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End of training

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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: google/vit-base-patch16-224
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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: UL_interior_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: validation
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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: 0.5875912408759124
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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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+ # UL_interior_classification
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+
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+ This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.2517
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+ - Accuracy: 0.5876
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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: 7
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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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+ | 2.7547 | 0.9811 | 13 | 2.3422 | 0.3285 |
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+ | 1.7119 | 1.9623 | 26 | 1.8850 | 0.4964 |
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+ | 1.249 | 2.9434 | 39 | 1.5653 | 0.5292 |
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+ | 0.8838 | 4.0 | 53 | 1.3675 | 0.5693 |
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+ | 0.8896 | 4.9811 | 66 | 1.2907 | 0.5803 |
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+ | 0.7262 | 5.9623 | 79 | 1.2625 | 0.5803 |
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+ | 0.6817 | 6.8679 | 91 | 1.2517 | 0.5876 |
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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 2.20.0
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+ - Tokenizers 0.19.1
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+ {
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+ "_name_or_path": "google/vit-base-patch16-224",
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+ "ViTForImageClassification"
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+ "encoder_stride": 16,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.0,
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+ "id2label": {
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+ "0": "bicycle_storage",
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+ "1": "building_interiors",
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+ "2": "cinema_room",
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+ "3": "communal_lounge",
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+ "4": "dining_area",
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+ "5": "entertainment_area",
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+ "6": "fitness_room",
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+ "7": "games_area",
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+ "8": "gym",
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+ "9": "laundry_area",
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+ "10": "living_area",
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+ "11": "living_area_shared_kitchen",
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+ "12": "meeting_room",
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+ "13": "parking",
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+ "14": "reception",
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+ "15": "rooftoop_area",
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+ "16": "storage_lockers",
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+ "17": "study_area",
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+ "18": "swimming_pool"
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+ },
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+ "image_size": 224,
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+ "layer_norm_eps": 1e-12,
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+ "model_type": "vit",
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+ "num_attention_heads": 12,
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+ "num_channels": 3,
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+ "num_hidden_layers": 12,
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+ "patch_size": 16,
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+ "problem_type": "single_label_classification",
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+ "qkv_bias": true,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.41.2"
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+ }
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