet18-dtd-batch_size_128_lr_0.01_training_data_ratio_1.0-1000/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_1.0-1000/preprocessor_config.json b/resnet18-dtd-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-dtd-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-dtd-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/README.md b/resnet18-dtd-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..1b13017160124e96359cac50e1978c3d3892606b --- /dev/null +++ b/resnet18-dtd-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 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: 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: 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_0.001_training_data_ratio_0.5-1000/config.json b/resnet18-dtd-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..f2ce6cd6d95d0a7c1905aabe792d0a5c4e2f515a --- /dev/null +++ b/resnet18-dtd-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/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_0.001_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet18-dtd-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-dtd-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-dtd-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/README.md b/resnet18-dtd-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..7f0c77a8398e0772a527ba0ac38896a128beb8cb --- /dev/null +++ b/resnet18-dtd-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/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 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_0.8-1000/config.json b/resnet18-dtd-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..f2ce6cd6d95d0a7c1905aabe792d0a5c4e2f515a --- /dev/null +++ b/resnet18-dtd-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/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_0.8-1000/preprocessor_config.json b/resnet18-dtd-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/resnet18-dtd-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/resnet18-dtd-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/README.md b/resnet18-dtd-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..c72e7f769598014a1c4ea53e10185c28cd5d5b37 --- /dev/null +++ b/resnet18-dtd-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 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: 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_0.01_training_data_ratio_0.8-2000/config.json b/resnet18-dtd-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..f2ce6cd6d95d0a7c1905aabe792d0a5c4e2f515a --- /dev/null +++ b/resnet18-dtd-batch_size_256_lr_0.01_training_data_ratio_0.8-2000/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", + 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"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_0.01_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet18-dtd-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-dtd-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 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b/resnet18-emnist_letters-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..722439a0dea011686afb81156228d6c9acfee64d --- /dev/null +++ b/resnet18-emnist_letters-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/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 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_0.5-1000/config.json b/resnet18-emnist_letters-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..13f9e0905aba09ddfb07306023093f9a4322f7a7 --- /dev/null +++ b/resnet18-emnist_letters-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/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_0.5-1000/preprocessor_config.json b/resnet18-emnist_letters-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/resnet18-emnist_letters-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/resnet18-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/README.md b/resnet18-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..eefd66ed5587f6970966be69be2a373f0cb6f354 --- /dev/null +++ b/resnet18-emnist_letters-batch_size_128_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 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: 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_128_lr_0.01_training_data_ratio_0.8-2000/config.json b/resnet18-emnist_letters-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..13f9e0905aba09ddfb07306023093f9a4322f7a7 --- /dev/null +++ b/resnet18-emnist_letters-batch_size_128_lr_0.01_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_128_lr_0.01_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet18-emnist_letters-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/resnet18-emnist_letters-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/resnet18-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/README.md b/resnet18-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..e331a778515ba03165691113a983c527f019a2df --- /dev/null +++ b/resnet18-emnist_letters-batch_size_64_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 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-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_0.001_training_data_ratio_0.5-1000/config.json b/resnet18-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..13f9e0905aba09ddfb07306023093f9a4322f7a7 --- /dev/null +++ b/resnet18-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/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_0.001_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet18-emnist_letters-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-emnist_letters-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-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/README.md b/resnet18-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..4312de8813ef041eab0f6458652bf1ddcb33b0f0 --- /dev/null +++ b/resnet18-emnist_letters-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 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: 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_0.001_training_data_ratio_0.8-3000/config.json b/resnet18-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..13f9e0905aba09ddfb07306023093f9a4322f7a7 --- /dev/null +++ b/resnet18-emnist_letters-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/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_64_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet18-emnist_letters-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-emnist_letters-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-emnist_letters-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/model.safetensors b/resnet18-emnist_letters-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..15e6b9df56b8336c2ae1b2a4754e48b447014e7d --- /dev/null +++ b/resnet18-emnist_letters-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6366866bcc30e5e894318f51c61a3a3aba9dc2ab977b7d586c00c6d27a7757c1 +size 44813584 diff --git a/resnet18-emnist_letters-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/README.md b/resnet18-emnist_letters-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..fa0acdfdc9505f1b32760ace4335c55646a19241 --- /dev/null +++ b/resnet18-emnist_letters-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 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: 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_0.01_training_data_ratio_0.8-1000/config.json b/resnet18-emnist_letters-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..13f9e0905aba09ddfb07306023093f9a4322f7a7 --- /dev/null +++ b/resnet18-emnist_letters-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/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_0.01_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet18-emnist_letters-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-emnist_letters-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-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.8-1000/README.md b/resnet18-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.8-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..b40e807de45ed64e065a48fbb86f47431efe2d1b --- /dev/null +++ b/resnet18-eurosat-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 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-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_0.005_training_data_ratio_0.8-1000/config.json b/resnet18-eurosat-batch_size_128_lr_0.005_training_data_ratio_0.8-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..cf61d0357a8d4fef0a1593df0f7b561cb9c545a1 --- /dev/null +++ b/resnet18-eurosat-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": "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_0.005_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet18-eurosat-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-eurosat-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-eurosat-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/README.md b/resnet18-eurosat-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..e98f7a46525955fcc384307bbfadff176ebf86ae --- /dev/null +++ b/resnet18-eurosat-batch_size_128_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 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: 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_128_lr_0.01_training_data_ratio_0.5-4000/config.json b/resnet18-eurosat-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..cf61d0357a8d4fef0a1593df0f7b561cb9c545a1 --- /dev/null +++ b/resnet18-eurosat-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/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": "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_0.5-4000/preprocessor_config.json b/resnet18-eurosat-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/resnet18-eurosat-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/resnet18-eurosat-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/model.safetensors b/resnet18-eurosat-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..6ed22000f071055b813c9ea5059f53754a8d8975 --- /dev/null +++ b/resnet18-eurosat-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:515d745899fbb847f607f77a4f124796ad8e26963fc7c0767ecf6715e3882828 +size 44780752 diff --git a/resnet18-eurosat-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/README.md b/resnet18-eurosat-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..cfc91b3ca34169327b0380ea95951e28d4a5f0f5 --- /dev/null +++ b/resnet18-eurosat-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 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: 0.001 + 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: 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_0.001_training_data_ratio_1.0-2000/config.json b/resnet18-eurosat-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..cf61d0357a8d4fef0a1593df0f7b561cb9c545a1 --- /dev/null +++ b/resnet18-eurosat-batch_size_256_lr_0.001_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": "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_0.001_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet18-eurosat-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-eurosat-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-eurosat-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/model.safetensors b/resnet18-eurosat-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..d4742f30be0a30d4538dcebdb33a7d4bd68e673f --- /dev/null +++ b/resnet18-eurosat-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e88b0d1030fdc1967f4bfa5a6bc1277e62e5e26f63f56bd9311129faac3d1c80 +size 44780752 diff --git a/resnet18-eurosat-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/model.safetensors b/resnet18-eurosat-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..a729afe4d3074f3977614204a7c236c849bafec1 --- /dev/null +++ b/resnet18-eurosat-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6a1d318dfd21e1a3e27798cd0eff751ed6666803da1324a01370d13590c030b0 +size 44780752 diff --git a/resnet18-eurosat-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/README.md b/resnet18-eurosat-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..cc5bb681ca738270c858dd2c66d5cbd93cd32906 --- /dev/null +++ b/resnet18-eurosat-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 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: 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: 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_1.0-4000/config.json b/resnet18-eurosat-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..cf61d0357a8d4fef0a1593df0f7b561cb9c545a1 --- /dev/null +++ b/resnet18-eurosat-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": "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_1.0-4000/preprocessor_config.json b/resnet18-eurosat-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-eurosat-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-eurosat-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/README.md b/resnet18-eurosat-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..cd2b707484b7a4c4636ea07b25e97a0e713ebd73 --- /dev/null +++ b/resnet18-eurosat-batch_size_64_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 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: 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: 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_64_lr_0.001_training_data_ratio_0.5-2000/config.json b/resnet18-eurosat-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..cf61d0357a8d4fef0a1593df0f7b561cb9c545a1 --- /dev/null +++ b/resnet18-eurosat-batch_size_64_lr_0.001_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": "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_64_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet18-eurosat-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/resnet18-eurosat-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/resnet18-eurosat-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/README.md b/resnet18-eurosat-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..376e18071bf03573a90cdb2b45892ebd8376e3da --- /dev/null +++ b/resnet18-eurosat-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 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: 0.01 + 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: 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_64_lr_0.01_training_data_ratio_1.0-1000/config.json b/resnet18-eurosat-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..cf61d0357a8d4fef0a1593df0f7b561cb9c545a1 --- /dev/null +++ b/resnet18-eurosat-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/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": "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_64_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet18-eurosat-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-eurosat-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-eurosat-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/model.safetensors b/resnet18-eurosat-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..1ef23e1c758650f77446b672c22b32058ed41992 --- /dev/null +++ b/resnet18-eurosat-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:30cf38151cde03ba7f2b1fa0a3902118a493de027ffbc5db1f41074a0d907c89 +size 44780752 diff --git a/resnet18-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/model.safetensors b/resnet18-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..f8613b554c3036410184db609ba0925d9ba99008 --- /dev/null +++ b/resnet18-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:dfbfee4d5e4779f487b518775bad0fdb9e23e16dd52f25e858f23ffad03c836f +size 44780752 diff --git a/resnet18-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md b/resnet18-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..970304d6671d2eb0ab63d2469e2a59ba49aa6f71 --- /dev/null +++ b/resnet18-fashion_mnist-batch_size_128_lr_0.005_training_data_ratio_0.8-3000/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: 0.005 + 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_0.8-3000/config.json b/resnet18-fashion_mnist-batch_size_128_lr_0.005_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_0.005_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": "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_0.8-3000/preprocessor_config.json b/resnet18-fashion_mnist-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-fashion_mnist-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-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/README.md b/resnet18-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..1e646e825b9103c7d7c9316f55e19da0c70fcb98 --- /dev/null +++ b/resnet18-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/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: 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_0.8-4000/config.json b/resnet18-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..95053393425e99bf8747d9695556f752509f4b0b --- /dev/null +++ b/resnet18-fashion_mnist-batch_size_256_lr_0.001_training_data_ratio_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": "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 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file mode 100644 index 0000000000000000000000000000000000000000..5e830aaeb240f1c12b13fa2ef9b92d9d0fe5bccc --- /dev/null +++ b/resnet18-fashion_mnist-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e36ba11eb2e9586a9922a32861d762c1f4f1032eac1b4d86197831993931db5a +size 44780752 diff --git a/resnet18-fashion_mnist-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/model.safetensors b/resnet18-fashion_mnist-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..7117c526a905100742f1f06bc4c5a78b5e0c6f0a --- /dev/null +++ b/resnet18-fashion_mnist-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3274a2c466d210d1bd8bfde03cf2e7bbba74bb0b1a692d1c956115f17c6bc042 +size 44780752 diff --git a/resnet18-fashion_mnist-batch_size_64_lr_0.001_training_data_ratio_0.8-4000/model.safetensors b/resnet18-fashion_mnist-batch_size_64_lr_0.001_training_data_ratio_0.8-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..859dde09aa9c8232e915375932694cf4e515f29e --- /dev/null +++ b/resnet18-fashion_mnist-batch_size_64_lr_0.001_training_data_ratio_0.8-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6cd289c87b26691ff5bad6253a84e62263740b8a881af439adf4d0c0b7a9d5b7 +size 44780752 diff --git a/resnet18-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/README.md b/resnet18-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..0221f2b3711bbbfd9c3d1ff822ec29c1a5dfa734 --- /dev/null +++ b/resnet18-fashion_mnist-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 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: 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_64_lr_0.005_training_data_ratio_0.8-1000/config.json b/resnet18-fashion_mnist-batch_size_64_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_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": "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_0.005_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet18-fashion_mnist-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-fashion_mnist-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-fer2013-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/model.safetensors b/resnet18-fer2013-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..d0b6d4a04fbc04bf2da22f29d7d272a6f44c044b --- /dev/null +++ b/resnet18-fer2013-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e77d70b68f6c073b93601a9baa76e5197ec33eefe7ee151fdf65dcf2c01bb5c4 +size 44774596 diff --git a/resnet18-fer2013-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/model.safetensors b/resnet18-fer2013-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..7205f4ffd5b7a1e52de93e6715a87d5537b07ffb --- /dev/null +++ b/resnet18-fer2013-batch_size_128_lr_0.001_training_data_ratio_1.0-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b0a7ff53d77bc37a02ad0feede05c29bfe8483b80d4d0d136bd669c6c62d15a9 +size 44774596 diff --git a/resnet18-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/README.md b/resnet18-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..2a75e6b659361d46292f854331440e03bc0e8b42 --- /dev/null +++ b/resnet18-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/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: 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: 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_0.01_training_data_ratio_0.5-4000/config.json b/resnet18-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..ce988daea92558cbffcf8c943ef8039e1e9a5ec2 --- /dev/null +++ b/resnet18-fer2013-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/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_128_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet18-fer2013-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/resnet18-fer2013-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/resnet18-fer2013-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/model.safetensors b/resnet18-fer2013-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..38a6ca445f10ba9f24e115f75d1596fea2263d93 --- /dev/null +++ b/resnet18-fer2013-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f55ec4b70febe548726dcb1a29bb7a8a3946aff93acf9246baf660aff2c75fce +size 44774596 diff --git a/resnet18-fer2013-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/README.md b/resnet18-fer2013-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..388758c91f8f7f7513224e09df1f0f42dcba012e --- /dev/null +++ b/resnet18-fer2013-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/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: 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: 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_0.005_training_data_ratio_0.5-4000/config.json b/resnet18-fer2013-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..ce988daea92558cbffcf8c943ef8039e1e9a5ec2 --- /dev/null +++ b/resnet18-fer2013-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/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_256_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet18-fer2013-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-fer2013-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-fer2013-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/model.safetensors b/resnet18-fer2013-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..070df4216103afdefe8a56c4b55ecdd6a3ea7c57 --- /dev/null +++ b/resnet18-fer2013-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:cce70e0bb5292101715975bd9572eef6638e646b749129f83925c88d25b7a12b +size 44774596 diff --git a/resnet18-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/README.md b/resnet18-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..76ae4b185402ef6199fb5cec90c806dbdfabdbf9 --- /dev/null +++ b/resnet18-fer2013-batch_size_64_lr_0.001_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: 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: 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_0.001_training_data_ratio_0.5-2000/config.json b/resnet18-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..ce988daea92558cbffcf8c943ef8039e1e9a5ec2 --- /dev/null +++ b/resnet18-fer2013-batch_size_64_lr_0.001_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_64_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet18-fer2013-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/resnet18-fer2013-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/resnet18-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/model.safetensors b/resnet18-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..b1a638bb4abb8da852b51a374386fe28236bf218 --- /dev/null +++ b/resnet18-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3d841ccff6732652168f9fedc683d7123582b390f3efd38b3314a512b42caae0 +size 44774596 diff --git a/resnet18-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/README.md b/resnet18-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..76ae4b185402ef6199fb5cec90c806dbdfabdbf9 --- /dev/null +++ b/resnet18-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/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: 0.001 + 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_64_lr_0.001_training_data_ratio_0.5-4000/config.json b/resnet18-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..ce988daea92558cbffcf8c943ef8039e1e9a5ec2 --- /dev/null +++ b/resnet18-fer2013-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/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_0.001_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet18-fer2013-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-fer2013-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-fer2013-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/README.md b/resnet18-fer2013-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..85fbd7f3a9c3294db12c949fd218582c9bb398ae --- /dev/null +++ b/resnet18-fer2013-batch_size_64_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: 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: 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_0.5-2000/config.json b/resnet18-fer2013-batch_size_64_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_64_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_64_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet18-fer2013-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-fer2013-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_64_lr_0.01_training_data_ratio_1.0-4000/model.safetensors b/resnet18-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..7e00b59ca30f0ac288af035daee0a96654f690e3 --- /dev/null +++ b/resnet18-fer2013-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e464ab2d8183bdd3f0db438fd09f4ba26be40e06dbde5c66bdca85c83b885aeb +size 44774596 diff --git a/resnet18-food101-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/README.md b/resnet18-food101-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..c23df13fcac055112a7e991978d46d1e77c79b55 --- /dev/null +++ b/resnet18-food101-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 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: 0.01 + 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: 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_0.01_training_data_ratio_0.8-4000/config.json b/resnet18-food101-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..2bba7874d0acf5076869a6fd62eb0fbe2d2041dc --- /dev/null +++ b/resnet18-food101-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/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_0.01_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet18-food101-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-food101-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-food101-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/README.md b/resnet18-food101-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..47d9c9afc5c4b7db5dc643b52724f432349dc633 --- /dev/null +++ b/resnet18-food101-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 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: 0.001 + 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_256_lr_0.001_training_data_ratio_0.8-2000/config.json b/resnet18-food101-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..2bba7874d0acf5076869a6fd62eb0fbe2d2041dc --- /dev/null +++ b/resnet18-food101-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/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, + 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b/resnet18-gtsrb-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 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_1.0-3000/config.json b/resnet18-gtsrb-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..62569c7f31f507ee6f3882e2441b38c75ccc59f3 --- /dev/null +++ b/resnet18-gtsrb-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/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_0.005_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet18-gtsrb-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-gtsrb-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-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/README.md b/resnet18-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..4a9620883123aac01576429de1a508810a3f7425 --- /dev/null +++ b/resnet18-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/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 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_0.5-4000/config.json b/resnet18-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..62569c7f31f507ee6f3882e2441b38c75ccc59f3 --- /dev/null +++ b/resnet18-gtsrb-batch_size_256_lr_0.01_training_data_ratio_0.5-4000/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_0.5-4000/preprocessor_config.json b/resnet18-gtsrb-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-gtsrb-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-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/README.md b/resnet18-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..281e1a9841948613831de41f6bbd888e177e67a7 --- /dev/null +++ b/resnet18-gtsrb-batch_size_64_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 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: 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_64_lr_0.001_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet18-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/resnet18-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/resnet18-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/model.safetensors b/resnet18-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..4ccde8a2f5e2ce93b46864d2a6cbb29ee7fc21c8 --- /dev/null +++ b/resnet18-gtsrb-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:cb3ec516230027b072180251a5e330c4c48527dc080c9b4b10e5160424050c23 +size 44848492 diff --git a/resnet18-gtsrb-batch_size_64_lr_0.01_training_data_ratio_0.8-2000/model.safetensors b/resnet18-gtsrb-batch_size_64_lr_0.01_training_data_ratio_0.8-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..2da094a0706cd1cb5e1d56797eafed2b00375958 --- /dev/null +++ b/resnet18-gtsrb-batch_size_64_lr_0.01_training_data_ratio_0.8-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0633274a92b3d197e76e6751f61b3cf4d3bd263ba7a0c77ccf7af13201a08c06 +size 44848492 diff --git a/resnet18-kmnist-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/README.md b/resnet18-kmnist-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..5f6c2be32455a63e1e54a53d135b66a11eaff89d --- /dev/null +++ b/resnet18-kmnist-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 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: 0.8 +``` + +### 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_128_lr_0.001_training_data_ratio_0.8-4000/config.json b/resnet18-kmnist-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..54cae3827bd20f790075f990d3712f8342d20c79 --- /dev/null +++ b/resnet18-kmnist-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": "\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_128_lr_0.001_training_data_ratio_0.8-4000/preprocessor_config.json 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b/resnet18-kmnist-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4b2f84381324243c87765d170d2a031cc1be9f4a0b9fbfcd10a83c9fa992198b +size 44780752 diff --git a/resnet18-kmnist-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/model.safetensors b/resnet18-kmnist-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..d602eb12aef7e827800fea7177d3724b49601c64 --- /dev/null +++ b/resnet18-kmnist-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:332037f7d583b5f3284bf1086daef66616bae9226114c8c549413da80820abff +size 44780752 diff --git a/resnet18-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/README.md b/resnet18-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..e4e54f1a5cf09e5e6e9b74bbe72efe3543140a3e --- /dev/null +++ b/resnet18-kmnist-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 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: 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: 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_0.5-4000/config.json b/resnet18-kmnist-batch_size_256_lr_0.001_training_data_ratio_0.5-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..54cae3827bd20f790075f990d3712f8342d20c79 --- /dev/null +++ b/resnet18-kmnist-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": "\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_0.5-4000/preprocessor_config.json b/resnet18-kmnist-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-kmnist-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-kmnist-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/README.md b/resnet18-kmnist-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..c3152d6411281ee09f19ec98d36ef662ad1dff2c --- /dev/null +++ b/resnet18-kmnist-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 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: 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: 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_0.5-4000/config.json b/resnet18-kmnist-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..54cae3827bd20f790075f990d3712f8342d20c79 --- /dev/null +++ b/resnet18-kmnist-batch_size_256_lr_0.005_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": "\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_0.5-4000/preprocessor_config.json b/resnet18-kmnist-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-kmnist-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-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/README.md b/resnet18-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..ef327c06f079cea18eb1714db33703de15e4ac94 --- /dev/null +++ b/resnet18-kmnist-batch_size_64_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 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: 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: 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_0.001_training_data_ratio_0.5-2000/config.json b/resnet18-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..54cae3827bd20f790075f990d3712f8342d20c79 --- /dev/null +++ b/resnet18-kmnist-batch_size_64_lr_0.001_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": "\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_0.001_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet18-kmnist-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/resnet18-kmnist-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/resnet18-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/model.safetensors b/resnet18-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..2ed3eee788c7722ff5e7adc3acec3cd46502fbcb --- /dev/null +++ b/resnet18-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ec399cd8a5c4abbf6e0e46213c407ca3cca4266397f8b5243602b102de3aeb2c +size 44780752 diff --git a/resnet18-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/README.md b/resnet18-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..ed3acfb6e3ce4d63891443d23fae46771cfb13ec --- /dev/null +++ b/resnet18-kmnist-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 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-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_0.001_training_data_ratio_0.8-3000/config.json b/resnet18-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.8-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..54cae3827bd20f790075f990d3712f8342d20c79 --- /dev/null +++ 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b/resnet18-mnist-batch_size_64_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 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: 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: 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_64_lr_0.01_training_data_ratio_0.8-2000/config.json b/resnet18-mnist-batch_size_64_lr_0.01_training_data_ratio_0.8-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..018e7d4d1ef4a7995d309411e18d7bc5d8d5f4a9 --- /dev/null +++ b/resnet18-mnist-batch_size_64_lr_0.01_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-mnist-batch_size_64_lr_0.01_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet18-mnist-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/resnet18-mnist-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/resnet18-mnist-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/README.md b/resnet18-mnist-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..dd34ed29eb76e7db23fe3658f5c672785468de22 --- /dev/null +++ b/resnet18-mnist-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 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: 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: 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_64_lr_0.01_training_data_ratio_0.8-4000/config.json b/resnet18-mnist-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..018e7d4d1ef4a7995d309411e18d7bc5d8d5f4a9 --- /dev/null +++ b/resnet18-mnist-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": "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_64_lr_0.01_training_data_ratio_0.8-4000/preprocessor_config.json 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b/resnet18-oxford-iiit-pet-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..eaa81a98628fc6cbf3dbfbd58054a4a5a94abeec --- /dev/null +++ b/resnet18-oxford-iiit-pet-batch_size_128_lr_0.001_training_data_ratio_0.5-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c63abd4b2fab09bf62381169c3b247339a0bebe602b2938bf0ca19688d53929c +size 44836180 diff --git a/resnet18-oxford-iiit-pet-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/README.md b/resnet18-oxford-iiit-pet-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..b0762e73785628bf6c45265a51d7f6320cb08bb2 --- /dev/null +++ b/resnet18-oxford-iiit-pet-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 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: 0.8 +``` + +### 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_128_lr_0.001_training_data_ratio_0.8-4000/config.json b/resnet18-oxford-iiit-pet-batch_size_128_lr_0.001_training_data_ratio_0.8-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..fd54d9408eb0bfa96cb8fb062f40297ff8e043a3 --- /dev/null +++ b/resnet18-oxford-iiit-pet-batch_size_128_lr_0.001_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_128_lr_0.001_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet18-oxford-iiit-pet-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-oxford-iiit-pet-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-oxford-iiit-pet-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/model.safetensors b/resnet18-oxford-iiit-pet-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..2a7646f93debbf508c4d47d02dd4f75c269b2da1 --- /dev/null +++ b/resnet18-oxford-iiit-pet-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a92f82b8650acda6433d038aa3cc14aa142c41ea18be065abcf82c4a195d0824 +size 44836180 diff --git a/resnet18-oxford-iiit-pet-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/README.md b/resnet18-oxford-iiit-pet-batch_size_128_lr_0.005_training_data_ratio_1.0-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..bcb9cfb54073d2a3c62a737dce4ef0c1fb1e2eb5 --- /dev/null +++ b/resnet18-oxford-iiit-pet-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 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: 0.005 + 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_128_lr_0.005_training_data_ratio_1.0-3000/config.json b/resnet18-oxford-iiit-pet-batch_size_128_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_128_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_128_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet18-oxford-iiit-pet-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-oxford-iiit-pet-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 + ], + 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mode 100644 index 0000000000000000000000000000000000000000..19a2d2a6ea5b9f18f34b8112f6c71e942299435f --- /dev/null +++ b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a306197fac6b2ff3d8998b2ea3662b11d205de8c6fa4ca44c205ac5161fa1b92 +size 44836180 diff --git a/resnet18-oxford-iiit-pet-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/model.safetensors b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..824670bfce6cc7023da0b0a1df9ca5eb45c40e21 --- /dev/null +++ b/resnet18-oxford-iiit-pet-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f5dc683a1daf15b2843bb106bb38836e578ae977e5b7ccd2255182c56a8c4541 +size 44836180 diff --git a/resnet18-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/README.md b/resnet18-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..832033bf011d770a1e385af57d807aae68caa5ff --- /dev/null +++ b/resnet18-oxford-iiit-pet-batch_size_64_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 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: 0.8 +``` + +### 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_64_lr_0.005_training_data_ratio_0.8-4000/config.json b/resnet18-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/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_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_64_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet18-oxford-iiit-pet-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-oxford-iiit-pet-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-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/model.safetensors b/resnet18-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..2c47d2589fd092239c342413bbefb7d7474be6f9 --- /dev/null +++ b/resnet18-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ac12a1f352b548e8d7075b31921efa3fb5d1fb3f4883c0b35368ba7752cb648b +size 44969560 diff --git a/resnet18-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/README.md b/resnet18-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..5e2a657ca9ac956b373c378c14e9aa0d446236ff --- /dev/null +++ b/resnet18-oxford_flowers102-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 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: 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_0.001_training_data_ratio_1.0-1000/config.json