
## 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': 0.001, '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 Accuracy | Validation Loss | Validation Accuracy |
 |--- |--- |--- |--- |--- |
| 1| 0.315|  0.915|  0.066|  0.983| 
| 2| 0.089|  0.982|  0.049|  0.99| 
| 3| 0.078|  0.987|  0.084|  0.983| 
| 4| 0.059|  0.983|  0.033|  0.993| 
| 5| 0.042|  0.99|  0.053|  0.99| 
| 6| 0.042|  0.996|  0.019|  0.993| 
| 7| 0.013|  0.999|  0.067|  0.987| 
| 8| 0.055|  0.988|  0.049|  0.99| 
| 9| 0.005|  1.0|  0.039|  0.993| 
| 10| 0.005|  1.0|  0.038|  0.99| 
| 11| 0.039|  0.995|  0.214|  0.97| 
| 12| 0.008|  1.0|  0.039|  0.99| 
| 13| 0.002|  1.0|  0.047|  0.993| 
| 14| 0.016|  0.999|  0.057|  0.99| 
| 15| 0.046|  0.993|  0.026|  0.997| 
| 16| 0.002|  1.0|  0.06|  0.99| 
 ## Model Plot

<details>
<summary>View Model Plot</summary>

![Model Image](./model.png)

</details>
{"library_name": "keras", "tags": ["computer-vision", "classification", "multiple-instance-learning "]}
keras tensorboard computer-vision classification multiple-instance-learning  has_space region:us
TAGS
#keras #tensorboard #computer-vision #classification #multiple-instance-learning  #has_space #region-us 

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': 0.001, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32


Training Metrics
----------------



Model Plot
----------



View Model Plot
!Model Image



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'learning\_rate': 0.001, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32


Training Metrics
----------------



Model Plot
----------



View Model Plot
!Model Image
TAGS
#keras #tensorboard #computer-vision #classification #multiple-instance-learning  #has_space #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'learning\_rate': 0.001, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32


Training Metrics
----------------



Model Plot
----------



View Model Plot
!Model Image
passage: TAGS
#keras #tensorboard #computer-vision #classification #multiple-instance-learning  #has_space #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'learning\_rate': 0.001, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32


Training Metrics
----------------



Model Plot
----------



View Model Plot
!Model Image