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End of training

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  1. README.md +69 -0
  2. config.json +30 -0
  3. preprocessor_config.json +22 -0
  4. tf_model.h5 +3 -0
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: amiguel/mri_classifier
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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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+ # amiguel/mri_classifier
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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: 0.0075
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+ - Validation Loss: 0.0023
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+ - Train Accuracy: 1.0
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+ - Epoch: 14
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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: {'name': 'AdamWeightDecay', 'learning_rate': 3e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
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+ - training_precision: float32
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+
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+ ### Training results
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+
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+ | Train Loss | Validation Loss | Train Accuracy | Epoch |
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+ |:----------:|:---------------:|:--------------:|:-----:|
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+ | 0.1501 | 0.0619 | 0.9845 | 0 |
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+ | 0.0524 | 0.0825 | 0.9733 | 1 |
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+ | 0.0324 | 0.1416 | 0.9494 | 2 |
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+ | 0.0243 | 0.0327 | 0.9887 | 3 |
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+ | 0.0258 | 0.0095 | 0.9986 | 4 |
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+ | 0.0166 | 0.0069 | 0.9986 | 5 |
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+ | 0.0342 | 0.0126 | 0.9958 | 6 |
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+ | 0.0131 | 0.0057 | 0.9986 | 7 |
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+ | 0.0120 | 0.0037 | 0.9986 | 8 |
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+ | 0.0163 | 0.0055 | 0.9972 | 9 |
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+ | 0.0083 | 0.0018 | 1.0 | 10 |
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+ | 0.0128 | 0.0027 | 0.9986 | 11 |
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+ | 0.0070 | 0.0020 | 1.0 | 12 |
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+ | 0.0083 | 0.0014 | 1.0 | 13 |
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+ | 0.0075 | 0.0023 | 1.0 | 14 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.4
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+ - TensorFlow 2.15.0
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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": "notumor",
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+ "1": "tumor"
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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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+ "notumor": "0",
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+ "tumor": "1"
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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": "4.42.4"
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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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+ 0.5,
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+ 0.5,
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+ 0.5
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+ ],
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+ "image_processor_type": "ViTImageProcessor",
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+ "image_std": [
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+ 0.5,
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+ 0.5,
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+ 0.5
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+ ],
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+ "resample": 2,
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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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+ }
tf_model.h5 ADDED
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