Push Keras model using huggingface_hub.

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
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+variables/variables.data-00000-of-00001 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,26 +1,7 @@
 ---
-license: apache-2.0
-base_model: google/vit-base-patch16-224-in21k
-tags:
-- generated_from_keras_callback
-model-index:
-- name: arieg/bw_spec_cls_100_00_noise_200
-  results: []
+library_name: keras
 ---
 
-<!-- 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. -->
-
-# arieg/bw_spec_cls_100_00_noise_200
-
-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: 0.0005
-- Train Sparse Categorical Accuracy: 1.0
-- Validation Loss: 0.0004
-- Validation Sparse Categorical Accuracy: 1.0
-- Epoch: 9
-
 ## Model description
 
 More information needed
@@ -38,28 +19,30 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- optimizer: {'name': 'AdamWeightDecay', 'clipnorm': 1.0, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 185040, '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
+| Hyperparameters | Value |
+| :-- | :-- |
+| 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 | 0.0010000000474974513 |
+| momentum | 0.0 |
+| nesterov | False |
+| training_precision | float32 |
+
 
-| Train Loss | Train Sparse Categorical Accuracy | Validation Loss | Validation Sparse Categorical Accuracy | Epoch |
-|:----------:|:---------------------------------:|:---------------:|:--------------------------------------:|:-----:|
-| 1.9258     | 0.9587                            | 0.6056          | 1.0                                    | 0     |
-| 0.2899     | 1.0                               | 0.1262          | 1.0                                    | 1     |
-| 0.0761     | 1.0                               | 0.0438          | 1.0                                    | 2     |
-| 0.0294     | 1.0                               | 0.0189          | 1.0                                    | 3     |
-| 0.0133     | 1.0                               | 0.0090          | 1.0                                    | 4     |
-| 0.0065     | 1.0                               | 0.0046          | 1.0                                    | 5     |
-| 0.0033     | 1.0                               | 0.0024          | 1.0                                    | 6     |
-| 0.0017     | 1.0                               | 0.0013          | 1.0                                    | 7     |
-| 0.0009     | 1.0                               | 0.0007          | 1.0                                    | 8     |
-| 0.0005     | 1.0                               | 0.0004          | 1.0                                    | 9     |
+ ## Model Plot
 
+<details>
+<summary>View Model Plot</summary>
 
-### Framework versions
+![Model Image](./model.png)
 
-- Transformers 4.35.0
-- TensorFlow 2.14.0
-- Datasets 2.14.6
-- Tokenizers 0.14.1
+</details>

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