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: Entrnal_eyes_data_6_true_agoiment211_model
+  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. -->
+
+# Entrnal_eyes_data_6_true_agoiment211_model
+
+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: 0.1455
+- Train Accuracy: 0.9282
+- Train Top-3-accuracy: 0.9908
+- Validation Loss: 0.3319
+- Validation Accuracy: 0.9322
+- Validation Top-3-accuracy: 0.9914
+- Epoch: 6
+
+## 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': 434, '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 |
+|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
+| 1.1623     | 0.5608         | 0.8521               | 0.7419          | 0.7200              | 0.9394                    | 0     |
+| 0.5255     | 0.7824         | 0.9588               | 0.4509          | 0.8190              | 0.9701                    | 1     |
+| 0.3218     | 0.8454         | 0.9759               | 0.3839          | 0.8644              | 0.9803                    | 2     |
+| 0.2230     | 0.8794         | 0.9830               | 0.3494          | 0.8923              | 0.9852                    | 3     |
+| 0.1755     | 0.9022         | 0.9868               | 0.3445          | 0.9104              | 0.9882                    | 4     |
+| 0.1539     | 0.9173         | 0.9892               | 0.3343          | 0.9231              | 0.9901                    | 5     |
+| 0.1455     | 0.9282         | 0.9908               | 0.3319          | 0.9322              | 0.9914                    | 6     |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- TensorFlow 2.15.1
+- Datasets 3.0.0
+- 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": "DR",
+    "2": "Glaucoma",
+    "3": "RVO",
+    "4": "normal"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "Cataract": "0",
+    "DR": "1",
+    "Glaucoma": "2",
+    "RVO": "3",
+    "normal": "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": "4.44.2"
+}

tf_model.h5

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+size 343478968