End of training

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_keras_callback
+model-index:
+- name: aditnnda/felidae_klasifikasi
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information Keras had access to. You should
+probably proofread and complete it, then remove this comment. -->
+
+# aditnnda/felidae_klasifikasi
+
+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.
+It achieves the following results on the evaluation set:
+- Train Loss: 0.9213
+- Train Accuracy: 0.7869
+- Validation Loss: 0.8231
+- Validation Accuracy: 0.7869
+- Epoch: 9
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 1820, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
+- training_precision: float32
+
+### Training results
+
+| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
+|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
+| 1.6070     | 0.3770         | 1.5670          | 0.3770              | 0     |
+| 1.5299     | 0.6557         | 1.4816          | 0.6557              | 1     |
+| 1.4347     | 0.6066         | 1.3838          | 0.6066              | 2     |
+| 1.3535     | 0.6885         | 1.2822          | 0.6885              | 3     |
+| 1.2562     | 0.6885         | 1.1766          | 0.6885              | 4     |
+| 1.1829     | 0.7705         | 1.0732          | 0.7705              | 5     |
+| 1.1037     | 0.8033         | 0.9889          | 0.8033              | 6     |
+| 1.0444     | 0.8525         | 0.9204          | 0.8525              | 7     |
+| 0.9640     | 0.8197         | 0.8722          | 0.8197              | 8     |
+| 0.9213     | 0.7869         | 0.8231          | 0.7869              | 9     |
+
+
+### Framework versions
+
+- Transformers 4.35.1
+- TensorFlow 2.14.0
+- Datasets 2.14.6
+- Tokenizers 0.14.1

config.json

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+{
+  "_name_or_path": "google/vit-base-patch16-224-in21k",
+  "architectures": [
+    "ViTForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "encoder_stride": 16,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "Cheetah",
+    "1": "Leopard",
+    "2": "Lion",
+    "3": "Puma",
+    "4": "Tiger"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "Cheetah": "0",
+    "Leopard": "1",
+    "Lion": "2",
+    "Puma": "3",
+    "Tiger": "4"
+  },
+  "layer_norm_eps": 1e-12,
+  "model_type": "vit",
+  "num_attention_heads": 12,
+  "num_channels": 3,
+  "num_hidden_layers": 12,
+  "patch_size": 16,
+  "qkv_bias": true,
+  "transformers_version": "4.35.1"
+}

preprocessor_config.json

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+{
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_processor_type": "ViTImageProcessor",
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 224,
+    "width": 224
+  }
+}

tf_model.h5

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+size 343478968