diff --git a/dags/map_reproducibility/nemo_gpt3.py b/dags/map_reproducibility/nemo_gpt3.py
index 85f7b006..3fbde9e7 100644
--- a/dags/map_reproducibility/nemo_gpt3.py
+++ b/dags/map_reproducibility/nemo_gpt3.py
@@ -44,6 +44,12 @@
 # Run once a day at 2 pm UTC (6 am PST)
 SCHEDULED_TIME = "0 14 * * *" if composer_env.is_prod_env() else None
 
+MODEL_ID = "gpt3-175b"
+BATCH_SIZE = 2048
+NUM_ACCELERATORS = 256
+PRECISION = "fp8"
+ACCELERATOR_TYPE = "h100"
+
 
 @task
 def run_aotc_workload():
@@ -62,6 +68,7 @@ def run_aotc_workload():
 
   with tempfile.TemporaryDirectory() as tmpdir:
     hook = SubprocessHook()
+    # TODO(gunjanjalori): clone recipe first and extract params
     result = hook.run_command(
         [
             "bash",
@@ -78,7 +85,13 @@ def run_aotc_workload():
                 + helm_apply_cmds()
                 + wait_for_jobs_cmds()
                 + copy_bucket_cmds()
-                + get_metrics_cmds()
+                + get_metrics_cmds(
+                    BATCH_SIZE,
+                    NUM_ACCELERATORS,
+                    PRECISION,
+                    MODEL_ID,
+                    ACCELERATOR_TYPE,
+                )
                 + cleanup_cmds()
                 + get_aotc_repo()
             ),
@@ -93,7 +106,7 @@ def run_aotc_workload():
     print(f"Base path in python: {python_base_path}")
     print(f"python to bq: {python_path_to_bq_writer}")
 
-    yaml_file_path = "reproducible-benchmark-recipes/projects/gpu-recipes/training/a3mega/gpt3-175b/nemo-pretraining-gke/values.yaml"
+    value_yaml_path = "reproducible-benchmark-recipes/projects/gpu-recipes/training/a3mega/gpt3-175b/nemo-pretraining-gke/values.yaml"
     config_yaml_path = "reproducible-benchmark-recipes/projects/gpu-recipes/src/frameworks/a3mega/nemo-configs/gpt3-175b-256gpus-fp8.yaml"
 
     (
@@ -103,7 +116,7 @@ def run_aotc_workload():
         precision,
         seq_length,
         max_steps,
-    ) = extract_run_details(tmpdir, yaml_file_path, config_yaml_path)
+    ) = extract_run_details(tmpdir, value_yaml_path, config_yaml_path)
     print(
         f"batch size: {global_batch_size}, number of nodes: {number_of_nodes}"
     )
diff --git a/dags/map_reproducibility/utils.py b/dags/map_reproducibility/utils.py
index 908d1fa4..5310f7b1 100644
--- a/dags/map_reproducibility/utils.py
+++ b/dags/map_reproducibility/utils.py
@@ -128,17 +128,18 @@ def copy_bucket_cmds():
   return copy_bucket_contents
 
 
-def get_metrics_cmds():
+def get_metrics_cmds(
+    batch_size, num_accelerators, precision, model_id, accelertator_type
+):
   # TODO(gunjanj007): get these parameters from the recipe
   cmds = (
-      # "METRICS_FILE=$COMPLETE_JOB_NAME/metrics.txt",
       "METRICS_FILE=metrics.txt",
       "python3 process_training_results.py --file"
-      " dllogger.json --batch_size 2048 "
-      "--num_accelerators 256 "
-      "--precision fp8  "
-      "--model_type gpt3-175b "
-      "--accelerator_type h100 | "
+      f" dllogger.json --batch_size {batch_size} "
+      f"--num_accelerators {num_accelerators} "
+      f"--precision {precision}  "
+      f"--model_type {model_id} "
+      f"--accelerator_type {accelertator_type} | "
       "gsutil cp - $METRICS_FILE",
       'echo "METRICS_FILE=${METRICS_FILE}"',
   )