Add model

.gitattributes

@@ -25,3 +25,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zstandard filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+model.png filter=lfs diff=lfs merge=lfs -text
+variables/variables.data-00000-of-00001 filter=lfs diff=lfs merge=lfs -text
+variables/variables.index filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,69 @@
+---
+library_name: keras
+tags:
+- structured-data-classification
+- imbalanced-classification
+---
+
+## 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': 'Adam', 'learning_rate': 0.01, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
+- training_precision: float32
+
+ ## Training Metrics
+
+| Epochs | Train Loss | Train Fn | Train Fp | Train Tn | Train Tp | Train Precision | Train Recall | Validation Loss | Validation Fn | Validation Fp | Validation Tn | Validation Tp | Validation Precision | Validation Recall |
+ |--- |--- |--- |--- |--- |--- |--- |--- |--- |--- |--- |--- |--- |--- |--- |
+| 1| 0.0|  14.0|  6202.0|  221227.0|  403.0|  0.061|  0.966|  0.043|  9.0|  622.0|  56264.0|  66.0|  0.096|  0.88| 
+| 2| 0.0|  3.0|  3514.0|  223915.0|  414.0|  0.105|  0.993|  0.025|  10.0|  528.0|  56358.0|  65.0|  0.11|  0.867| 
+| 3| 0.0|  2.0|  2419.0|  225010.0|  415.0|  0.146|  0.995|  0.014|  11.0|  283.0|  56603.0|  64.0|  0.184|  0.853| 
+| 4| 0.0|  3.0|  2482.0|  224947.0|  414.0|  0.143|  0.993|  0.027|  11.0|  340.0|  56546.0|  64.0|  0.158|  0.853| 
+| 5| 0.0|  2.0|  2295.0|  225134.0|  415.0|  0.153|  0.995|  0.034|  11.0|  245.0|  56641.0|  64.0|  0.207|  0.853| 
+| 6| 0.0|  3.0|  2239.0|  225190.0|  414.0|  0.156|  0.993|  0.037|  10.0|  495.0|  56391.0|  65.0|  0.116|  0.867| 
+| 7| 0.0|  2.0|  3095.0|  224334.0|  415.0|  0.118|  0.995|  0.011|  11.0|  194.0|  56692.0|  64.0|  0.248|  0.853| 
+| 8| 0.0|  4.0|  1844.0|  225585.0|  413.0|  0.183|  0.99|  0.035|  9.0|  429.0|  56457.0|  66.0|  0.133|  0.88| 
+| 9| 0.0|  1.0|  2119.0|  225310.0|  416.0|  0.164|  0.998|  0.012|  11.0|  167.0|  56719.0|  64.0|  0.277|  0.853| 
+| 10| 0.0|  3.0|  1539.0|  225890.0|  414.0|  0.212|  0.993|  0.013|  13.0|  144.0|  56742.0|  62.0|  0.301|  0.827| 
+| 11| 0.0|  6.0|  3444.0|  223985.0|  411.0|  0.107|  0.986|  0.039|  11.0|  394.0|  56492.0|  64.0|  0.14|  0.853| 
+| 12| 0.0|  4.0|  3818.0|  223611.0|  413.0|  0.098|  0.99|  0.03|  9.0|  523.0|  56363.0|  66.0|  0.112|  0.88| 
+| 13| 0.0|  7.0|  4482.0|  222947.0|  410.0|  0.084|  0.983|  0.059|  6.0|  1364.0|  55522.0|  69.0|  0.048|  0.92| 
+| 14| 0.0|  2.0|  3064.0|  224365.0|  415.0|  0.119|  0.995|  0.033|  9.0|  699.0|  56187.0|  66.0|  0.086|  0.88| 
+| 15| 0.0|  4.0|  3563.0|  223866.0|  413.0|  0.104|  0.99|  0.066|  8.0|  956.0|  55930.0|  67.0|  0.065|  0.893| 
+| 16| 0.0|  4.0|  2536.0|  224893.0|  413.0|  0.14|  0.99|  0.016|  9.0|  339.0|  56547.0|  66.0|  0.163|  0.88| 
+| 17| 0.0|  6.0|  2594.0|  224835.0|  411.0|  0.137|  0.986|  0.049|  8.0|  821.0|  56065.0|  67.0|  0.075|  0.893| 
+| 18| 0.0|  1.0|  1911.0|  225518.0|  416.0|  0.179|  0.998|  0.013|  8.0|  215.0|  56671.0|  67.0|  0.238|  0.893| 
+| 19| 0.0|  2.0|  1457.0|  225972.0|  415.0|  0.222|  0.995|  0.018|  7.0|  342.0|  56544.0|  68.0|  0.166|  0.907| 
+| 20| 0.0|  0.0|  1132.0|  226297.0|  417.0|  0.269|  1.0|  0.011|  10.0|  172.0|  56714.0|  65.0|  0.274|  0.867| 
+| 21| 0.0|  1.0|  840.0|  226589.0|  416.0|  0.331|  0.998|  0.008|  11.0|  100.0|  56786.0|  64.0|  0.39|  0.853| 
+| 22| 0.0|  1.0|  2124.0|  225305.0|  416.0|  0.164|  0.998|  0.075|  10.0|  350.0|  56536.0|  65.0|  0.157|  0.867| 
+| 23| 0.0|  2.0|  1457.0|  225972.0|  415.0|  0.222|  0.995|  0.03|  11.0|  242.0|  56644.0|  64.0|  0.209|  0.853| 
+| 24| 0.0|  5.0|  2761.0|  224668.0|  412.0|  0.13|  0.988|  0.297|  6.0|  2741.0|  54145.0|  69.0|  0.025|  0.92| 
+| 25| 0.0|  3.0|  2484.0|  224945.0|  414.0|  0.143|  0.993|  0.025|  10.0|  199.0|  56687.0|  65.0|  0.246|  0.867| 
+| 26| 0.0|  4.0|  4867.0|  222562.0|  413.0|  0.078|  0.99|  0.021|  18.0|  33.0|  56853.0|  57.0|  0.633|  0.76| 
+| 27| 0.0|  8.0|  4230.0|  223199.0|  409.0|  0.088|  0.981|  0.053|  9.0|  1541.0|  55345.0|  66.0|  0.041|  0.88| 
+| 28| 0.0|  9.0|  5305.0|  222124.0|  408.0|  0.071|  0.978|  0.026|  9.0|  398.0|  56488.0|  66.0|  0.142|  0.88| 
+| 29| 0.0|  5.0|  4846.0|  222583.0|  412.0|  0.078|  0.988|  0.242|  6.0|  7883.0|  49003.0|  69.0|  0.009|  0.92| 
+| 30| 0.0|  5.0|  5193.0|  222236.0|  412.0|  0.074|  0.988|  0.026|  7.0|  449.0|  56437.0|  68.0|  0.132|  0.907| 
+ ## Model Plot
+
+<details>
+<summary>View Model Plot</summary>
+
+![Model Image](./model.png)
+
+</details>

history.json

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