# Remote GPU Cluster YOLOv10 Training All Sweeps Result in \< null \>

**URL:** <https://community.wandb.ai/t/remote-gpu-cluster-yolov10-training-all-sweeps-result-in-null/9064>\
**Category:** W&B Help\
**Tags:** sweeps\
**Created:** [February 23, 2025, 9:02pm UTC](https://community.wandb.ai/t/remote-gpu-cluster-yolov10-training-all-sweeps-result-in-null/9064 "2025-02-23T21:02:00Z")\
**Posts on this page:** 1\
**Page:** 1

<div class="post-metadata">

**Author:** ![shkrum](https://avatars.discourse-cdn.com/v4/letter/s/a183cd/32.png) [@shkrum](https://community.wandb.ai/u/shkrum)\
**Post date:** [February 23, 2025, 9:02pm UTC](https://community.wandb.ai/t/remote-gpu-cluster-yolov10-training-all-sweeps-result-in-null/9064/1 "2025-02-23T21:02:00Z")

</div>

Hello, WandB Community!  
I run YOLOv10 training script on a remote GPU cluster and want to finetune hyperparameters before running the main model training.  
I run 20 sweeps and all of them result in \< null \> (see image below)

 ![sweeps](https://us1.discourse-cdn.com/flex020/uploads/wandb/original/2X/9/98ddf8c57d5142a9c7b0eef695f37c366deec9ad.png)

However, in my yolov10\_training/yolov10\_finetune\_LARD\_13/02\_19\_52/ I can see results.csv which are not null, see the image below

| epoch | time | train/box\_loss | train/cls\_loss | train/dfl\_loss | metrics/precision(B) | metrics/recall(B) | metrics/mAP50(B) | metrics/mAP50-95(B) | val/box\_loss | val/cls\_loss | val/dfl\_loss | lr/pg0 | lr/pg1 | lr/pg2 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | 165.006 | 2.91836 | 10.6008 | 1.95599 | 0.48503 | 0.276 | 0.28385 | 0.14981 | 3.57982 | 6.09934 | 2.40669 | 0.000663743 | 0.000663743 | 0.000663743 |
| 2 | 340.683 | 2.55896 | 4.95659 | 1.93792 | 0.59701 | 0.44838 | 0.43939 | 0.24511 | 3.36526 | 4.47328 | 2.29902 | 0.00106699 | 0.00106699 | 0.00106699 |
| 3 | 516.641 | 2.36457 | 2.97833 | 1.85849 | 0.5841 | 0.48533 | 0.4661 | 0.26107 | 3.38215 | 4.35041 | 2.25128 | 0.00120623 | 0.00120623 | 0.00120623 |
| 4 | 689.54 | 2.12222 | 2.12358 | 1.8063 | 0.58889 | 0.37333 | 0.40226 | 0.24237 | 3.13558 | 3.75161 | 2.21274 | 0.000812 | 0.000812 | 0.000812 |
| 5 | 865.638 | 1.82564 | 1.71369 | 1.77575 | 0.66677 | 0.45888 | 0.48731 | 0.2987 | 3.04279 | 3.14339 | 2.14769 | 0.000416 | 0.000416 | 0.000416 |

this is my train\_model.py:

import ultralytics  
import wandb  
from ultralytics import YOLO  
import sys  
import yaml  
import datetime  
import torch

if **name** == ‘ **main** ’:  
sys.stdout.reconfigure(encoding=‘utf-8’)  
ultralytics.checks()  
wandb.login(key=“my\_api\_key\_here”)

```
dataset = "LARD"
time = datetime.datetime.now().strftime("%d/%m_%H_%M")

sweep_configuration = {
    "method": "random",
    "name": "yolov10-sweep",
    "metric": {"name": "loss", "goal": "minimize"},
    "parameters": {
        "batch_size": {"values": [16, 32, 64]},
        "epochs": {"values": [5, 10, 15]},
        "lr": {"max": 0.1, "min": 0.0001},
    },
}

sweep_id = wandb.sweep(sweep=sweep_configuration, project="RLD-training")

def train_yolo():
    wandb.init(project="RLD-training", name=f"RLD_Train_{dataset}_{time}")
    
    config_file = "yolo/config/yolov10_config.yaml"
    config_data = {
        "train": "dataset/images/train",
        "val": "dataset/images/train",  
        "test": "dataset/images/test",
        "nc": 1,  
        "names": ["runway"] 
    }
    with open(config_file, "w") as f:
        yaml.dump(config_data, f)

    model = YOLO("yolo/weights/yolov10n.pt").to(torch.device("cuda"))
    model_path = "best_yolov10.pt"
    
    model.train(
        data="yolo/config/yolov10_config.yaml", 
        epochs=wandb.config.epochs,   
        batch=wandb.config.batch_size,    
        lr0=wandb.config.lr,        
        project="yolov10_training",
        name=f"yolov10_finetune_{dataset}_{time}",
    )

    model.save(model_path)
    wandb.log_model(model_path)

wandb.agent(sweep_id, function=train_yolo, count=10)
wandb.finish()

```

Please, help me fix the visualization of wandb sweeps.  
Regards,  
Yulian.