b/resnet18-oxford_flowers102-batch_size_128_lr_0.001_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_0.001_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_0.001_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet18-oxford_flowers102-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-oxford_flowers102-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-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/model.safetensors b/resnet18-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..7e498db90087aaaf52a216602c548fafed617685 --- /dev/null +++ b/resnet18-oxford_flowers102-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e8e7e5ad0e4c32db1fca67378abe8d3e9f83c5e3228fbbf2bab79f2afbd6bd4c +size 44969560 diff --git a/resnet18-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/model.safetensors b/resnet18-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..ffc1085d2a78681dbd01083cd15e0a79b8dd5528 --- /dev/null +++ b/resnet18-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c60be1c17b3a738d07d6afaf39192569af4cd72dd6cdf9175235c1ae03482efb +size 44969560 diff --git a/resnet18-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/README.md b/resnet18-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..c7b6fc32619e14d18178596629d8e8e0315c576b --- /dev/null +++ b/resnet18-oxford_flowers102-batch_size_256_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 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: 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_256_lr_0.001_training_data_ratio_0.8-3000/config.json b/resnet18-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..f938618d830ad3512a63af4ea0f8ca5e6b26a242 --- /dev/null +++ b/resnet18-oxford_flowers102-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/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_256_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet18-oxford_flowers102-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/resnet18-oxford_flowers102-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/resnet18-oxford_flowers102-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/README.md b/resnet18-oxford_flowers102-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..77bd689e0f2ac41eac2c231f7aeef5f5b507f7b5 --- /dev/null +++ b/resnet18-oxford_flowers102-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 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: 0.01 + 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: 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_0.01_training_data_ratio_0.5-2000/config.json b/resnet18-oxford_flowers102-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..f938618d830ad3512a63af4ea0f8ca5e6b26a242 --- /dev/null +++ b/resnet18-oxford_flowers102-batch_size_256_lr_0.01_training_data_ratio_0.5-2000/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_0.01_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet18-oxford_flowers102-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-oxford_flowers102-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, + 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b/resnet18-oxford_flowers102-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..fe3c63225502d15cd8b2cfdc327a1086ce1234b1 --- /dev/null +++ b/resnet18-oxford_flowers102-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b11837144128a11d20c3c647df77e3649cbaaab7876af201fd625d769f949745 +size 44969560 diff --git a/resnet18-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/README.md b/resnet18-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..d2862d5c9c295b9a17d92f0df1e926e0889b4f81 --- /dev/null +++ b/resnet18-oxford_flowers102-batch_size_64_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 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-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_0.005_training_data_ratio_0.8-4000/config.json b/resnet18-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..f938618d830ad3512a63af4ea0f8ca5e6b26a242 --- /dev/null +++ b/resnet18-oxford_flowers102-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/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_64_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet18-oxford_flowers102-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-oxford_flowers102-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-oxford_flowers102-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/model.safetensors b/resnet18-oxford_flowers102-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..8e186c07a81c9e8e048227ea6244a282207f5ffb --- /dev/null +++ b/resnet18-oxford_flowers102-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:873f1b931cd18df44cde353569d32e676db3d864e8a1ca67c7676b8986ecbb09 +size 44969560 diff --git a/resnet18-pcam-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/model.safetensors b/resnet18-pcam-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..654aed1cde6a2389dddd510a8ed62256158ee9b0 --- /dev/null +++ b/resnet18-pcam-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6b073e6740030040fb9dc2edcae548e192ae1db2c5e2b35486fd3ae766622d8a +size 44764336 diff --git a/resnet18-pcam-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/README.md b/resnet18-pcam-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..16933ce77bbf376a7455a958ca0e48cca666b89c --- /dev/null +++ b/resnet18-pcam-batch_size_128_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 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-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_0.01_training_data_ratio_0.8-2000/config.json b/resnet18-pcam-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..af7ef4427b07ea4c1e108606639855234dfa1a8d --- /dev/null +++ b/resnet18-pcam-batch_size_128_lr_0.01_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": "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_0.01_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet18-pcam-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/resnet18-pcam-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/resnet18-pcam-batch_size_256_lr_0.01_training_data_ratio_0.8-1000/config.json b/resnet18-pcam-batch_size_256_lr_0.01_training_data_ratio_0.8-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..af7ef4427b07ea4c1e108606639855234dfa1a8d --- /dev/null +++ b/resnet18-pcam-batch_size_256_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": "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_0.8-1000/preprocessor_config.json b/resnet18-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/resnet18-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/resnet18-pcam-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/model.safetensors b/resnet18-pcam-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..13f5401645537dac8bc60b002aeb931136293fb8 --- /dev/null +++ b/resnet18-pcam-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:19eee6f8866ac110146d16ff03077dd7a177daeec148117a05a975b103831837 +size 44764336 diff --git a/resnet18-pcam-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/model.safetensors b/resnet18-pcam-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..cc98ed8d621e4d8355b05e8456f414701811555c --- /dev/null +++ b/resnet18-pcam-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a664e10f3c9476401a6d7cb716bbb0b6453a882b51b28cfc95cb1b7301547c83 +size 44764336 diff --git a/resnet18-pcam-batch_size_64_lr_0.01_training_data_ratio_0.5-1000/README.md b/resnet18-pcam-batch_size_64_lr_0.01_training_data_ratio_0.5-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..189d40cc545fb149c408ee6a90be3fa741ed86bb --- /dev/null +++ b/resnet18-pcam-batch_size_64_lr_0.01_training_data_ratio_0.5-1000/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: 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_0.5-1000/config.json b/resnet18-pcam-batch_size_64_lr_0.01_training_data_ratio_0.5-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..af7ef4427b07ea4c1e108606639855234dfa1a8d --- /dev/null +++ b/resnet18-pcam-batch_size_64_lr_0.01_training_data_ratio_0.5-1000/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_64_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet18-pcam-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/resnet18-pcam-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/resnet18-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.5-1000/README.md b/resnet18-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.5-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..b1f6e2569481bd78f9f619ea8b93e4117006baea --- /dev/null +++ b/resnet18-rendered-sst2-batch_size_128_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 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-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_0.001_training_data_ratio_0.5-1000/config.json b/resnet18-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.5-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..7de77b1b23edcbdb1f59b2b21726aa56f03fbfdb --- /dev/null +++ b/resnet18-rendered-sst2-batch_size_128_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": "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_0.001_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet18-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json new file mode 100644 index 0000000000000000000000000000000000000000..8228c2b6b7368920da26fa97ecf6b616791fd03d --- /dev/null +++ b/resnet18-rendered-sst2-batch_size_128_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-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/README.md b/resnet18-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..b1f6e2569481bd78f9f619ea8b93e4117006baea --- /dev/null +++ b/resnet18-rendered-sst2-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 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-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_0.001_training_data_ratio_0.5-2000/config.json b/resnet18-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..7de77b1b23edcbdb1f59b2b21726aa56f03fbfdb --- /dev/null +++ b/resnet18-rendered-sst2-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": "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_0.001_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet18-rendered-sst2-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-rendered-sst2-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-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/README.md b/resnet18-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..1e5be97e60f092380f64574b9b682c1be685a434 --- /dev/null +++ b/resnet18-rendered-sst2-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 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-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_0.001_training_data_ratio_1.0-4000/config.json b/resnet18-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..7de77b1b23edcbdb1f59b2b21726aa56f03fbfdb --- /dev/null +++ b/resnet18-rendered-sst2-batch_size_128_lr_0.001_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": "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_0.001_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet18-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/resnet18-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 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-0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e315957f06c3e7b0f87bb632b8741b92ec1def16fd99fee4290957007c378ce6 +size 44764336 diff --git a/resnet18-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/model.safetensors b/resnet18-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..5247cc13a9648ff6a50d5fc6fdbd7168c1fb690c --- /dev/null +++ b/resnet18-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_0.8-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b45ccadc2e8d3cfe20eb2cc6affa54ae8486a9b53d2ee0b682d4c936650d4f72 +size 44764336 diff --git a/resnet18-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/model.safetensors b/resnet18-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..8307feb0649734acfe7518fadd9fd01e58c24ce1 --- /dev/null +++ b/resnet18-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:cea3ad88046856b8d6650a483f68d4cac5ce563186d71f681d8cf421a1307705 +size 44764336 diff --git a/resnet18-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/README.md b/resnet18-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..3c1d10803dbcd8b8bab918837103290abad1d4b7 --- /dev/null +++ b/resnet18-rendered-sst2-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 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-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_1.0-2000/config.json b/resnet18-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..7de77b1b23edcbdb1f59b2b21726aa56f03fbfdb --- /dev/null +++ b/resnet18-rendered-sst2-batch_size_128_lr_0.005_training_data_ratio_1.0-2000/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_128_lr_0.005_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet18-rendered-sst2-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-rendered-sst2-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-rendered-sst2-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/README.md b/resnet18-rendered-sst2-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..31f73042c5c30b82c7a58af5e0e93d38a03ddb5b --- /dev/null +++ b/resnet18-rendered-sst2-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 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-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_1.0-2000/config.json b/resnet18-rendered-sst2-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..7de77b1b23edcbdb1f59b2b21726aa56f03fbfdb --- /dev/null +++ b/resnet18-rendered-sst2-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/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_128_lr_0.01_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet18-rendered-sst2-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-rendered-sst2-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-rendered-sst2-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/README.md b/resnet18-rendered-sst2-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..a6e9cc5e0d27e15d041d136482b5b5cc0595e39b --- /dev/null +++ b/resnet18-rendered-sst2-batch_size_256_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 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-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_0.001_training_data_ratio_0.8-4000/config.json b/resnet18-rendered-sst2-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..7de77b1b23edcbdb1f59b2b21726aa56f03fbfdb --- /dev/null +++ b/resnet18-rendered-sst2-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/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_256_lr_0.001_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet18-rendered-sst2-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/resnet18-rendered-sst2-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/resnet18-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/model.safetensors b/resnet18-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..90210f9a78bf7f2ec6b69387e508e283b7f3cf9a --- /dev/null +++ b/resnet18-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:9f9ce612ce967fc86021aa7c8280a364b1258aab2c8c5e81b52f8a4509d610ae +size 44764336 diff --git a/resnet18-rendered-sst2-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/model.safetensors b/resnet18-rendered-sst2-batch_size_256_lr_0.01_training_data_ratio_0.5-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..670a467909a824d75127c82499e160debeb5aa62 --- /dev/null +++ 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sha256:0bb0e73ae4f990d019f28d1e01171e0ceb9b21db0a01ae203995ab6f5f916ddc +size 44852596 diff --git a/resnet18-resisc45-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/README.md b/resnet18-resisc45-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..b33df0dc89e37a93dcc2eb045148cd06a627d941 --- /dev/null +++ b/resnet18-resisc45-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 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-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_0.001_training_data_ratio_0.5-3000/config.json b/resnet18-resisc45-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..92840a13704fe0d58f3cc8774361fed5e980dc70 --- /dev/null +++ b/resnet18-resisc45-batch_size_256_lr_0.001_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_256_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet18-resisc45-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-resisc45-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-resisc45-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/model.safetensors b/resnet18-resisc45-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..b51e224498a169bc5e1684c0ce986b4514317a6e --- /dev/null +++ b/resnet18-resisc45-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6a58423c1559b85ad2e77c5776ef1e3f05b426491205cb2617b0ee06173b1104 +size 44852596 diff --git a/resnet18-resisc45-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/README.md b/resnet18-resisc45-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..0caaa2cf421225e3a9a6b24955d9a158e7a108dd --- /dev/null +++ b/resnet18-resisc45-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 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: 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_0.005_training_data_ratio_1.0-2000/config.json b/resnet18-resisc45-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..92840a13704fe0d58f3cc8774361fed5e980dc70 --- /dev/null +++ b/resnet18-resisc45-batch_size_256_lr_0.005_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_256_lr_0.005_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet18-resisc45-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-resisc45-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-resisc45-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/README.md b/resnet18-resisc45-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..38b08b5b03851358e20c81e804c4271dbf09ef0b --- /dev/null +++ b/resnet18-resisc45-batch_size_64_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 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: 0.001 + 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: 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_0.001_training_data_ratio_0.8-2000/config.json b/resnet18-resisc45-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..92840a13704fe0d58f3cc8774361fed5e980dc70 --- /dev/null +++ b/resnet18-resisc45-batch_size_64_lr_0.001_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_64_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet18-resisc45-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/resnet18-resisc45-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/resnet18-resisc45-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/model.safetensors b/resnet18-resisc45-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..5c6e6c5a11b1d0bd2d9ca8f999b5ab3f9191bcd7 --- /dev/null +++ b/resnet18-resisc45-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0ffdb4e2489805a8a7dd18a58aa74050f47de9db52e270ac22de1af1e5cc323b +size 44852596 diff --git a/resnet18-resisc45-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/README.md b/resnet18-resisc45-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..6d613130e429d57d862e265f740cf6dc399b969c --- /dev/null +++ b/resnet18-resisc45-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/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: 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_0.8-2000/config.json b/resnet18-resisc45-batch_size_64_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_64_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_64_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet18-resisc45-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-resisc45-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-resisc45-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/model.safetensors 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b/resnet18-stanford-cars-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 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: 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_256_lr_0.005_training_data_ratio_1.0-2000/config.json b/resnet18-stanford-cars-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..ea904dca37c3e1bd676cdab8c844dff369a4e286 --- /dev/null +++ b/resnet18-stanford-cars-batch_size_256_lr_0.005_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 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0000000000000000000000000000000000000000..faa6300b256bcd3a3df2fb589a07019edac9c699 --- /dev/null +++ b/resnet18-stanford-cars-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 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: 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_256_lr_0.01_training_data_ratio_1.0-4000/config.json b/resnet18-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..ea904dca37c3e1bd676cdab8c844dff369a4e286 --- /dev/null +++ b/resnet18-stanford-cars-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/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": 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"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 