diff --git a/src/cloudcasting/validation.py b/src/cloudcasting/validation.py
index efdb41d..2b52f23 100644
--- a/src/cloudcasting/validation.py
+++ b/src/cloudcasting/validation.py
@@ -2,6 +2,8 @@
 
 import importlib.util
 import inspect
+import logging
+import os
 import sys
 from collections.abc import Callable
 from functools import partial
@@ -43,6 +45,9 @@
 )
 from cloudcasting.utils import numpy_validation_collate_fn
 
+logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
+logger = logging.getLogger(__name__)
+
 # defined in manchester prize technical document
 WANDB_ENTITY = "manchester_prize"
 VIDEO_SAMPLE_DATES = [
@@ -243,6 +248,9 @@ def get_pix_function(
     # we probably want to accumulate metrics here instead of taking the mean of means!
     loop_steps = len(valid_dataloader) if batch_limit is None else batch_limit
 
+    info_str = f"Validating model on {loop_steps} batches..."
+    logger.info(info_str)
+
     for i, (X, y) in tqdm(enumerate(valid_dataloader), total=loop_steps):
         y_hat = model(X)
 
@@ -355,8 +363,16 @@ def validate(
         msg = f"Failed to run the model forward due to the following error: {err}"
         raise ValueError(msg) from err
 
-    # Login to wandb
-    wandb.login()
+    # grab api key from environment variable
+    wandb_api_key = os.environ.get("WANDB_API_KEY")
+
+    if not wandb_api_key:
+        msg = "WANDB_API_KEY environment variable not set. Attempting interactive login..."
+        logger.warning(msg)
+        wandb.login()
+    else:
+        logger.info("API key found. Logging in to WandB...")
+        wandb.login(key=wandb_api_key)
 
     # Set up the validation dataset
     valid_dataset = ValidationSatelliteDataset(