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End of training

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  1. README.md +58 -0
  2. config.json +46 -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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+ tags:
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+ - generated_from_keras_callback
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+ model-index:
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+ - name: codingwithboba/cifar_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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+ # codingwithboba/cifar_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: 0.1524
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+ - Validation Loss: 0.3447
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+ - Train Accuracy: 0.902
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+ - Epoch: 4
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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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 20000, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, '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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+ | 1.6641 | 0.9964 | 0.825 | 0 |
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+ | 0.7272 | 0.5292 | 0.904 | 1 |
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+ | 0.3683 | 0.4030 | 0.895 | 2 |
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+ | 0.2274 | 0.3136 | 0.924 | 3 |
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+ | 0.1524 | 0.3447 | 0.902 | 4 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.29.1
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+ - TensorFlow 2.12.0
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+ - Datasets 2.12.0
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+ - Tokenizers 0.13.3
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": "airplane",
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+ "1": "automobile",
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+ "2": "bird",
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+ "3": "cat",
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+ "4": "deer",
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+ "5": "dog",
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+ "6": "frog",
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+ "7": "horse",
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+ "8": "ship",
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+ "9": "truck"
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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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+ "airplane": "0",
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+ "automobile": "1",
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+ "bird": "2",
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+ "cat": "3",
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+ "deer": "4",
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+ "dog": "5",
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+ "frog": "6",
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+ "horse": "7",
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+ "ship": "8",
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+ "truck": "9"
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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": "4.29.1"
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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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