Upload TFViTForImageClassification

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_keras_callback
+model-index:
+- name: glacoma_andOther_model1
+  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. -->
+
+# glacoma_andOther_model1
+
+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: 0.0575
+- Train Accuracy: 0.9403
+- Train Top-3-accuracy: 0.9984
+- Validation Loss: 0.2329
+- Validation Accuracy: 0.9442
+- Validation Top-3-accuracy: 0.9985
+- Epoch: 5
+
+## 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': 1266, '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 | Train Top-3-accuracy | Validation Loss | Validation Accuracy | Validation Top-3-accuracy | Epoch |
+|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
+| 0.5871     | 0.7237         | 0.9808               | 0.3574          | 0.8358              | 0.9916                    | 0     |
+| 0.2606     | 0.8643         | 0.9942               | 0.2785          | 0.8821              | 0.9958                    | 1     |
+| 0.1643     | 0.8966         | 0.9966               | 0.2490          | 0.9077              | 0.9971                    | 2     |
+| 0.1114     | 0.9168         | 0.9975               | 0.2644          | 0.9239              | 0.9978                    | 3     |
+| 0.0797     | 0.9301         | 0.9980               | 0.2345          | 0.9353              | 0.9982                    | 4     |
+| 0.0575     | 0.9403         | 0.9984               | 0.2329          | 0.9442              | 0.9985                    | 5     |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- TensorFlow 2.15.0
+- Datasets 2.21.0
+- Tokenizers 0.19.1

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": "cataract",
+    "1": "diabetic_retinopathy",
+    "2": "glaucoma",
+    "3": "normal"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "cataract": "0",
+    "diabetic_retinopathy": "1",
+    "glaucoma": "2",
+    "normal": "3"
+  },
+  "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": "4.44.2"
+}

tf_model.h5

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+oid sha256:9c1bb323c226fba91cc26c0bb48465efb2024c528fc55b461a40d9947b31b963
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