wandb_quickstart_init_config_and_log_training_metrics.py

1import wandb
2import random
3
4# 1. Start a new run to track this script
5wandb.init(
6    # Set the project where this run will be logged
7    project="my-awesome-project",
8    # Track hyperparameters and run metadata
9    config={
10        "learning_rate": 0.02,
11        "architecture": "CNN",
12        "dataset": "CIFAR-100",
13        "epochs": 10,
14    },
15)
16
17# 2. Simulate a training loop
18epochs = 10
19offset = random.random() / 5
20for epoch in range(2, epochs):
21    acc = 1 - 2**-epoch - random.random() / epoch - offset
22    loss = 2**-epoch + random.random() / epoch + offset
23
24    # 3. Log metrics to visualize performance over time
25    wandb.log({"acc": acc, "loss": loss})
26
27# 4. [Optional] Finish the W&B run
28wandb.finish()