Upload folder using huggingface_hub

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: 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
+```
+

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"
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8335be814676ebfccc7593622294876f3cdbf36222377a1bc25d9995e3884263
+size 233387400

preprocessor_config.json

@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}