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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_1.0-4000/preprocessor_config.json b/resnet18-stanford-cars-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-stanford-cars-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-stanford-cars-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/README.md b/resnet18-stanford-cars-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..e59b423bd71cab854dfd2697624e846dc46423ce --- /dev/null +++ b/resnet18-stanford-cars-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 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: 0.8 +``` + +### 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_64_lr_0.005_training_data_ratio_0.8-2000/config.json b/resnet18-stanford-cars-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..ea904dca37c3e1bd676cdab8c844dff369a4e286 --- /dev/null +++ b/resnet18-stanford-cars-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/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 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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_0.8-2000/preprocessor_config.json b/resnet18-stanford-cars-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-stanford-cars-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-stl10-batch_size_128_lr_0.005_training_data_ratio_0.5-4000/README.md b/resnet18-stl10-batch_size_128_lr_0.005_training_data_ratio_0.5-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..69d168b7386525caee0119068aae575b49ddc58b --- /dev/null +++ b/resnet18-stl10-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 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: 0.5 +``` + +### 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_128_lr_0.005_training_data_ratio_0.5-4000/config.json b/resnet18-stl10-batch_size_128_lr_0.005_training_data_ratio_0.5-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..29c93b2c12685a5b5caf379e93026d934c412298 --- /dev/null +++ b/resnet18-stl10-batch_size_128_lr_0.005_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": "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_0.5-4000/preprocessor_config.json b/resnet18-stl10-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-stl10-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-stl10-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/model.safetensors b/resnet18-stl10-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..72ab0a44abe2be60baca82763538a70102baec8b --- /dev/null +++ b/resnet18-stl10-batch_size_128_lr_0.005_training_data_ratio_1.0-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:facc56458a2dc5ea195ab610269b6cca7175382b4c459d993248427c700aa651 +size 44780752 diff --git a/resnet18-stl10-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/README.md b/resnet18-stl10-batch_size_128_lr_0.01_training_data_ratio_0.5-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..2fb28fea3bc03906cb93e673df1651695bba7cb1 --- /dev/null +++ b/resnet18-stl10-batch_size_128_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: 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: 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_0.01_training_data_ratio_0.5-2000/config.json b/resnet18-stl10-batch_size_128_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_128_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_128_lr_0.01_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet18-stl10-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/resnet18-stl10-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/resnet18-stl10-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/README.md b/resnet18-stl10-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..2fb28fea3bc03906cb93e673df1651695bba7cb1 --- /dev/null +++ b/resnet18-stl10-batch_size_128_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 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: 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_128_lr_0.01_training_data_ratio_0.5-4000/config.json b/resnet18-stl10-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..29c93b2c12685a5b5caf379e93026d934c412298 --- /dev/null +++ b/resnet18-stl10-batch_size_128_lr_0.01_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": "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_0.01_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet18-stl10-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/resnet18-stl10-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/resnet18-stl10-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/model.safetensors b/resnet18-stl10-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..95caf17acd5b3d821e820518a3fbd869ca57eda0 --- /dev/null +++ b/resnet18-stl10-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f4598c860e7c0116e460c4ff26ba47a3cfdd89e8ca3135d47abecf994a07d69b +size 44780752 diff --git a/resnet18-stl10-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/README.md b/resnet18-stl10-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..422ed57685e10fd2cdab815e8ab3057dd4a31645 --- /dev/null +++ b/resnet18-stl10-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 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: 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_0.01_training_data_ratio_0.8-3000/config.json b/resnet18-stl10-batch_size_128_lr_0.01_training_data_ratio_0.8-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..29c93b2c12685a5b5caf379e93026d934c412298 --- /dev/null +++ b/resnet18-stl10-batch_size_128_lr_0.01_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": "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_0.01_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet18-stl10-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-stl10-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-stl10-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/model.safetensors b/resnet18-stl10-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..2d9b1ff342c8a8d32a1542b8ce14a3f316beb5d8 --- /dev/null +++ b/resnet18-stl10-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6f2f56c366121f43abb589f969352c13b1ce590255dfe30d82332809aa2b2680 +size 44780752 diff --git a/resnet18-stl10-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/README.md b/resnet18-stl10-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..a612f76d163793205d0652175889a50f5295a173 --- /dev/null +++ b/resnet18-stl10-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 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-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_0.01_training_data_ratio_1.0-3000/config.json b/resnet18-stl10-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..29c93b2c12685a5b5caf379e93026d934c412298 --- /dev/null +++ b/resnet18-stl10-batch_size_128_lr_0.01_training_data_ratio_1.0-3000/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_0.01_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet18-stl10-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-stl10-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-stl10-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/README.md b/resnet18-stl10-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..ecbfed179a19b814a67b33837821f9aa867fc1ec --- /dev/null +++ b/resnet18-stl10-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 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: 0.001 + 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: 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_0.001_training_data_ratio_0.5-1000/config.json b/resnet18-stl10-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..29c93b2c12685a5b5caf379e93026d934c412298 --- /dev/null +++ b/resnet18-stl10-batch_size_256_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": "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_0.001_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet18-stl10-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-stl10-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-stl10-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/README.md b/resnet18-stl10-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..ecbfed179a19b814a67b33837821f9aa867fc1ec --- /dev/null +++ b/resnet18-stl10-batch_size_256_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 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: 0.001 + 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: 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_0.001_training_data_ratio_0.5-2000/config.json b/resnet18-stl10-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..29c93b2c12685a5b5caf379e93026d934c412298 --- /dev/null +++ b/resnet18-stl10-batch_size_256_lr_0.001_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_0.001_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet18-stl10-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/resnet18-stl10-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/resnet18-stl10-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/model.safetensors 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+size 44780752 diff --git a/resnet18-stl10-batch_size_256_lr_0.001_training_data_ratio_1.0-1000/model.safetensors b/resnet18-stl10-batch_size_256_lr_0.001_training_data_ratio_1.0-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..3901a3ebb92fc4eef74e699334d0bef8ffbcaf14 --- /dev/null +++ b/resnet18-stl10-batch_size_256_lr_0.001_training_data_ratio_1.0-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:99c0f9791a17c9233bec83b7e020ad81798a7c20cc4f211d223539162b2e9b65 +size 44780752 diff --git a/resnet18-stl10-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/README.md b/resnet18-stl10-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..d5ad0614d5ea5a49d8ca85752197bba1d64d8a85 --- /dev/null +++ b/resnet18-stl10-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 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: 0.5 +``` + +### 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_0.005_training_data_ratio_0.5-2000/config.json b/resnet18-stl10-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..29c93b2c12685a5b5caf379e93026d934c412298 --- /dev/null +++ b/resnet18-stl10-batch_size_256_lr_0.005_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": "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_0.5-2000/preprocessor_config.json b/resnet18-stl10-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-stl10-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-stl10-batch_size_256_lr_0.005_training_data_ratio_0.5-3000/README.md b/resnet18-stl10-batch_size_256_lr_0.005_training_data_ratio_0.5-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..d5ad0614d5ea5a49d8ca85752197bba1d64d8a85 --- /dev/null +++ b/resnet18-stl10-batch_size_256_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 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: 0.5 +``` + +### 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_0.005_training_data_ratio_0.5-3000/config.json b/resnet18-stl10-batch_size_256_lr_0.005_training_data_ratio_0.5-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..29c93b2c12685a5b5caf379e93026d934c412298 --- /dev/null +++ b/resnet18-stl10-batch_size_256_lr_0.005_training_data_ratio_0.5-3000/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": "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_0.5-3000/preprocessor_config.json b/resnet18-stl10-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/resnet18-stl10-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/resnet18-stl10-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/model.safetensors b/resnet18-stl10-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..ef2e3191835fc4fcc967d7ca55b201885afe0159 --- /dev/null +++ b/resnet18-stl10-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:fdf96915db876059dec395b97963b8c4e1d8cf37b25b7748b9b2b5a359b3f756 +size 44780752 diff --git a/resnet18-stl10-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/README.md b/resnet18-stl10-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..5ec8010f3e2669c0054d724a781ab82e7103513a --- /dev/null +++ b/resnet18-stl10-batch_size_64_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 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-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_0.001_training_data_ratio_0.5-1000/config.json b/resnet18-stl10-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..29c93b2c12685a5b5caf379e93026d934c412298 --- /dev/null +++ b/resnet18-stl10-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": "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_0.001_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet18-stl10-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-stl10-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-stl10-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/README.md b/resnet18-stl10-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..7ec06e80d3cf4d1353485b4e73fa69674cbf3bd9 --- /dev/null +++ b/resnet18-stl10-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 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: 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: 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_0.001_training_data_ratio_1.0-3000/config.json b/resnet18-stl10-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..29c93b2c12685a5b5caf379e93026d934c412298 --- /dev/null +++ b/resnet18-stl10-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/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_64_lr_0.001_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet18-stl10-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-stl10-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-sun397-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/README.md b/resnet18-sun397-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..a190f6be3f39ff91a55cfac82a40c9baa1b8e18f --- /dev/null +++ b/resnet18-sun397-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 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: 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_0.001_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet18-sun397-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-sun397-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-sun397-batch_size_128_lr_0.005_training_data_ratio_1.0-4000/model.safetensors b/resnet18-sun397-batch_size_128_lr_0.005_training_data_ratio_1.0-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..040111658e0c2996473c9516ce7f2696904af683 --- /dev/null +++ b/resnet18-sun397-batch_size_128_lr_0.005_training_data_ratio_1.0-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0dae15963a2ea038a825336fdef6aaa305e4abd2117a11467573bffe1adda255 +size 45574948 diff --git a/resnet18-sun397-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/README.md b/resnet18-sun397-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..20edde2444e951b4f42a46372b344768ae552a16 --- /dev/null +++ b/resnet18-sun397-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/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: 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_1.0-4000/config.json b/resnet18-sun397-batch_size_128_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_128_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_128_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet18-sun397-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/resnet18-sun397-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/resnet18-sun397-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/README.md b/resnet18-sun397-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..a9cb72271b19e1c577a169d581989b0c4cf17bde --- /dev/null +++ b/resnet18-sun397-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/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: 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_0.8-3000/config.json b/resnet18-sun397-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..886da3497a7114ff31c2408ec559a773285de738 --- /dev/null +++ b/resnet18-sun397-batch_size_256_lr_0.001_training_data_ratio_0.8-3000/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_256_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet18-sun397-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/resnet18-sun397-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/resnet18-sun397-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/README.md b/resnet18-sun397-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..8182009d9d1fcc2f480a73742d3bff73b55cd578 --- /dev/null +++ b/resnet18-sun397-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 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: 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_256_lr_0.001_training_data_ratio_1.0-2000/config.json b/resnet18-sun397-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..886da3497a7114ff31c2408ec559a773285de738 --- /dev/null +++ b/resnet18-sun397-batch_size_256_lr_0.001_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_256_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet18-sun397-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-sun397-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-sun397-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/README.md b/resnet18-sun397-batch_size_256_lr_0.01_training_data_ratio_1.0-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..bd83e632c18c7ab3b74e8c1fdff8a5ab676ad1ec --- /dev/null +++ b/resnet18-sun397-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 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: 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_256_lr_0.01_training_data_ratio_1.0-1000/config.json b/resnet18-sun397-batch_size_256_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_256_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_256_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet18-sun397-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-sun397-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-sun397-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/model.safetensors b/resnet18-sun397-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..b9412a152d84886d6c21613525f5aa8f11e2164c --- /dev/null +++ b/resnet18-sun397-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ba7b7c160ff6a02d6d717546d1ba8271455390898cac68ef2e35ecc6f9a9da99 +size 45574948 diff --git a/resnet18-sun397-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/README.md b/resnet18-sun397-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..f3391716cb2e82edc04c7ba7c04e716e18b15e23 --- /dev/null +++ b/resnet18-sun397-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 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-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_0.001_training_data_ratio_0.5-4000/config.json b/resnet18-sun397-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..886da3497a7114ff31c2408ec559a773285de738 --- /dev/null +++ b/resnet18-sun397-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/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_0.001_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet18-sun397-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-sun397-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-sun397-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/model.safetensors b/resnet18-sun397-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..1427b57fd364297d0cfef048d9d155bcd22b0678 --- /dev/null +++ b/resnet18-sun397-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:bc3ba8e12980cc839573ef2ba3eda48eda8ed3ffbbcb4afa93bc2acd9b6575b4 +size 45574948 diff --git a/resnet18-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/README.md b/resnet18-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..59f2b1ef6e869917954ab70e99b757e8490e1487 --- /dev/null +++ b/resnet18-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/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: 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_1.0-3000/config.json b/resnet18-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..886da3497a7114ff31c2408ec559a773285de738 --- /dev/null +++ b/resnet18-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/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 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+ "stem", + "stage1", + "stage2", + "stage3", + "stage4" + ], + "transformers_version": "4.56.1" +} diff --git a/resnet18-sun397-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet18-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/resnet18-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/resnet18-svhn-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/model.safetensors 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44780752 diff --git a/resnet18-svhn-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/README.md b/resnet18-svhn-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..98b7661a35a40b4010c04020d1a2f79e05607422 --- /dev/null +++ b/resnet18-svhn-batch_size_256_lr_0.001_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: 0.001 + 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: 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_0.001_training_data_ratio_0.8-2000/config.json b/resnet18-svhn-batch_size_256_lr_0.001_training_data_ratio_0.8-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..018e7d4d1ef4a7995d309411e18d7bc5d8d5f4a9 --- /dev/null +++ b/resnet18-svhn-batch_size_256_lr_0.001_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": "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_0.001_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet18-svhn-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-svhn-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-svhn-batch_size_256_lr_0.001_training_data_ratio_1.0-1000/model.safetensors b/resnet18-svhn-batch_size_256_lr_0.001_training_data_ratio_1.0-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..8185aa8ba507e4fb9fad7a4b4b0df382d77bc9bc --- /dev/null +++ b/resnet18-svhn-batch_size_256_lr_0.001_training_data_ratio_1.0-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:058c0f9b240d75231582496ec7d788c9d28329b87c724e3bab6b3e10d4533bf5 +size 44780752 diff --git a/resnet18-svhn-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/model.safetensors b/resnet18-svhn-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..a3b21c29fdf11b16f293ac886ad6f2786356bbb6 --- /dev/null +++ b/resnet18-svhn-batch_size_256_lr_0.001_training_data_ratio_1.0-2000/model.safetensors @@ -0,0 +1,3 @@ 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b/resnet18-svhn-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/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: 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_0.5-2000/config.json b/resnet18-svhn-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..018e7d4d1ef4a7995d309411e18d7bc5d8d5f4a9 --- /dev/null +++ b/resnet18-svhn-batch_size_64_lr_0.001_training_data_ratio_0.5-2000/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 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b/resnet50-cifar10-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 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: 0.005 + 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: 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_0.005_training_data_ratio_0.5-1000/config.json b/resnet50-cifar10-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..3c885e0d0eac58ee224a40f544b024413974088f --- /dev/null +++ b/resnet50-cifar10-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": "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_0.005_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet50-cifar10-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-cifar10-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-cifar10-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/model.safetensors b/resnet50-cifar10-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..a5b2bb38b5468f3cfc5e16b4766126f6a87ace70 --- /dev/null +++ b/resnet50-cifar10-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e9e321b14c9da157146030f97c0a5e2b2f9c955e2936ed6989f4089322a1b3d9 +size 94368544 diff --git a/resnet50-cifar10-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/README.md b/resnet50-cifar10-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..5a8eeb80221d8fe99c6d02a198995d3cee36b8ce --- /dev/null +++ b/resnet50-cifar10-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 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: 0.005 + 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_256_lr_0.005_training_data_ratio_1.0-4000/config.json b/resnet50-cifar10-batch_size_256_lr_0.005_training_data_ratio_1.0-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..3c885e0d0eac58ee224a40f544b024413974088f --- /dev/null +++ b/resnet50-cifar10-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": "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_0.005_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet50-cifar10-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-cifar10-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-cifar10-batch_size_256_lr_0.01_training_data_ratio_0.8-3000/README.md b/resnet50-cifar10-batch_size_256_lr_0.01_training_data_ratio_0.8-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..305e6dadd068ce46d65b0a4cc929c96d6105d8f1 --- /dev/null +++ b/resnet50-cifar10-batch_size_256_lr_0.01_training_data_ratio_0.8-3000/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: 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_0.8-3000/config.json b/resnet50-cifar10-batch_size_256_lr_0.01_training_data_ratio_0.8-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..3c885e0d0eac58ee224a40f544b024413974088f --- /dev/null +++ b/resnet50-cifar10-batch_size_256_lr_0.01_training_data_ratio_0.8-3000/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_256_lr_0.01_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet50-cifar10-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/resnet50-cifar10-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/resnet50-cifar10-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/README.md b/resnet50-cifar10-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..791897941a2d0c28b659920088d6cc3706aa8e3c --- /dev/null +++ b/resnet50-cifar10-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 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: 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_64_lr_0.001_training_data_ratio_0.5-3000/config.json b/resnet50-cifar10-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..3c885e0d0eac58ee224a40f544b024413974088f --- /dev/null +++ b/resnet50-cifar10-batch_size_64_lr_0.001_training_data_ratio_0.5-3000/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_64_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet50-cifar10-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-cifar10-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-cifar10-batch_size_64_lr_0.001_training_data_ratio_0.8-1000/model.safetensors b/resnet50-cifar10-batch_size_64_lr_0.001_training_data_ratio_0.8-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..8a3527c18392fceea9f2092b2a6e4ee227b7c394 --- /dev/null +++ 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index 0000000000000000000000000000000000000000..ca41757fb547ae6f676574651225edbabbd28b18 --- /dev/null +++ b/resnet50-cifar100-batch_size_128_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 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: 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: 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_128_lr_0.001_training_data_ratio_0.8-3000/config.json b/resnet50-cifar100-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..4eba7ae9631d2b0e864ded80157f76e37582afd4 --- /dev/null +++ b/resnet50-cifar100-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/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_128_lr_0.001_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet50-cifar100-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/resnet50-cifar100-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/resnet50-cifar100-batch_size_128_lr_0.005_training_data_ratio_0.5-4000/model.safetensors b/resnet50-cifar100-batch_size_128_lr_0.005_training_data_ratio_0.5-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..b0ec8eee71cd37e78f4e59620c8204a1d4793703 --- /dev/null +++ b/resnet50-cifar100-batch_size_128_lr_0.005_training_data_ratio_0.5-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:13c69c84b2d1bd821037b08d37f7fb4ada3f27675fb30f6b23a900f3bbd4f844 +size 95106288 diff --git a/resnet50-cifar100-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/README.md b/resnet50-cifar100-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..5b827639e51c2da93c1f199d8ec597493d3532f5 --- /dev/null +++ b/resnet50-cifar100-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 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-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_128_lr_0.01_training_data_ratio_0.5-3000/config.json b/resnet50-cifar100-batch_size_128_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_128_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, + 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"out_indices": [ + 4 + ], + "stage_names": [ + "stem", + "stage1", + "stage2", + "stage3", + "stage4" + ], + "transformers_version": "4.56.1" +} diff --git a/resnet50-cifar100-batch_size_128_lr_0.01_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet50-cifar100-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-cifar100-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-cifar100-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/model.safetensors b/resnet50-cifar100-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..efe36150f30cfbb43a8b55ea33d73caedc010b2e --- /dev/null +++ b/resnet50-cifar100-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5a8fdd7921e43d9f186ce7395f09d07bc9520832cabbc3ec9aab14dc7168a5bc +size 95106288 diff --git a/resnet50-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/README.md b/resnet50-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..473c8e4d5b2c2d224ea3673a1b952a1b7f21ed5a --- /dev/null +++ b/resnet50-cifar100-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 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-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_0.001_training_data_ratio_0.8-2000/config.json b/resnet50-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..4eba7ae9631d2b0e864ded80157f76e37582afd4 --- /dev/null +++ b/resnet50-cifar100-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/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, + 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+oid sha256:4b08d065b194e86123f4a3f928191555caa76b094e7bdc47f7158c0cd0b15754 +size 94671852 diff --git a/resnet50-emnist_letters-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/README.md b/resnet50-emnist_letters-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..16da88812525c8ce89bd3d90f0563849e03461ff --- /dev/null +++ b/resnet50-emnist_letters-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 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: 0.001 + 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_256_lr_0.001_training_data_ratio_1.0-4000/config.json b/resnet50-emnist_letters-batch_size_256_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_256_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_256_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet50-emnist_letters-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-emnist_letters-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-emnist_letters-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/README.md b/resnet50-emnist_letters-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..9b17de90e42a232fe0c38cd366d7bd46a3fd069d --- /dev/null +++ b/resnet50-emnist_letters-batch_size_256_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 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: 0.005 + 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: 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_256_lr_0.005_training_data_ratio_1.0-1000/config.json b/resnet50-emnist_letters-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..9d1862748747d6d484a29b20c512dd46535c93b1 --- /dev/null +++ b/resnet50-emnist_letters-batch_size_256_lr_0.005_training_data_ratio_1.0-1000/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_256_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet50-emnist_letters-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/resnet50-emnist_letters-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": 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b/resnet50-emnist_letters-batch_size_256_lr_0.01_training_data_ratio_0.8-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d41dd31331f5c993e3371ea54178825d2a5b145a1565b7b4e6f181953ceaabe6 +size 94499704 diff --git a/resnet50-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/README.md b/resnet50-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..7cb3fa4f02cfb08d4ab2ff042b6637a839e21ee3 --- /dev/null +++ b/resnet50-emnist_letters-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 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: 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_0.005_training_data_ratio_1.0-2000/config.json b/resnet50-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..9d1862748747d6d484a29b20c512dd46535c93b1 --- /dev/null +++ b/resnet50-emnist_letters-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/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_1.0-2000/preprocessor_config.json b/resnet50-emnist_letters-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-emnist_letters-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-emnist_letters-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/README.md b/resnet50-emnist_letters-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..0af350195995ac0ce7579a1b3c792c61dd90ce6c --- /dev/null +++ b/resnet50-emnist_letters-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/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: 0.01 + 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_1.0-1000/config.json b/resnet50-emnist_letters-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..9d1862748747d6d484a29b20c512dd46535c93b1 --- /dev/null +++ b/resnet50-emnist_letters-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/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_0.01_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet50-emnist_letters-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/resnet50-emnist_letters-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/resnet50-eurosat-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/model.safetensors b/resnet50-eurosat-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..64d608d43d0a128ab5093738d661d0aadd98925d --- /dev/null +++ b/resnet50-eurosat-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:48032e889f153374d24e090e56e16bc37c3cff0a85f5800e6f86be7b1fe38d00 +size 94368544 diff --git a/resnet50-eurosat-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/README.md b/resnet50-eurosat-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..3051bc5d9329810dd35c4bba3a404aad5c802b1e --- /dev/null +++ b/resnet50-eurosat-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 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: 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: 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_0.01_training_data_ratio_0.5-4000/config.json b/resnet50-eurosat-batch_size_128_lr_0.01_training_data_ratio_0.5-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..4b8f5a722ee7ec6f4a2d02ac651ae80260967eae --- /dev/null +++ b/resnet50-eurosat-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": "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_0.01_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet50-eurosat-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-eurosat-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-eurosat-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/model.safetensors b/resnet50-eurosat-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..e1baa39b431bf1953949e7d0947ab79283e59343 --- /dev/null +++ b/resnet50-eurosat-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:93cac0b0f4dda2879abaae5b4208999ff598392023d4ffb901d7a5071ec1e618 +size 94368544 diff --git a/resnet50-eurosat-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/README.md b/resnet50-eurosat-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..34ef849ae4e5f1f964cee1f6340a78a8019ab412 --- /dev/null +++ b/resnet50-eurosat-batch_size_128_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 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: 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: 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_0.01_training_data_ratio_1.0-2000/config.json b/resnet50-eurosat-batch_size_128_lr_0.01_training_data_ratio_1.0-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..4b8f5a722ee7ec6f4a2d02ac651ae80260967eae --- /dev/null +++ b/resnet50-eurosat-batch_size_128_lr_0.01_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": "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_0.01_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet50-eurosat-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/resnet50-eurosat-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/resnet50-eurosat-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/README.md b/resnet50-eurosat-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..38db379e526a3152bf6e4867f4ebc1d5e03b0050 --- /dev/null +++ b/resnet50-eurosat-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 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: 0.001 + 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: 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_256_lr_0.001_training_data_ratio_0.5-1000/config.json b/resnet50-eurosat-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..4b8f5a722ee7ec6f4a2d02ac651ae80260967eae --- /dev/null +++ b/resnet50-eurosat-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": "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_256_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet50-eurosat-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-eurosat-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-eurosat-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/README.md b/resnet50-eurosat-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..883642f38b857c7ed7cc6a7d30f00e6a34b2b266 --- /dev/null +++ b/resnet50-eurosat-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 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: 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: 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_256_lr_0.01_training_data_ratio_1.0-2000/config.json b/resnet50-eurosat-batch_size_256_lr_0.01_training_data_ratio_1.0-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..4b8f5a722ee7ec6f4a2d02ac651ae80260967eae --- /dev/null +++ b/resnet50-eurosat-batch_size_256_lr_0.01_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": "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_256_lr_0.01_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet50-eurosat-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-eurosat-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-eurosat-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/model.safetensors b/resnet50-eurosat-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..429c7adec11621bcf7ba0ee559dc9e88c6da7010 --- /dev/null +++ b/resnet50-eurosat-batch_size_64_lr_0.001_training_data_ratio_0.5-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c114a8e9fdde6d08c312444f6a25b9645271390d1a5856c4450ab0869f83d9b6 +size 94368544 diff --git a/resnet50-eurosat-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/model.safetensors b/resnet50-eurosat-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..63aee178997c83bc0d44f0a0c63288ebc001c2cb --- /dev/null +++ b/resnet50-eurosat-batch_size_64_lr_0.001_training_data_ratio_1.0-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ba019b40ca43951c72e43262e15e8cff2a4972dd6f600254c8cd3b5484d6c95c +size 94368544 diff --git a/resnet50-eurosat-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/README.md b/resnet50-eurosat-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..4ae92c18343867154602f143c4fea7c0e630255a --- /dev/null +++ b/resnet50-eurosat-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 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-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_64_lr_0.001_training_data_ratio_1.0-2000/config.json b/resnet50-eurosat-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..4b8f5a722ee7ec6f4a2d02ac651ae80260967eae --- /dev/null +++ b/resnet50-eurosat-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": "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_64_lr_0.001_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet50-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/resnet50-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/resnet50-eurosat-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/config.json b/resnet50-eurosat-batch_size_64_lr_0.001_training_data_ratio_1.0-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..4b8f5a722ee7ec6f4a2d02ac651ae80260967eae --- /dev/null +++ b/resnet50-eurosat-batch_size_64_lr_0.001_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": "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_64_lr_0.001_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet50-eurosat-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-eurosat-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-eurosat-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/model.safetensors b/resnet50-eurosat-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..4548a941000583e35a491f5264da6e6b2d261a19 --- /dev/null +++ b/resnet50-eurosat-batch_size_64_lr_0.005_training_data_ratio_0.5-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4c943d53540c545ecee21c78749c1972ae57bfbd7d62edf5ca72d90c3653b49d +size 94368544 diff --git a/resnet50-eurosat-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/README.md b/resnet50-eurosat-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..6e28158536397a2bc7a60c6824637071c18f5ca2 --- /dev/null +++ b/resnet50-eurosat-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 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: 0.005 + 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: 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_64_lr_0.005_training_data_ratio_1.0-1000/config.json b/resnet50-eurosat-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..4b8f5a722ee7ec6f4a2d02ac651ae80260967eae --- /dev/null +++ b/resnet50-eurosat-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": "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_64_lr_0.005_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet50-eurosat-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-eurosat-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-eurosat-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/model.safetensors b/resnet50-eurosat-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..f6be5ae8e6c5969f547176924fbc3446b0fd8e7b --- /dev/null +++ b/resnet50-eurosat-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/model.safetensors @@ -0,0 +1,3 @@ +version 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b/resnet50-fashion_mnist-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 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: 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: 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_0.01_training_data_ratio_0.8-4000/config.json b/resnet50-fashion_mnist-batch_size_128_lr_0.01_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_0.01_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_0.01_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet50-fashion_mnist-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-fashion_mnist-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-fashion_mnist-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/model.safetensors 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sha256:c3f6fbce899be964713b8363a914f52409bc3b0a136a029250e8a3fd5c127fbb +size 94368544 diff --git a/resnet50-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/README.md b/resnet50-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..d85bca6d2d74898595fb87169bd86c59e845dc5c --- /dev/null +++ b/resnet50-fashion_mnist-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 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: 0.5 +``` + +### 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_0.005_training_data_ratio_0.5-4000/config.json b/resnet50-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..55bcbf447ad396e78893f8c1d15e0049595b04f9 --- /dev/null +++ b/resnet50-fashion_mnist-batch_size_64_lr_0.005_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": "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_0.005_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet50-fashion_mnist-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-fashion_mnist-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-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/model.safetensors b/resnet50-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..c6738737c88c110f2f2f4daa19b82cdddf0cd203 --- /dev/null +++ b/resnet50-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_0.8-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:64ce6667bd1e34aaaeab489e8ada8d49b45e3dff1663906ee3c5a81062387f1b +size 94368544 diff --git a/resnet50-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/README.md b/resnet50-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..5f9ceb7cf65f229bb4f46b00f63e24016bfceef2 --- /dev/null +++ b/resnet50-fashion_mnist-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 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-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_0.005_training_data_ratio_0.8-3000/config.json b/resnet50-fashion_mnist-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..55bcbf447ad396e78893f8c1d15e0049595b04f9 --- /dev/null +++ b/resnet50-fashion_mnist-batch_size_64_lr_0.005_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": "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_0.005_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet50-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/resnet50-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": 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num_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: 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_0.01_training_data_ratio_1.0-4000/config.json 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"out_indices": [ + 4 + ], + "stage_names": [ + "stem", + "stage1", + "stage2", + "stage3", + "stage4" + ], + "transformers_version": "4.56.1" +} diff --git a/resnet50-fer2013-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet50-fer2013-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-fer2013-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 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mode 100644 index 0000000000000000000000000000000000000000..8c483b186149fe4993207cbaf525d1a879c28766 --- /dev/null +++ b/resnet50-food101-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:335cc4e582440dbe3b73075e350008a06279ba1af4a87bfc7c773813e2e01911 +size 95114484 diff --git a/resnet50-food101-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/README.md b/resnet50-food101-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..dd0730f4e56d491dc59e5917a00be51e5e50cade --- /dev/null +++ b/resnet50-food101-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 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: 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: 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_0.005_training_data_ratio_0.5-1000/config.json b/resnet50-food101-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..d9f442b44934b43685324cae134e295127e8bfb3 --- /dev/null +++ b/resnet50-food101-batch_size_256_lr_0.005_training_data_ratio_0.5-1000/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_256_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet50-food101-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-food101-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-food101-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/model.safetensors b/resnet50-food101-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..7b6740d4b9498547296f7734ee6e867e73bcd2c9 --- /dev/null +++ b/resnet50-food101-batch_size_256_lr_0.005_training_data_ratio_0.5-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:91a79ebf3a0f9a7811a4f2ba11b932f109c65ad91587ab1932556152b9721055 +size 95114484 diff --git a/resnet50-food101-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/README.md b/resnet50-food101-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..0f9be2747bc0b91b3f9f1a5a57a731ae880ab803 --- /dev/null +++ b/resnet50-food101-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 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: 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_256_lr_0.005_training_data_ratio_0.8-1000/config.json b/resnet50-food101-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..d9f442b44934b43685324cae134e295127e8bfb3 --- /dev/null +++ b/resnet50-food101-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/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_256_lr_0.005_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet50-food101-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-food101-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-food101-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/README.md b/resnet50-food101-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..7e2eb2bccd78ad0d29e90ecd9e2f09021526bfcf --- /dev/null +++ b/resnet50-food101-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 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: 0.5 +``` + +### 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: 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_0.5-1000/config.json b/resnet50-food101-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..d9f442b44934b43685324cae134e295127e8bfb3 --- /dev/null +++ b/resnet50-food101-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/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_256_lr_0.01_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet50-food101-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-food101-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-food101-batch_size_256_lr_0.01_training_data_ratio_0.8-4000/model.safetensors b/resnet50-food101-batch_size_256_lr_0.01_training_data_ratio_0.8-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..de19cf28cdee3995348fdd4756e6052e8f4e4236 --- /dev/null +++ b/resnet50-food101-batch_size_256_lr_0.01_training_data_ratio_0.8-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2c8b0a257eadb665e295c463630b23140d21a8b2b6bd2c2c3c30fff2693cee2f +size 95114484 diff --git a/resnet50-food101-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/README.md b/resnet50-food101-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..0c77cac29fc0fea4d0c85acc6633ef24407a3669 --- /dev/null +++ b/resnet50-food101-batch_size_64_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 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: 0.5 +``` + +### 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: 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_0.5-1000/config.json b/resnet50-food101-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..d9f442b44934b43685324cae134e295127e8bfb3 --- /dev/null +++ b/resnet50-food101-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/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_0.001_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet50-food101-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/resnet50-food101-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/resnet50-food101-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/model.safetensors b/resnet50-food101-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..2c277100e6c890d9ab778d132ee2dc7fb2bc903e --- /dev/null +++ b/resnet50-food101-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8c27e4261512dc2a1839480f8c648a514428a421e837f844ddbe915de88e04f4 +size 95114484 diff --git a/resnet50-food101-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/README.md b/resnet50-food101-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..4d1bfbb7b48efadff88f04fbb6bf852500f05a74 --- /dev/null +++ b/resnet50-food101-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 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: 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: 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_0.01_training_data_ratio_0.5-4000/config.json b/resnet50-food101-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..d9f442b44934b43685324cae134e295127e8bfb3 --- /dev/null +++ b/resnet50-food101-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/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_0.01_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet50-food101-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-food101-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-food101-batch_size_64_lr_0.01_training_data_ratio_0.8-3000/README.md b/resnet50-food101-batch_size_64_lr_0.01_training_data_ratio_0.8-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..45503173e6181aecdaeac8fe2b481476ccbb6af2 --- /dev/null +++ b/resnet50-food101-batch_size_64_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 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: 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_64_lr_0.01_training_data_ratio_0.8-3000/config.json b/resnet50-food101-batch_size_64_lr_0.01_training_data_ratio_0.8-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..d9f442b44934b43685324cae134e295127e8bfb3 --- /dev/null +++ b/resnet50-food101-batch_size_64_lr_0.01_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_64_lr_0.01_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet50-food101-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-food101-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_64_lr_0.01_training_data_ratio_1.0-2000/README.md b/resnet50-food101-batch_size_64_lr_0.01_training_data_ratio_1.0-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..875a5f50f975161bfb23ca95d4b9e9152edf82dc --- /dev/null +++ b/resnet50-food101-batch_size_64_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 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-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-gtsrb-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/README.md b/resnet50-gtsrb-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..5d56a236ae831130dfb2fce828bc0b96d10265fd --- /dev/null +++ b/resnet50-gtsrb-batch_size_128_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 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: 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_128_lr_0.001_training_data_ratio_0.8-2000/config.json b/resnet50-gtsrb-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..72e5aa2e6ca1e8845fcf4a68dc7cd82ec3c90ca4 --- /dev/null +++ b/resnet50-gtsrb-batch_size_128_lr_0.001_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_128_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet50-gtsrb-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/resnet50-gtsrb-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 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b/resnet50-gtsrb-batch_size_256_lr_0.001_training_data_ratio_0.5-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:70f2e9c26834a649b75b8f1a560299cecd98ab7afa26524aa3371026f8c2bf86 +size 94639052 diff --git a/resnet50-gtsrb-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/README.md b/resnet50-gtsrb-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..4b3cae91514257db7ff7265b1157bf605fefd8fe --- /dev/null +++ b/resnet50-gtsrb-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 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-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_0.5-2000/config.json b/resnet50-gtsrb-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..72e5aa2e6ca1e8845fcf4a68dc7cd82ec3c90ca4 --- /dev/null +++ b/resnet50-gtsrb-batch_size_256_lr_0.001_training_data_ratio_0.5-2000/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_256_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet50-gtsrb-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-gtsrb-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-gtsrb-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/model.safetensors b/resnet50-gtsrb-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..bc645c0d72b69aabc29400700f2bacf8f5e9d6d2 --- /dev/null +++ b/resnet50-gtsrb-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:cf411688d14faa9940e0ed47668c9ee1b64b4bb192fd0cbad055d04adf962a1c +size 94639052 diff --git a/resnet50-gtsrb-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/model.safetensors b/resnet50-gtsrb-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..9bc2bdbdeca0da2957fbac4af23968fe2a603f92 --- /dev/null +++ b/resnet50-gtsrb-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:01c3e32c321c5922f647cd155bed9f1fdb306af3922eb9b7cbacbca2f3413545 +size 94639052 diff --git a/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/README.md b/resnet50-gtsrb-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..f3b5930b52f0965503999c1199fc20deae92b909 --- /dev/null +++ b/resnet50-gtsrb-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 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-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_0.5-3000/config.json b/resnet50-gtsrb-batch_size_64_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_64_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_64_lr_0.005_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet50-gtsrb-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-gtsrb-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-gtsrb-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/model.safetensors b/resnet50-gtsrb-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..701833f50e1bfe06a04543b4f2bdd746ad5a57a0 --- /dev/null +++ b/resnet50-gtsrb-batch_size_64_lr_0.01_training_data_ratio_0.5-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:04024c2c41c404b13a9acc59cec8ea9667204b2ffe5882d7d9711f5bef7a1c94 +size 94639052 diff --git a/resnet50-gtsrb-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/README.md b/resnet50-gtsrb-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..80c49db656a90cfb7b486d55711174ebc00fbe68 --- /dev/null +++ b/resnet50-gtsrb-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 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: 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: 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_0.01_training_data_ratio_0.5-4000/config.json b/resnet50-gtsrb-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..72e5aa2e6ca1e8845fcf4a68dc7cd82ec3c90ca4 --- /dev/null +++ b/resnet50-gtsrb-batch_size_64_lr_0.01_training_data_ratio_0.5-4000/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_64_lr_0.01_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet50-gtsrb-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-gtsrb-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-gtsrb-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/README.md b/resnet50-gtsrb-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..ccf36cfb19da52a4ad800430c319502c82aa0534 --- /dev/null +++ b/resnet50-gtsrb-batch_size_64_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 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: 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_0.01_training_data_ratio_1.0-4000/config.json b/resnet50-gtsrb-batch_size_64_lr_0.01_training_data_ratio_1.0-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..72e5aa2e6ca1e8845fcf4a68dc7cd82ec3c90ca4 --- /dev/null +++ b/resnet50-gtsrb-batch_size_64_lr_0.01_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_64_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet50-gtsrb-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/resnet50-gtsrb-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/resnet50-kmnist-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/model.safetensors b/resnet50-kmnist-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..6ea26fbd4b56c67a1883089105452b48a03be676 --- /dev/null +++ b/resnet50-kmnist-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:cf63b814920f9dda1ff11475a66a359c7cde17c1e68fa41338e1158e9de98715 +size 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b/resnet50-kmnist-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 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: 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_0.01_training_data_ratio_0.5-1000/config.json b/resnet50-kmnist-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..7cb9e38ace4738e265b487d7c814cd0f7cdbeae1 --- /dev/null +++ b/resnet50-kmnist-batch_size_256_lr_0.01_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": "\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_0.01_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet50-kmnist-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-kmnist-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-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.8-1000/model.safetensors b/resnet50-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.8-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..1cbd86485a1631fea5f9726a4ae5a6dbe7860bbe --- /dev/null +++ b/resnet50-kmnist-batch_size_64_lr_0.001_training_data_ratio_0.8-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4cb9507a177048b7362a9caf0740979e3bdfbe9044189f12b01a1757a393edf0 +size 94368544 diff --git a/resnet50-kmnist-batch_size_64_lr_0.01_training_data_ratio_0.5-1000/README.md b/resnet50-kmnist-batch_size_64_lr_0.01_training_data_ratio_0.5-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..7a7d3dc155782ee947f5c2cd0e88c5f7023002e4 --- /dev/null +++ b/resnet50-kmnist-batch_size_64_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 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: 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_0.01_training_data_ratio_0.5-1000/config.json b/resnet50-kmnist-batch_size_64_lr_0.01_training_data_ratio_0.5-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..7cb9e38ace4738e265b487d7c814cd0f7cdbeae1 --- /dev/null +++ b/resnet50-kmnist-batch_size_64_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": "\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_0.5-1000/preprocessor_config.json