Checking Your Customization Job Metrics#
After completing a customization job, you can monitor its performance through training and validation metrics. There are three ways to access these metrics:
Using the API
Through MLflow (optional)
Using Weights & Biases (optional)
Note
The time to complete this tutorial is approximately 10 minutes.
Available Metrics#
Each customization job tracks two key metrics:
Training Loss: Calculated during training, logged every 10 steps
Validation Loss: Calculated during validation, logged every epoch
Prerequisites#
Completed customization job with a valid ID
(Optional) Access to NeMo with MLflow tracking enabled
(Optional) Weights & Biases account and API key for enhanced visualization
Viewing Your Metrics#
Using the API#
Get metrics with a simple API call:
curl ${CUST_HOSTNAME}/v1/customization/jobs/${customizationID}/status
The response includes timestamped training and validation loss values.
Using MLflow#
Access the MLflow UI (typically available through your cluster’s external URL)
Find your experiment using the customization ID
Select the run to view metrics under “Metrics”
Using Weights & Biases#
To enable W&B integration, include your API key when creating a customization job in the call header:
curl --location "https://${CUST_HOSTNAME}/v1/customization/jobs" \
--header 'Content-Type: application/json' \
--header 'Accept: application/json' \
--header 'wandb-api-key: <WANDB_API_KEY>' \
--data '{
"config": "meta/llama-3.1-8b-instruct",
"dataset": {"name": "test-dataset"},
"hyperparameters": {
"training_type": "sft",
"finetuning_type": "lora",
"epochs": 10,
"batch_size": 16,
"learning_rate": 0.0001,
"lora": {
"adapter_dim": 8,
}
}'
Then view your results at wandb.ai under the nvidia-nemo-customizer
project.
Note
The W&B integration is optional. When enabled, we’ll send training metrics to W&B using your API key. While we encrypt your API key and don’t log it internally, please review W&B’s terms of service before use.