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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-large-patch32-224-in21k
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+ tags:
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+ - image-classification
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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: vit-large-brain-xray
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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: sartajbhuvaji/Brain-Tumor-Classification
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+ type: imagefolder
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+ config: default
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+ split: Testing
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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: 0.7081218274111675
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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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+ # vit-large-brain-xray
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+
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+ This model is a fine-tuned version of [google/vit-large-patch32-224-in21k](https://huggingface.co/google/vit-large-patch32-224-in21k) on the sartajbhuvaji/Brain-Tumor-Classification dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.0935
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+ - Accuracy: 0.7081
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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: 0.0002
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+ - train_batch_size: 16
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+ - eval_batch_size: 8
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+ - seed: 42
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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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+ - num_epochs: 4
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+ - mixed_precision_training: Native AMP
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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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+ | 0.2144 | 0.5556 | 100 | 1.2679 | 0.6269 |
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+ | 0.1091 | 1.1111 | 200 | 1.0935 | 0.7081 |
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+ | 0.1078 | 1.6667 | 300 | 1.1237 | 0.7589 |
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+ | 0.016 | 2.2222 | 400 | 1.2356 | 0.7563 |
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+ | 0.0095 | 2.7778 | 500 | 1.2316 | 0.7589 |
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+ | 0.0066 | 3.3333 | 600 | 1.3165 | 0.7589 |
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+ | 0.0161 | 3.8889 | 700 | 1.3412 | 0.7614 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.1
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.19.0
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+ - Tokenizers 0.19.1
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+ {
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+ "total_flos": 3.16768696086528e+18,
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+ "train_loss": 0.15098576029348704,
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+ "train_runtime": 924.305,
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+ "train_steps_per_second": 0.779
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+ }
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+ {
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+ "_name_or_path": "google/vit-large-patch32-224-in21k",
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+ "architectures": [
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+ "ViTForImageClassification"
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+ ],
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+ "hidden_dropout_prob": 0.0,
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+ "id2label": {
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+ "0": "glioma_tumor",
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+ "1": "meningioma_tumor",
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+ "2": "no_tumor",
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+ "3": "pituitary_tumor"
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+ "glioma_tumor": "0",
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+ "pituitary_tumor": "3"
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+ "layer_norm_eps": 1e-12,
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+ "model_type": "vit",
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+ "num_attention_heads": 16,
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+ "patch_size": 32,
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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": "4.40.1"
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+ }
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