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/weather_classifier_model2
+  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/weather_classifier_model2
+
+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: 0.0700
+- Validation Loss: 0.2853
+- Train Accuracy: 0.9250
+- Train Precision: 0.9267
+- Train Recall: 0.9250
+- Train F1: 0.9248
+- Epoch: 19
+
+## 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': 109780, '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 |
+|:----------:|:---------------:|:--------------:|:---------------:|:------------:|:--------:|:-----:|
+| 1.2545     | 0.6449          | 0.8944         | 0.9010          | 0.8944       | 0.8907   | 0     |
+| 0.5392     | 0.3960          | 0.9177         | 0.9191          | 0.9177       | 0.9181   | 1     |
+| 0.3498     | 0.3183          | 0.9264         | 0.9271          | 0.9264       | 0.9263   | 2     |
+| 0.2787     | 0.2797          | 0.9323         | 0.9331          | 0.9323       | 0.9323   | 3     |
+| 0.2155     | 0.2695          | 0.9257         | 0.9279          | 0.9257       | 0.9260   | 4     |
+| 0.1899     | 0.3079          | 0.9126         | 0.9165          | 0.9126       | 0.9121   | 5     |
+| 0.1599     | 0.2749          | 0.9235         | 0.9259          | 0.9235       | 0.9241   | 6     |
+| 0.1470     | 0.2709          | 0.9243         | 0.9257          | 0.9243       | 0.9237   | 7     |
+| 0.1305     | 0.2566          | 0.9257         | 0.9263          | 0.9257       | 0.9259   | 8     |
+| 0.1131     | 0.2699          | 0.9257         | 0.9271          | 0.9257       | 0.9260   | 9     |
+| 0.1042     | 0.2719          | 0.9228         | 0.9240          | 0.9228       | 0.9229   | 10    |
+| 0.0977     | 0.2857          | 0.9199         | 0.9208          | 0.9199       | 0.9197   | 11    |
+| 0.0816     | 0.2592          | 0.9279         | 0.9294          | 0.9279       | 0.9281   | 12    |
+| 0.0894     | 0.2888          | 0.9228         | 0.9256          | 0.9228       | 0.9226   | 13    |
+| 0.1011     | 0.2978          | 0.9264         | 0.9287          | 0.9264       | 0.9264   | 14    |
+| 0.0756     | 0.2590          | 0.9330         | 0.9344          | 0.9330       | 0.9330   | 15    |
+| 0.0668     | 0.2863          | 0.9228         | 0.9255          | 0.9228       | 0.9235   | 16    |
+| 0.0650     | 0.2871          | 0.9264         | 0.9282          | 0.9264       | 0.9262   | 17    |
+| 0.0644     | 0.3003          | 0.9257         | 0.9279          | 0.9257       | 0.9261   | 18    |
+| 0.0700     | 0.2853          | 0.9250         | 0.9267          | 0.9250       | 0.9248   | 19    |
+
+
+### 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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+version https://git-lfs.github.com/spec/v1
+oid sha256:746d6d3bff64d9b0c61605750eacc7cccdb8d640422bc41c001f97eb71b48180
+size 343513784