cnn | swel4ik Overview – Weights & Biases

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Group: cnn

1-2

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Tags

Notes

Author

State

Finished

Start time

April 2nd, 2021 12:16:14 PM

Runtime

54s

Tracked hours

53s

Run path

swel4ik/first_steps/x4n1gflg

OS

Windows-10-10.0.19041-SP0

Python version

3.6.12

Command

w%B.ipynb

System Hardware

CPU count	12
GPU count	1
GPU type	GeForce GTX 1650 Ti

W&B CLI Version

0.10.24

Group

Config parameters are your model's inputs. Learn more

▶
Config parameters:{} 12 keys
- activation_1:
  "relu"
- activation_out:
  "softmax"
- batch_size:
  32
- conv_1:
  16
- conv_2:
  32
- dropout:
  0.7
- epoch:
  6
- ▶
  kernel_size:[] 2 items
  - 0:
    3
  - 1:
    3
- loss:
  "sparse_categorical_crossentropy"
- metric:
  "accuracy"
- optimizer:
  "adam"
- ▶
  pool_size:[] 2 items
  - 0:
    2
  - 1:
    2

Summary metrics are your model's outputs. Learn more

▶
Summary metrics:{} 9 keys
- accuracy:
  0.949999988079071
- best_epoch:
  5
- best_val_loss:
  0.08379972720518708
- epoch:
  5
- ▶
  examples:{} 6 keys
- ▶
  graph:{} 4 keys
  - _type:
    "graph-file"
  - path:
    "media/graph/graph_summary_1dea4691.graph.json"
  - sha256:
    "1dea469148b28d14b4ffd7618a03bc8af598825ed4484997f4e231ad2a696082"
  - size:
    1,251
- loss:
  0.1594740716392795
- val_accuracy:
  0.9745000004768372
- val_loss:
  0.08379972720518708

This run produced these artifacts as outputs. Total: 1. Learn more

run-x4n1gflg-history:v0

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