Bug in validation dataset name

[donhuvy]

Bug in validation dataset name.

Dear team,

At this link https://platform.ultralytics.com/ultralytics/yolo26 , I think this is a bug. I tried 10 different file names for the datasets, but I was unsuccessful.

Please see the attached file.

Best regards,

[UltralyticsAssistant]

👋 Hello @donhuvy, thank you for reporting this potential bug in the validation dataset name workflow on the Ultralytics Platform 🚀 This is an automated response to help gather the right details quickly, and an Ultralytics engineer will also assist you soon.

We recommend a quick visit to the Docs where you can find many Python and CLI usage examples and where many of the most common questions may already be answered.

Since this appears to be a 🐛 Bug Report, please provide a minimum reproducible example to help us debug it. 🙏
Useful details include:

• The exact dataset names you tried
• Whether the issue happens for training datasets, validation datasets, or both
• The file type and structure of the uploaded dataset
• Any error messages shown in the UI
• A short step-by-step sequence to reproduce the problem consistently
• Additional screenshots if available

If this is a custom training ❓ Question, please provide as much information as possible, including dataset image examples and training logs, and verify you are following our Tips for Best Training Results.

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[glenn-jocher]

If this is a dataset YAML issue rather than a Platform UI bug, the validation split must be defined as val: in data.yaml alongside train:; validation: is auto-mapped, but valid: or custom split keys are not, per the dataset YAML checks, so please paste your exact data.yaml and the UI error text here as text and we’ll check it.

[donhuvy]

Thank you, bro. I know you YOLO's founder 👍 . I tried to upload my dataset (object detection), Is 5 GB and 2000 images (30200 images objects) ok for uploading? Maybe you consider make user interace more easier to understand. I did not know what is next step . I train model at local success, just try to upload online for impression my master thesis supervisor.

My data set

for this mobile app https://score.donhuvy.com/

[banu4prasad]

Is 5 GB and 2000 images (30200 images objects) ok for uploading?

Ig the upload limit is 10 GB on platform.ultralytics.com

just try to upload online for impression my master thesis supervisor.

For that create a folder like <multi_choice....> and upload ur trained model here first then u can deploy later

[glenn-jocher]

Yes, 5 GB and 2000 images are within the supported Platform limits as long as your dataset is packaged in a valid YOLO structure with a data.yaml plus train and val splits; after upload finishes processing, open the dataset and click New Model to start training, and the Platform dataset guide and quickstart show the expected layout and next steps.

[donhuvy]

[donhuvy]

I have file C:\Users\ADMIN\PyCharmMiscProject\brain-tumor.yaml has full content:

# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license

# Brain-tumor dataset by Ultralytics
# Documentation: https://docs.ultralytics.com/datasets/detect/brain-tumor/
# Example usage: yolo train data=brain-tumor.yaml
# parent
# ├── ultralytics
# └── datasets
#     └── brain-tumor ← downloads here (4.21 MB)

# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: brain-tumor # dataset root dir
train: images/train # train images (relative to 'path') 893 images
val: images/val # val images (relative to 'path') 223 images
test: # test images (relative to 'path')

# Classes
names:
  0: A
  1: B
  2: C
  3: D

# Download script/URL (optional)
download: https://github.com/ultralytics/assets/releases/download/v0.0.0/brain-tumor.zip

[glenn-jocher]

The YAML filename is not the issue here; per the Brain Tumor dataset docs, the official brain-tumor.yaml is a 2-class dataset (negative, positive) with train: images/train and val: images/val, so your names block with 4 classes will only work if your label files also use class IDs 0-3. After correcting the YAML/labels, delete any labels/*.cache files and retry, and if it still fails please paste the full text error plus yolo checks output.