cnn | broutonlab Overview – Weights & Biases

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Broutonlab's group workspace

Group: cnn

1-3

of 3

Tags

Notes

Author

State

Finished

Start time

May 4th, 2021 4:32:33 PM

Runtime

20s

Tracked hours

18s

Run path

broutonlab/first_steps/85mzzlqw

OS

Windows-10-10.0.19041-SP0

Python version

3.6.12

Command

Experiments management with Weights & Biases.ipynb

System Hardware

CPU count	12
GPU count	1
GPU type	NVIDIA 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:
  0.9474166631698608
- best_epoch:
  5
- best_val_loss:
  0.08945741167999804
- epoch:
  5
- ▶
  examples:{} 6 keys
- ▶
  graph:{} 4 keys
  - _type:
    "graph-file"
  - path:
    "media/graph/graph_summary_f87de240.graph.json"
  - sha256:
    "f87de240ae50e55aac95cf23dddd0e83402369ec23910aff026e5df963d43558"
  - size:
    1,251
- loss:
  0.1726387672275305
- val_accuracy:
  0.9735000133514404
- val_loss:
  0.08945741167999804

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

run-85mzzlqw-history:v0

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