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Training in progress epoch 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: google/vit-base-patch16-224-in21k
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+ tags:
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+ - generated_from_keras_callback
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+ model-index:
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+ - name: dwiedarioo/vit-base-patch16-224-in21k-final2multibrainmri
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information Keras had access to. You should
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+ probably proofread and complete it, then remove this comment. -->
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+
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+ # dwiedarioo/vit-base-patch16-224-in21k-final2multibrainmri
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+
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+ This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Train Loss: 2.2785
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+ - Train Accuracy: 0.3948
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+ - Train Top-3-accuracy: 0.6296
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+ - Validation Loss: 1.8843
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+ - Validation Accuracy: 0.5767
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+ - Validation Top-3-accuracy: 0.8207
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+ - Epoch: 0
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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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+ - optimizer: {'inner_optimizer': {'module': 'transformers.optimization_tf', 'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 8200, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.8999999761581421, 'beta_2': 0.9990000128746033, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}, 'registered_name': 'AdamWeightDecay'}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
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+ - training_precision: mixed_float16
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+
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+ ### Training results
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+
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+ | Train Loss | Train Accuracy | Train Top-3-accuracy | Validation Loss | Validation Accuracy | Validation Top-3-accuracy | Epoch |
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+ |:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
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+ | 2.2785 | 0.3948 | 0.6296 | 1.8843 | 0.5767 | 0.8207 | 0 |
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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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+ - TensorFlow 2.14.0
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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": "google/vit-base-patch16-224-in21k",
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+ "architectures": [
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+ "ViTForImageClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.0,
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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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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "Schwannoma",
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+ "1": "Germinoma",
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+ "10": "Tuberculoma",
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+ "11": "Oligodendroglioma",
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+ "12": "Meningioma",
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+ "13": "_NORMAL",
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+ "14": "Ganglioglioma",
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+ "2": "Glioblastoma",
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+ "3": "Meduloblastoma",
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+ "4": "Neurocitoma",
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+ "5": "Papiloma",
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+ "6": "Astrocitoma",
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+ "7": "Carcinoma",
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+ "8": "Ependimoma",
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+ "9": "Granuloma"
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+ },
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+ "image_size": 224,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "label2id": {
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+ "Astrocitoma": "6",
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+ "Carcinoma": "7",
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+ "Ependimoma": "8",
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+ "Ganglioglioma": "14",
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+ "Germinoma": "1",
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+ "Glioblastoma": "2",
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+ "Granuloma": "9",
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+ "Meduloblastoma": "3",
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+ "Meningioma": "12",
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+ "Neurocitoma": "4",
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+ "Oligodendroglioma": "11",
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+ "Papiloma": "5",
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+ "Schwannoma": "0",
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+ "Tuberculoma": "10",
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+ "_NORMAL": "13"
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+ },
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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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+ "qkv_bias": true,
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+ "transformers_version": "4.35.0"
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+ }
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