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: VIT_fourclass_classifier
+  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. -->
+
+# VIT_fourclass_classifier
+
+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: 0.0945
+- Validation Loss: 1.7241
+- Train Accuracy: 0.6974
+- Epoch: 14
+
+## 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': 'SGD', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': np.float32(0.01), 'momentum': 0.0, 'nesterov': False}
+- training_precision: float32
+
+### Training results
+
+| Train Loss | Validation Loss | Train Accuracy | Epoch |
+|:----------:|:---------------:|:--------------:|:-----:|
+| 0.7946     | 1.1484          | 0.6272         | 0     |
+| 0.3246     | 1.1792          | 0.6769         | 1     |
+| 0.2266     | 1.2812          | 0.6842         | 2     |
+| 0.1841     | 1.5085          | 0.6754         | 3     |
+| 0.1589     | 1.4224          | 0.6944         | 4     |
+| 0.1244     | 1.4229          | 0.6901         | 5     |
+| 0.1174     | 1.4858          | 0.6784         | 6     |
+| 0.1133     | 1.4221          | 0.6974         | 7     |
+| 0.1026     | 1.4273          | 0.7003         | 8     |
+| 0.1083     | 1.5406          | 0.7003         | 9     |
+| 0.1038     | 1.6223          | 0.6974         | 10    |
+| 0.0876     | 1.5613          | 0.6959         | 11    |
+| 0.1018     | 1.4540          | 0.7149         | 12    |
+| 0.0808     | 1.4853          | 0.7193         | 13    |
+| 0.0945     | 1.7241          | 0.6974         | 14    |
+
+
+### Framework versions
+
+- Transformers 4.52.4
+- TensorFlow 2.18.0
+- Datasets 3.6.0
+- Tokenizers 0.21.1

config.json

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+{
+  "architectures": [
+    "ViTForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "encoder_stride": 16,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "glioma_tumor",
+    "1": "meningioma_tumor",
+    "2": "no_tumor",
+    "3": "pituitary_tumor"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "glioma_tumor": "0",
+    "meningioma_tumor": "1",
+    "no_tumor": "2",
+    "pituitary_tumor": "3"
+  },
+  "layer_norm_eps": 1e-12,
+  "model_type": "vit",
+  "num_attention_heads": 12,
+  "num_channels": 3,
+  "num_hidden_layers": 12,
+  "patch_size": 16,
+  "pooler_act": "tanh",
+  "pooler_output_size": 768,
+  "qkv_bias": true,
+  "transformers_version": "4.52.4"
+}

tf_model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f53ca4dd60a996b67e3d9967bc174fb0c4cc55c243a3de2a0836ba865df287a1
+size 343475896