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swin-tiny-patch4-window7-224-Mid-NonMidMarket-Classification

Image Classification
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Generated from Trainer
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  1. README.md +87 -0
  2. all_results.json +13 -0
  3. config.json +97 -0
  4. eval_results.json +8 -0
  5. model.safetensors +3 -0
  6. preprocessor_config.json +36 -0
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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: swin-tiny-patch4-window7-224-Mid-NonMidMarket-Classification
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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: 0.8425624321389794
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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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+ # swin-tiny-patch4-window7-224-Mid-NonMidMarket-Classification
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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: 0.4046
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+ - Accuracy: 0.8426
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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: 10
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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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+ | 0.5809 | 0.9884 | 64 | 0.5024 | 0.7937 |
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+ | 0.5326 | 1.9923 | 129 | 0.4402 | 0.8132 |
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+ | 0.4626 | 2.9961 | 194 | 0.4244 | 0.8284 |
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+ | 0.4778 | 4.0 | 259 | 0.4234 | 0.8274 |
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+ | 0.4109 | 4.9884 | 323 | 0.4197 | 0.8306 |
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+ | 0.3764 | 5.9923 | 388 | 0.4095 | 0.8295 |
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+ | 0.3725 | 6.9961 | 453 | 0.4046 | 0.8426 |
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+ | 0.3583 | 8.0 | 518 | 0.4109 | 0.8371 |
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+ | 0.3451 | 8.9884 | 582 | 0.4171 | 0.8350 |
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+ | 0.3351 | 9.8842 | 640 | 0.4153 | 0.8404 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.2
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+ - Tokenizers 0.19.1
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+ {
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+ "epoch": 9.884169884169884,
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+ "eval_accuracy": 0.8425624321389794,
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+ "eval_loss": 0.4046495258808136,
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+ "eval_runtime": 106.7707,
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+ "eval_samples_per_second": 8.626,
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+ "eval_steps_per_second": 0.272,
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+ "total_flos": 2.0360358039744737e+18,
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+ "train_loss": 0.45154881179332734,
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+ "train_runtime": 9581.2043,
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+ "train_samples_per_second": 8.649,
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+ "train_steps_per_second": 0.067
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+ }
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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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+ ],
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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": "Automobiles",
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+ "1": "Beauty_and_Wellness",
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+ "2": "Books_Stationary",
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+ "3": "Business___Professional_Services",
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+ "4": "Education",
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+ "5": "Entertainment",
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+ "6": "Food___Beverages",
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+ "7": "Fresh_Products",
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+ "8": "Fuel",
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+ "9": "Grocery_General_Store",
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+ "10": "Home_Services",
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+ "11": "Home_Utilities",
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+ "12": "Liquor_Alcohol",
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+ "13": "Medical_Health_Care",
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+ "14": "Office_Complex",
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+ "15": "Others_Miscellaneous",
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+ "16": "Retail_Outlets",
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+ "17": "Supermarket",
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+ "18": "Travels_Transport___Hospitality",
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+ "19": "Wholesaler_Distributor_Manufacturer_Godown"
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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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+ "Automobiles": 0,
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+ "Beauty_and_Wellness": 1,
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+ "Books_Stationary": 2,
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+ "Home_Utilities": 11,
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+ "Liquor_Alcohol": 12,
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+ "Medical_Health_Care": 13,
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+ "Office_Complex": 14,
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+ "Others_Miscellaneous": 15,
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+ "Retail_Outlets": 16,
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+ "Supermarket": 17,
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+ "Travels_Transport___Hospitality": 18,
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+ "Wholesaler_Distributor_Manufacturer_Godown": 19
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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": "4.41.2",
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+ "use_absolute_embeddings": false,
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+ "window_size": 7
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+ }
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