wandb_quickstart_training_loop_with_metric_logging.py

1import wandb
2import random
3
4# 1. Start a W&B Run
5run = wandb.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        "epochs": 10,
12    },
13)
14
15# 2. Simulate a training loop
16epochs = 10
17offset = random.random() / 5
18for epoch in range(2, epochs):
19    acc = 1 - 2**-epoch - random.random() / epoch - offset
20    loss = 2**-epoch + random.random() / epoch + offset
21
22    # 3. Log metrics to W&B
23    wandb.log({"acc": acc, "loss": loss})
24
25# Mark the run as finished
26wandb.finish()