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  1. README.md +84 -0
  2. config.json +77 -0
  3. model.safetensors +3 -0
  4. preprocessor_config.json +22 -0
  5. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: microsoft/swin-tiny-patch4-window7-224
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - imagefolder
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: None
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+ results:
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+ - task:
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+ name: Image Classification
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+ type: image-classification
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+ dataset:
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+ name: imagefolder
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+ type: imagefolder
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+ config: default
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+ split: train
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.866
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # None
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+
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+ This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4987
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+ - Accuracy: 0.866
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 1
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 2.1773 | 0.14 | 10 | 1.8121 | 0.521 |
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+ | 1.6444 | 0.28 | 20 | 1.1345 | 0.695 |
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+ | 1.2437 | 0.43 | 30 | 0.8262 | 0.762 |
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+ | 1.0201 | 0.57 | 40 | 0.6576 | 0.804 |
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+ | 0.9683 | 0.71 | 50 | 0.5604 | 0.838 |
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+ | 0.8936 | 0.85 | 60 | 0.5137 | 0.853 |
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+ | 0.8535 | 0.99 | 70 | 0.4987 | 0.866 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.1.1
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
config.json ADDED
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+ {
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+ "_name_or_path": "microsoft/swin-tiny-patch4-window7-224",
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+ "architectures": [
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+ "SwinForImageClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.0,
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+ "depths": [
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+ 2,
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+ 2,
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+ 6,
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+ 2
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+ ],
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+ "drop_path_rate": 0.1,
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+ "embed_dim": 96,
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+ "encoder_stride": 32,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.0,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "Airplane",
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+ "1": "Automobile",
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+ "2": "Bird",
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+ "3": "Cat",
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+ "4": "Deer",
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+ "5": "Dog",
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+ "6": "Frog",
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+ "7": "Horse",
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+ "8": "Ship",
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+ "9": "Truck"
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+ },
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+ "image_size": 224,
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+ "initializer_range": 0.02,
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+ "label2id": {
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+ "Airplane": 0,
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+ "Automobile": 1,
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+ "Bird": 2,
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+ "Cat": 3,
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+ "Deer": 4,
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+ "Dog": 5,
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+ "Frog": 6,
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+ "Horse": 7,
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+ "Ship": 8,
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+ "Truck": 9
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+ },
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+ "layer_norm_eps": 1e-05,
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+ "mlp_ratio": 4.0,
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+ "model_type": "swin",
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+ "num_channels": 3,
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+ "num_heads": [
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+ 3,
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+ 6,
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+ 12,
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+ 24
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+ ],
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+ "num_layers": 4,
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+ "out_features": [
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+ "stage4"
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+ ],
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+ "out_indices": [
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+ 4
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+ ],
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+ "patch_size": 4,
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+ "path_norm": true,
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+ "problem_type": "single_label_classification",
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+ "qkv_bias": true,
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+ "stage_names": [
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+ "stem",
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+ "stage1",
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+ "stage2",
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+ "stage3",
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+ "stage4"
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+ ],
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.35.0",
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+ "use_absolute_embeddings": false,
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+ "window_size": 7
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+ }
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preprocessor_config.json ADDED
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+ {
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+ "do_normalize": true,
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+ "do_rescale": true,
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+ "do_resize": true,
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+ "image_mean": [
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+ 0.485,
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+ 0.456,
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+ 0.406
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+ ],
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+ "image_processor_type": "ViTImageProcessor",
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+ "image_std": [
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+ 0.229,
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+ 0.224,
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+ 0.225
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+ ],
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+ "resample": 3,
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+ "rescale_factor": 0.00392156862745098,
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+ "size": {
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+ "height": 224,
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+ "width": 224
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+ }
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+ }
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