ChannelWise-Target | ayush-thakur Workspace – Weights & Biases

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Ayush-thakur's group workspace

Group: ChannelWise-Target

3

1-1

of 1

Tags

Notes

Train EfficientNetB0 by stacking target spectrograms channel-wise

Tags

effnetb0

full-channel

Author

State

Finished

Start time

June 9th, 2021 1:45:05 AM

Runtime

5m 51s

Tracked hours

5m 50s

Run path

ayush-thakur/kaggle-seti-exp/35f0g71y

OS

Linux-4.19.0-16-cloud-amd64-x86_64-with-debian-10.9

Python version

3.7.10

Command

SETI/train-seti-experiments.ipynb

System Hardware

CPU count	8
GPU count	1
GPU type	Tesla V100-SXM2-16GB

W&B CLI Version

0.10.31

Group

ChannelWise-Target

Job Type

train

Config parameters are your model's inputs. Learn more

▶
Config parameters:{} 14 keys
- architecture:
  "CNN"
- batch_size:
  64
- epochs:
  100
- group:
  "ChannelWise-Target"
- img_height:
  224
- img_width:
  224
- infra:
  "GCP"
- learning_rate:
  0.001
- model_name:
  "EffNetB0"
- num_folds:
  5
- num_labels:
  1
- seed:
  42
- train_val_split:
  0.2
- wandb_kernel:
  true

Summary metrics are your model's outputs. Learn more

▶
Summary metrics:{} 9 keys
- auc:
  0.9957096576690674
- best_epoch:
  12
- best_val_loss:
  0.23908136785030365
- epoch:
  17
- ▶
  graph:{} 4 keys
  - _type:
    "graph-file"
  - path:
    "media/graph/graph_summary_7c10e28a.graph.json"
  - sha256:
    "7c10e28a1b30d746624cded62c9f23fb75dc40e43a40b7b0950babb89a1b36d6"
  - size:
    985
- loss:
  0.07980848103761673
- Val AUC-ROC:
  0.8665245771408081
- val_auc:
  0.8614668846130371
- val_loss:
  0.24628296494483948

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

run-35f0g71y-history:v0

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