End of training

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: AlaaHussien/final_weather
+  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. -->
+
+# AlaaHussien/final_weather
+
+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: 0.2163
+- Validation Loss: 0.2833
+- Train Accuracy: 0.9228
+- Train Precision: 0.9236
+- Train Recall: 0.9228
+- Train F1: 0.9228
+- Epoch: 4
+
+## 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': 27445, '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 | Validation Loss | Train Accuracy | Train Precision | Train Recall | Train F1 | Epoch |
+|:----------:|:---------------:|:--------------:|:---------------:|:------------:|:--------:|:-----:|
+| 1.2256     | 0.6330          | 0.8958         | 0.8986          | 0.8958       | 0.8958   | 0     |
+| 0.5082     | 0.4391          | 0.9097         | 0.9112          | 0.9097       | 0.9099   | 1     |
+| 0.3426     | 0.3675          | 0.9075         | 0.9129          | 0.9075       | 0.9066   | 2     |
+| 0.2638     | 0.3435          | 0.9111         | 0.9155          | 0.9111       | 0.9108   | 3     |
+| 0.2163     | 0.2833          | 0.9228         | 0.9236          | 0.9228       | 0.9228   | 4     |
+
+
+### Framework versions
+
+- Transformers 4.51.3
+- 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": "dew",
+    "1": "fogsmog",
+    "2": "frost",
+    "3": "glaze",
+    "4": "hail",
+    "5": "lightning",
+    "6": "rain",
+    "7": "rainbow",
+    "8": "rime",
+    "9": "sandstorm",
+    "10": "snow"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "dew": 0,
+    "fogsmog": 1,
+    "frost": 2,
+    "glaze": 3,
+    "hail": 4,
+    "lightning": 5,
+    "rain": 6,
+    "rainbow": 7,
+    "rime": 8,
+    "sandstorm": 9,
+    "snow": 10
+  },
+  "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": "4.51.3"
+}

preprocessor_config.json

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+{
+  "do_convert_rgb": null,
+  "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 343497400