b/resnet50-kmnist-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-kmnist-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-mnist-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/model.safetensors b/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..076d496038ef9fbac9cf7fe85454f9efd4677f26 --- /dev/null +++ b/resnet50-mnist-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:dd2957b587cedd9d59f8a3005f65118f0c0c7bcf4bb115ac88ef77e8e3c700b3 +size 94368544 diff --git a/resnet50-mnist-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/model.safetensors b/resnet50-mnist-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..0dce1bcbaad65b2cb55a50329f4bc712984422db --- /dev/null +++ b/resnet50-mnist-batch_size_128_lr_0.01_training_data_ratio_0.8-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8bb11d07a510e1aa05d4c1b405948180ffc0dbd2e57933784d374dc8715ad3bc +size 94368544 diff --git a/resnet50-mnist-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/README.md b/resnet50-mnist-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..d3c549c4305badedaa3c7a349aa9451f39ca0ef5 --- /dev/null +++ b/resnet50-mnist-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 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: 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_0.01_training_data_ratio_1.0-4000/config.json b/resnet50-mnist-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..1edcdd247f31547feb0c0bebd29bf1cd24a4532f --- /dev/null +++ b/resnet50-mnist-batch_size_128_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": "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_1.0-4000/preprocessor_config.json 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b/resnet50-mnist-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..744e9a0c1fe44f8c1d549c59694391e11de929d5 --- /dev/null +++ b/resnet50-mnist-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 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: 0.8 +``` + +### 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_64_lr_0.001_training_data_ratio_0.8-2000/config.json b/resnet50-mnist-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..1edcdd247f31547feb0c0bebd29bf1cd24a4532f --- /dev/null +++ b/resnet50-mnist-batch_size_64_lr_0.001_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": "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_0.001_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet50-mnist-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-mnist-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-mnist-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/README.md b/resnet50-mnist-batch_size_64_lr_0.005_training_data_ratio_1.0-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..5575d050978021cf05225650109f67e57fa16911 --- /dev/null +++ b/resnet50-mnist-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 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: 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_64_lr_0.005_training_data_ratio_1.0-3000/config.json b/resnet50-mnist-batch_size_64_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_64_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_64_lr_0.005_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet50-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/resnet50-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/resnet50-oxford-iiit-pet-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/model.safetensors b/resnet50-oxford-iiit-pet-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..f9cd7ebda240cf1fff11a778d5a633611da5f8f8 --- /dev/null +++ b/resnet50-oxford-iiit-pet-batch_size_128_lr_0.001_training_data_ratio_0.8-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2cf93d644dbcaffefa27be60a5ce4010fa160e8da0fc6a8efe617f29f4c213af +size 94589868 diff --git a/resnet50-oxford-iiit-pet-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/model.safetensors b/resnet50-oxford-iiit-pet-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..ecc9423531dae23f255119a547ea0fb268f2a68b --- /dev/null +++ b/resnet50-oxford-iiit-pet-batch_size_128_lr_0.005_training_data_ratio_0.5-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0a9105dbd23485c02ff98dd769e74eaa67588d8641e13e9c27b9bbe1fecd16a6 +size 94589868 diff --git a/resnet50-oxford-iiit-pet-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/README.md b/resnet50-oxford-iiit-pet-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..ca1d25a1950d5168c68a0d3497a131a642e14694 --- /dev/null +++ b/resnet50-oxford-iiit-pet-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 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: 0.005 + 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-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_0.005_training_data_ratio_0.8-4000/config.json b/resnet50-oxford-iiit-pet-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..70c303978f48704b0d2ed76247d55f7c0a3fe6b2 --- /dev/null +++ b/resnet50-oxford-iiit-pet-batch_size_128_lr_0.005_training_data_ratio_0.8-4000/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": 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b/resnet50-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..7bfcf514372ec1bcc8137f0e064e41e949eb20b3 --- /dev/null +++ b/resnet50-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4ce73de6ce809b60a026507288d668af0a5d08d48b186bebfe09b5bfd34990fa +size 94589868 diff --git a/resnet50-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/README.md b/resnet50-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..c389122b15f40eb5088466214790b9c45c105771 --- /dev/null +++ b/resnet50-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-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: 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: 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_256_lr_0.005_training_data_ratio_1.0-2000/config.json b/resnet50-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..70c303978f48704b0d2ed76247d55f7c0a3fe6b2 --- /dev/null +++ b/resnet50-oxford-iiit-pet-batch_size_256_lr_0.005_training_data_ratio_1.0-2000/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_256_lr_0.005_training_data_ratio_1.0-2000/preprocessor_config.json b/resnet50-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/resnet50-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": { + 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b/resnet50-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..4ca499ea8099d794001e03749c38a2252ad5a1c5 --- /dev/null +++ b/resnet50-oxford-iiit-pet-batch_size_64_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 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: 0.8 +``` + +### 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-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_64_lr_0.005_training_data_ratio_0.8-4000/config.json b/resnet50-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..70c303978f48704b0d2ed76247d55f7c0a3fe6b2 --- /dev/null +++ b/resnet50-oxford-iiit-pet-batch_size_64_lr_0.005_training_data_ratio_0.8-4000/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": 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+++ b/resnet50-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:09d37223e46152c1483f1ffcab3ff2e03abb34595f7a93faf3212ca5f81de197 +size 95122680 diff --git a/resnet50-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/README.md b/resnet50-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..f2ad1a325c8f9db2eb242fd5a7850f5003fdcc14 --- /dev/null +++ b/resnet50-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/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: 0.001 + 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_1.0-1000/config.json b/resnet50-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..ee05e378f6d60c8217f7b8db60be10c17bce37e2 --- /dev/null +++ b/resnet50-oxford_flowers102-batch_size_128_lr_0.001_training_data_ratio_1.0-1000/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 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b/resnet50-oxford_flowers102-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 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: 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_64_lr_0.001_training_data_ratio_1.0-2000/config.json b/resnet50-oxford_flowers102-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..ee05e378f6d60c8217f7b8db60be10c17bce37e2 --- /dev/null +++ b/resnet50-oxford_flowers102-batch_size_64_lr_0.001_training_data_ratio_1.0-2000/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_1.0-2000/preprocessor_config.json b/resnet50-oxford_flowers102-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-oxford_flowers102-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-pcam-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/model.safetensors b/resnet50-pcam-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..5e68f97da545a994ed24ce5306bf2d2c1b183c6a --- /dev/null +++ b/resnet50-pcam-batch_size_128_lr_0.005_training_data_ratio_0.5-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5d1b068ff672e747b53a78d516a30fe23eb6ead3a88868a5844edcac9d355a84 +size 94302952 diff --git a/resnet50-pcam-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/README.md b/resnet50-pcam-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..3501f410ff0d3874e2c0a408ace53335ef639d5b --- /dev/null +++ b/resnet50-pcam-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 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: 0.8 +``` + +### 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_0.001_training_data_ratio_0.8-4000/config.json b/resnet50-pcam-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..4b0ac74d3d8fd86ac59d6ac1791d9e00ac89d34c --- /dev/null +++ b/resnet50-pcam-batch_size_256_lr_0.001_training_data_ratio_0.8-4000/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_256_lr_0.001_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet50-pcam-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-pcam-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-pcam-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/README.md b/resnet50-pcam-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..31bff57cb5e7fc167139ad8967d4e276707509bc --- /dev/null +++ b/resnet50-pcam-batch_size_256_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 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: 0.005 + 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: 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_0.005_training_data_ratio_0.8-4000/config.json b/resnet50-pcam-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..4b0ac74d3d8fd86ac59d6ac1791d9e00ac89d34c --- /dev/null +++ b/resnet50-pcam-batch_size_256_lr_0.005_training_data_ratio_0.8-4000/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_256_lr_0.005_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet50-pcam-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/resnet50-pcam-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/resnet50-pcam-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/README.md b/resnet50-pcam-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..5d76eec3fe0295b03f63e38bb59aee1e5eae76c4 --- /dev/null +++ b/resnet50-pcam-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 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: 0.005 + 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: 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_0.005_training_data_ratio_1.0-3000/config.json b/resnet50-pcam-batch_size_256_lr_0.005_training_data_ratio_1.0-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..4b0ac74d3d8fd86ac59d6ac1791d9e00ac89d34c --- /dev/null +++ b/resnet50-pcam-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": "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_0.005_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet50-pcam-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-pcam-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-pcam-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/model.safetensors b/resnet50-pcam-batch_size_64_lr_0.001_training_data_ratio_0.8-2000/model.safetensors new file mode 100644 index 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b/resnet50-pcam-batch_size_64_lr_0.01_training_data_ratio_0.8-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..ee679f2a1d41763c5fbdf6077b35e6f4c60487e4 --- /dev/null +++ b/resnet50-pcam-batch_size_64_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: 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-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_64_lr_0.01_training_data_ratio_0.8-1000/config.json b/resnet50-pcam-batch_size_64_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_64_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_64_lr_0.01_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet50-pcam-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/resnet50-pcam-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/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/README.md b/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..549a16e02bad0ccfbc7f8a9b28aeb1f706b14d08 --- /dev/null +++ b/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/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: 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_0.5-2000/config.json b/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..8e2d395685cee2a9c76c2b7224752720ae236c37 --- /dev/null +++ b/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/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_128_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet50-rendered-sst2-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/resnet50-rendered-sst2-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/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/model.safetensors b/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..baecf27b3f280f03d2f0bb8c41ea342f8d8a664d --- /dev/null +++ b/resnet50-rendered-sst2-batch_size_128_lr_0.001_training_data_ratio_1.0-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d257667fb80c41475d6eef4a8b29f253e8a680e85368a1973b8ed60d20ca4edf +size 94302952 diff --git a/resnet50-rendered-sst2-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/README.md b/resnet50-rendered-sst2-batch_size_256_lr_0.001_training_data_ratio_0.5-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..fe43d624e1db2ff7d47e4dc87de5a3243e3f8564 --- /dev/null +++ b/resnet50-rendered-sst2-batch_size_256_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: 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: 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_0.5-3000/config.json b/resnet50-rendered-sst2-batch_size_256_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_256_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_256_lr_0.001_training_data_ratio_0.5-3000/preprocessor_config.json b/resnet50-rendered-sst2-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/resnet50-rendered-sst2-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/resnet50-rendered-sst2-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/README.md b/resnet50-rendered-sst2-batch_size_256_lr_0.001_training_data_ratio_1.0-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..20b688b6f94add020e8c7e5b205828826cb22239 --- /dev/null +++ b/resnet50-rendered-sst2-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 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: 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_0.001_training_data_ratio_1.0-3000/config.json b/resnet50-rendered-sst2-batch_size_256_lr_0.001_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_0.001_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_0.001_training_data_ratio_1.0-3000/preprocessor_config.json b/resnet50-rendered-sst2-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-rendered-sst2-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-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/model.safetensors b/resnet50-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..faaa194ae39f7063d1843896d0d8a599617b3c6a --- /dev/null +++ b/resnet50-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.5-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:836fe7704a06ce368e7d74d70dba3a7aac2f7da0080851dc4bf10486f3d4de0b +size 94302952 diff --git a/resnet50-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/README.md b/resnet50-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..03bd05e476a51e884f112fa9a70409d646f23280 --- /dev/null +++ b/resnet50-rendered-sst2-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 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-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_0.8-1000/config.json b/resnet50-rendered-sst2-batch_size_256_lr_0.005_training_data_ratio_0.8-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..8e2d395685cee2a9c76c2b7224752720ae236c37 --- /dev/null +++ b/resnet50-rendered-sst2-batch_size_256_lr_0.005_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": "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_0.8-1000/preprocessor_config.json b/resnet50-rendered-sst2-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-rendered-sst2-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-rendered-sst2-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/model.safetensors b/resnet50-rendered-sst2-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..caf3cfd685ebe7f1db78d561b304505e8957974f --- /dev/null +++ b/resnet50-rendered-sst2-batch_size_256_lr_0.01_training_data_ratio_0.5-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:18b9e6192a50db0b6ab95c14b8eecc327fd28be4c9d5c53efedbc64114ece4a7 +size 94302952 diff --git a/resnet50-rendered-sst2-batch_size_256_lr_0.01_training_data_ratio_0.8-3000/README.md b/resnet50-rendered-sst2-batch_size_256_lr_0.01_training_data_ratio_0.8-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..4bf6f8b33e51f47c64ebe27d7ef5f989956f914a --- /dev/null +++ b/resnet50-rendered-sst2-batch_size_256_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 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: 0.01 + 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: 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_0.01_training_data_ratio_0.8-3000/config.json b/resnet50-rendered-sst2-batch_size_256_lr_0.01_training_data_ratio_0.8-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..8e2d395685cee2a9c76c2b7224752720ae236c37 --- /dev/null +++ b/resnet50-rendered-sst2-batch_size_256_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": "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_0.01_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet50-rendered-sst2-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/resnet50-rendered-sst2-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/resnet50-rendered-sst2-batch_size_256_lr_0.01_training_data_ratio_0.8-4000/README.md b/resnet50-rendered-sst2-batch_size_256_lr_0.01_training_data_ratio_0.8-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..4bf6f8b33e51f47c64ebe27d7ef5f989956f914a --- /dev/null +++ b/resnet50-rendered-sst2-batch_size_256_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 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: 0.01 + 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: 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_0.01_training_data_ratio_0.8-4000/config.json b/resnet50-rendered-sst2-batch_size_256_lr_0.01_training_data_ratio_0.8-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..8e2d395685cee2a9c76c2b7224752720ae236c37 --- /dev/null +++ b/resnet50-rendered-sst2-batch_size_256_lr_0.01_training_data_ratio_0.8-4000/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_256_lr_0.01_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet50-rendered-sst2-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/resnet50-rendered-sst2-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/resnet50-rendered-sst2-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/model.safetensors b/resnet50-rendered-sst2-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..e8ca56a96ae81d608c5d38f2bcaee185f048cf2b --- /dev/null +++ b/resnet50-rendered-sst2-batch_size_64_lr_0.005_training_data_ratio_0.8-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0906478fc747f2d70440720bc6bd89f18b0cc017ad1261e4b5a89adcdd688155 +size 94302952 diff --git a/resnet50-rendered-sst2-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/README.md b/resnet50-rendered-sst2-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..1759c6a2c37549169d0a50f498506110fc82b2ba --- /dev/null +++ b/resnet50-rendered-sst2-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 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: 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_64_lr_0.005_training_data_ratio_1.0-1000/config.json b/resnet50-rendered-sst2-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..8e2d395685cee2a9c76c2b7224752720ae236c37 --- /dev/null +++ b/resnet50-rendered-sst2-batch_size_64_lr_0.005_training_data_ratio_1.0-1000/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": "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_0.005_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet50-rendered-sst2-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-rendered-sst2-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-resisc45-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/README.md b/resnet50-resisc45-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..ede7cbb149b3ea9be37610f93524b9b59762f638 --- /dev/null +++ b/resnet50-resisc45-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 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: 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: 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_0.001_training_data_ratio_0.8-1000/config.json b/resnet50-resisc45-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..f19cd9d15140683527543a4e276977d9a205e4b4 --- /dev/null +++ b/resnet50-resisc45-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/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_128_lr_0.001_training_data_ratio_0.8-1000/preprocessor_config.json b/resnet50-resisc45-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-resisc45-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-resisc45-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/README.md b/resnet50-resisc45-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..b9fe04566b73031f39bd65f0d4d7aeb3d7f66709 --- /dev/null +++ b/resnet50-resisc45-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/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: 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_0.5-1000/config.json b/resnet50-resisc45-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..f19cd9d15140683527543a4e276977d9a205e4b4 --- /dev/null +++ b/resnet50-resisc45-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/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_128_lr_0.005_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet50-resisc45-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/resnet50-resisc45-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/resnet50-resisc45-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/README.md b/resnet50-resisc45-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..831e432c6062fa5d7d5f14dc97551f6b1c184448 --- /dev/null +++ b/resnet50-resisc45-batch_size_128_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 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: 0.8 +``` + +### 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: 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_0.01_training_data_ratio_0.8-1000/config.json b/resnet50-resisc45-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..f19cd9d15140683527543a4e276977d9a205e4b4 --- /dev/null +++ b/resnet50-resisc45-batch_size_128_lr_0.01_training_data_ratio_0.8-1000/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, + 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b/resnet50-resisc45-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..8615e17541aa8a53cf31b5337ac486cc9b84fc82 --- /dev/null +++ b/resnet50-resisc45-batch_size_64_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 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: 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: 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_64_lr_0.01_training_data_ratio_1.0-1000/config.json b/resnet50-resisc45-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..f19cd9d15140683527543a4e276977d9a205e4b4 --- /dev/null +++ b/resnet50-resisc45-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/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_64_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json b/resnet50-resisc45-batch_size_64_lr_0.01_training_data_ratio_1.0-1000/preprocessor_config.json 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https://git-lfs.github.com/spec/v1 +oid sha256:e8f90449190ff5f4c1c50b3dc71cc47629cce242620f8a9240eaccc65fcf3d66 +size 94368544 diff --git a/resnet50-stl10-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/README.md b/resnet50-stl10-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..a7538cc7fbb827c488f15d833664a856374413d0 --- /dev/null +++ b/resnet50-stl10-batch_size_256_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 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: 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: 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_256_lr_0.005_training_data_ratio_0.8-2000/config.json b/resnet50-stl10-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..589b71bb15675afba14a3d018d8e1b4a07ab7182 --- /dev/null +++ b/resnet50-stl10-batch_size_256_lr_0.005_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": "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_256_lr_0.005_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet50-stl10-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/resnet50-stl10-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/resnet50-stl10-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/model.safetensors b/resnet50-stl10-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..98c3c653ca15923d60718c2e8c5b0056e8d92eb8 --- /dev/null +++ b/resnet50-stl10-batch_size_256_lr_0.01_training_data_ratio_1.0-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:93edc6819772025646d4819fbd90363e827f919784055af0029920fae723a7c1 +size 94368544 diff --git a/resnet50-stl10-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/README.md b/resnet50-stl10-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..7cb7a12b87f7e9d69c322aea30488a048d45ebfc --- /dev/null +++ b/resnet50-stl10-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 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: 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: 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_256_lr_0.01_training_data_ratio_1.0-4000/config.json b/resnet50-stl10-batch_size_256_lr_0.01_training_data_ratio_1.0-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..589b71bb15675afba14a3d018d8e1b4a07ab7182 --- /dev/null +++ b/resnet50-stl10-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": "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_256_lr_0.01_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet50-stl10-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-stl10-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-stl10-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/model.safetensors b/resnet50-stl10-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..371c000366165dd4209d175f162c4321e00064a3 --- /dev/null +++ b/resnet50-stl10-batch_size_64_lr_0.001_training_data_ratio_1.0-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:88d7290cbe45757aa22911020c0cf388ba563312004b4ab8710bf6a416057031 +size 94368544 diff --git a/resnet50-stl10-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/README.md b/resnet50-stl10-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..a2f93595aac18c53b802c194feca1ccccb122f2e --- /dev/null +++ b/resnet50-stl10-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 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: 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: 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_64_lr_0.005_training_data_ratio_0.8-3000/config.json b/resnet50-stl10-batch_size_64_lr_0.005_training_data_ratio_0.8-3000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..589b71bb15675afba14a3d018d8e1b4a07ab7182 --- /dev/null +++ b/resnet50-stl10-batch_size_64_lr_0.005_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": "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_64_lr_0.005_training_data_ratio_0.8-3000/preprocessor_config.json b/resnet50-stl10-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-stl10-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-stl10-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/model.safetensors b/resnet50-stl10-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..1469a8ed6e9cc45a797fdaa24b0e913d279a71d7 --- /dev/null +++ b/resnet50-stl10-batch_size_64_lr_0.01_training_data_ratio_1.0-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2296a8428320f79ff316d3d535c36e66d91d51dd0c09fe48d39b4f9ab9a2de2c +size 94368544 diff --git a/resnet50-sun397-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/README.md b/resnet50-sun397-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..a5ea672ba19830d7292baed45c0d38cd12b54642 --- /dev/null +++ b/resnet50-sun397-batch_size_128_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 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: 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_128_lr_0.001_training_data_ratio_0.5-2000/config.json b/resnet50-sun397-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..7b3f0b16022576c1d5cf54a17e75ff9088c89b17 --- /dev/null +++ b/resnet50-sun397-batch_size_128_lr_0.001_training_data_ratio_0.5-2000/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_128_lr_0.001_training_data_ratio_0.5-2000/preprocessor_config.json b/resnet50-sun397-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/resnet50-sun397-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/resnet50-sun397-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/model.safetensors b/resnet50-sun397-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..3a1b31a973f08173b4a22b69798a0f1b122f81a0 --- /dev/null +++ b/resnet50-sun397-batch_size_128_lr_0.001_training_data_ratio_0.5-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4c48397a824815e2c4cacce189948c3d10c94505314e060ac2dae45b2ce695e5 +size 97540532 diff --git a/resnet50-sun397-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/README.md b/resnet50-sun397-batch_size_128_lr_0.001_training_data_ratio_0.8-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..198d79d5fa12004e1c84c61b4898688c8059a8b5 --- /dev/null +++ b/resnet50-sun397-batch_size_128_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: 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-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_128_lr_0.001_training_data_ratio_0.8-2000/config.json b/resnet50-sun397-batch_size_128_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_128_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_128_lr_0.001_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet50-sun397-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/resnet50-sun397-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/resnet50-sun397-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/model.safetensors b/resnet50-sun397-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..134dddca24672ec2f4bf34bed5c54999380d6238 --- /dev/null +++ b/resnet50-sun397-batch_size_128_lr_0.005_training_data_ratio_0.5-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b6477b4f067816331004958c76c402ffad2d962e23cd777d86b9b1005c95323e +size 97540532 diff --git a/resnet50-sun397-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/README.md b/resnet50-sun397-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..475764883d5c42c7cf491ba91c6f9055d9008965 --- /dev/null +++ b/resnet50-sun397-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 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: 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_128_lr_0.01_training_data_ratio_1.0-4000/config.json b/resnet50-sun397-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..7b3f0b16022576c1d5cf54a17e75ff9088c89b17 --- /dev/null +++ b/resnet50-sun397-batch_size_128_lr_0.01_training_data_ratio_1.0-4000/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": 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https://git-lfs.github.com/spec/v1 +oid sha256:49d78ffae3ca13fd3f8c9cc82b3a8f435a1e4ac71b3cc3c758ecee5dfbe96ea9 +size 97540532 diff --git a/resnet50-sun397-batch_size_64_lr_0.005_training_data_ratio_0.5-2000/README.md b/resnet50-sun397-batch_size_64_lr_0.005_training_data_ratio_0.5-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..e2b809b47accbc8a61d8ab3fa511fea6ecb9210e --- /dev/null +++ b/resnet50-sun397-batch_size_64_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 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: 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_0.005_training_data_ratio_0.5-2000/config.json b/resnet50-sun397-batch_size_64_lr_0.005_training_data_ratio_0.5-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..7b3f0b16022576c1d5cf54a17e75ff9088c89b17 --- /dev/null +++ b/resnet50-sun397-batch_size_64_lr_0.005_training_data_ratio_0.5-2000/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_0.5-2000/preprocessor_config.json b/resnet50-sun397-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/resnet50-sun397-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/resnet50-sun397-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/README.md b/resnet50-sun397-batch_size_64_lr_0.005_training_data_ratio_0.5-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..e2b809b47accbc8a61d8ab3fa511fea6ecb9210e --- /dev/null +++ b/resnet50-sun397-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 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: 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_0.005_training_data_ratio_0.5-4000/config.json b/resnet50-sun397-batch_size_64_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_64_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_64_lr_0.005_training_data_ratio_0.5-4000/preprocessor_config.json b/resnet50-sun397-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-sun397-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, + 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file mode 100644 index 0000000000000000000000000000000000000000..88daa1b5f13afcce3ed228e0476eaa9db2e2fc50 --- /dev/null +++ b/resnet50-sun397-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 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_1.0-4000/config.json b/resnet50-sun397-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..7b3f0b16022576c1d5cf54a17e75ff9088c89b17 --- /dev/null +++ b/resnet50-sun397-batch_size_64_lr_0.005_training_data_ratio_1.0-4000/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_64_lr_0.005_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet50-sun397-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-sun397-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-svhn-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/model.safetensors b/resnet50-svhn-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..7daf2211c673fb37af3d416826238e7bcdb91408 --- /dev/null +++ b/resnet50-svhn-batch_size_128_lr_0.001_training_data_ratio_0.8-1000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e73e1d30177a95bea98cd9034dc26610e12004152259de6266fe7a91bc13fedb +size 94368544 diff --git a/resnet50-svhn-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/README.md b/resnet50-svhn-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..71cee6f5ade1a8a95203958eb5ff31b734780efd --- /dev/null +++ b/resnet50-svhn-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/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: 0.001 + 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_1.0-4000/config.json b/resnet50-svhn-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..1edcdd247f31547feb0c0bebd29bf1cd24a4532f --- /dev/null +++ b/resnet50-svhn-batch_size_128_lr_0.001_training_data_ratio_1.0-4000/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_0.001_training_data_ratio_1.0-4000/preprocessor_config.json b/resnet50-svhn-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-svhn-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-svhn-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/README.md b/resnet50-svhn-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..bc7371186276d5ba6b5dd8bf058e862e78fbc542 --- /dev/null +++ b/resnet50-svhn-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/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: 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: 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_0.01_training_data_ratio_0.8-2000/config.json b/resnet50-svhn-batch_size_128_lr_0.01_training_data_ratio_0.8-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..1edcdd247f31547feb0c0bebd29bf1cd24a4532f --- /dev/null +++ b/resnet50-svhn-batch_size_128_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": "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_0.01_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet50-svhn-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/resnet50-svhn-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/resnet50-svhn-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/model.safetensors b/resnet50-svhn-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..fe2bd70c7cfe4a148134c0de49ab6c97b936ec7d --- /dev/null +++ b/resnet50-svhn-batch_size_256_lr_0.001_training_data_ratio_1.0-4000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d50fe4635f38e4f8512f0d3e64bb2d642f28e4cd9f9ce7385e105cb8fc83a749 +size 94368544 diff --git a/resnet50-svhn-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/model.safetensors b/resnet50-svhn-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..414e8ddc3559fb4d2f51de592ad9957f29bb68c6 --- /dev/null +++ b/resnet50-svhn-batch_size_256_lr_0.005_training_data_ratio_0.8-2000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2b6c29c69ea45f069ccf550188a62629d7fc106fa7c5d2be4012c7762b954024 +size 94368544 diff --git a/resnet50-svhn-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/README.md b/resnet50-svhn-batch_size_64_lr_0.001_training_data_ratio_0.5-1000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..930ef6be1123a64b5835f584a7f831cee7faa11c --- /dev/null +++ b/resnet50-svhn-batch_size_64_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: 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: 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_0.5-1000/config.json b/resnet50-svhn-batch_size_64_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_64_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_64_lr_0.001_training_data_ratio_0.5-1000/preprocessor_config.json b/resnet50-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/resnet50-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/resnet50-svhn-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/model.safetensors b/resnet50-svhn-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..47db82156165f08243fc23ae5351542de389af54 --- /dev/null +++ b/resnet50-svhn-batch_size_64_lr_0.005_training_data_ratio_0.5-3000/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:11c3d0cfe38dab060c3fbf3ae2fd8bea665a497052579ae9e81fb69a8894c60a +size 94368544 diff --git a/resnet50-svhn-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/model.safetensors b/resnet50-svhn-batch_size_64_lr_0.005_training_data_ratio_1.0-2000/model.safetensors new file mode 100644 index 0000000000000000000000000000000000000000..a5294f8bef5d4d8967cea96d006c3e0a7bafb26e --- /dev/null +++ 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0000000000000000000000000000000000000000..91689d67b68f58890ca635d8fe84b5be8b09cd30 --- /dev/null +++ b/resnet50-svhn-batch_size_64_lr_0.01_training_data_ratio_0.8-2000/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: 0.01 + 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: 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_0.01_training_data_ratio_0.8-2000/config.json b/resnet50-svhn-batch_size_64_lr_0.01_training_data_ratio_0.8-2000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..1edcdd247f31547feb0c0bebd29bf1cd24a4532f --- /dev/null +++ b/resnet50-svhn-batch_size_64_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": "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_0.01_training_data_ratio_0.8-2000/preprocessor_config.json b/resnet50-svhn-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/resnet50-svhn-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/resnet50-svhn-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/README.md b/resnet50-svhn-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/README.md new file mode 100644 index 0000000000000000000000000000000000000000..91689d67b68f58890ca635d8fe84b5be8b09cd30 --- /dev/null +++ b/resnet50-svhn-batch_size_64_lr_0.01_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: 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: 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_0.01_training_data_ratio_0.8-4000/config.json b/resnet50-svhn-batch_size_64_lr_0.01_training_data_ratio_0.8-4000/config.json new file mode 100644 index 0000000000000000000000000000000000000000..1edcdd247f31547feb0c0bebd29bf1cd24a4532f --- /dev/null +++ b/resnet50-svhn-batch_size_64_lr_0.01_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_64_lr_0.01_training_data_ratio_0.8-4000/preprocessor_config.json b/resnet50-svhn-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/resnet50-svhn-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 + } +}