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_Jun25
+  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_Jun25
+
+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: 0.0938
+- Validation Loss: 2.3960
+- Train Accuracy: 0.51
+- 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 |
+|:----------:|:---------------:|:--------------:|:-----:|
+| 0.9196     | 1.2060          | 0.38           | 0     |
+| 0.3792     | 1.4807          | 0.48           | 1     |
+| 0.2729     | 1.7396          | 0.45           | 2     |
+| 0.2006     | 2.4379          | 0.29           | 3     |
+| 0.1996     | 2.4795          | 0.36           | 4     |
+| 0.1734     | 2.7916          | 0.35           | 5     |
+| 0.1860     | 4.1270          | 0.09           | 6     |
+| 0.1490     | 2.7235          | 0.37           | 7     |
+| 0.1077     | 3.5380          | 0.26           | 8     |
+| 0.1173     | 2.7697          | 0.42           | 9     |
+| 0.1526     | 2.7868          | 0.42           | 10    |
+| 0.1161     | 3.1132          | 0.36           | 11    |
+| 0.1093     | 3.5738          | 0.33           | 12    |
+| 0.0884     | 3.1227          | 0.37           | 13    |
+| 0.0938     | 2.3960          | 0.51           | 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:e5a63bbe6e26be9fdaae1b0d968af2a864ec7a4504ade4f4c7707ecbf0bdba24
+size 343475896