cnnrnn-sweep-5 | thesis Workspace – Weights & Biases

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Group: cnnrnn-sweep-5

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Tags

Notes

Author

State

Failed

Start time

May 7th, 2021 11:56:16 AM

Sweep

Runtime

10s

Tracked hours

-

Run path

nbvanting/thesis/7wnco6y8

OS

Linux-4.19.112+-x86_64-with-Ubuntu-18.04-bionic

Python version

3.7.10

Command

Thesis - Sweep Run.ipynb

System Hardware

CPU count	2
GPU count	1
GPU type	Tesla T4

W&B CLI Version

0.10.29

Group

Config parameters are your model's inputs. Learn more

▶
Config parameters:{} 26 keys
- activation_cnn:
  "relu"
- activation_gru:
  "tanh"
- batch_size:
  209
- cnn_lay_2:
  false
- cnn_lay_3:
  false
- cnn_layer_size_1:
  88
- cnn_layer_size_2:
  71
- cnn_layer_size_3:
  122
- dataset:
  "strib"
- dropout:
  0.10727328652638862
- epochs:
  25
- gru_lay_1:
  false
- gru_lay_2:
  true
- gru_layer_size_1:
  219
- gru_layer_size_2:
  34
- gru_layer_size_3:
  33
- kernelsize:
  3
- learning_rate:
  0.021740576834116496
- lookback:
  744
- momentum:
  0.8349192446685972
- num_cnn_layers:
  2
- num_features:
  9
- num_gru_layers:
  2
- optimizer:
  "sgd"
- splitmethod:
  "standard"
- splitrate:
  0.8

Summary metrics are your model's outputs. Learn more

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Check the summary metrics documentation for more information.