Model save

README.md

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+---
+license: apache-2.0
+base_model: microsoft/swin-base-patch4-window7-224-in22k
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: swin-base-patch4-window7-224-in22k-newly-trained
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.959
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# swin-base-patch4-window7-224-in22k-newly-trained
+
+This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-base-patch4-window7-224-in22k) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1335
+- Accuracy: 0.959
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.2459        | 0.14  | 10   | 1.7346          | 0.575    |
+| 1.4338        | 0.28  | 20   | 0.7222          | 0.841    |
+| 0.8059        | 0.43  | 30   | 0.3252          | 0.915    |
+| 0.5772        | 0.57  | 40   | 0.2071          | 0.942    |
+| 0.5599        | 0.71  | 50   | 0.1553          | 0.958    |
+| 0.4473        | 0.85  | 60   | 0.1373          | 0.958    |
+| 0.4292        | 0.99  | 70   | 0.1335          | 0.959    |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.1.1
+- Datasets 2.14.6
+- Tokenizers 0.14.1

config.json

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+{
+  "_name_or_path": "microsoft/swin-base-patch4-window7-224-in22k",
+  "architectures": [
+    "SwinForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "depths": [
+    2,
+    2,
+    18,
+    2
+  ],
+  "drop_path_rate": 0.1,
+  "embed_dim": 128,
+  "encoder_stride": 32,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "Airplane",
+    "1": "Automobile",
+    "2": "Bird",
+    "3": "Cat",
+    "4": "Deer",
+    "5": "Dog",
+    "6": "Frog",
+    "7": "Horse",
+    "8": "Ship",
+    "9": "Truck"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "Airplane": 0,
+    "Automobile": 1,
+    "Bird": 2,
+    "Cat": 3,
+    "Deer": 4,
+    "Dog": 5,
+    "Frog": 6,
+    "Horse": 7,
+    "Ship": 8,
+    "Truck": 9
+  },
+  "layer_norm_eps": 1e-05,
+  "mlp_ratio": 4.0,
+  "model_type": "swin",
+  "num_channels": 3,
+  "num_heads": [
+    4,
+    8,
+    16,
+    32
+  ],
+  "num_layers": 4,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "patch_size": 4,
+  "path_norm": true,
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "torch_dtype": "float32",
+  "transformers_version": "4.35.0",
+  "use_absolute_embeddings": false,
+  "window_size": 7
+}

model.safetensors

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+size 347531616

preprocessor_config.json

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+{
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ViTImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 224,
+    "width": 224
+  }
+}

training_args.bin

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