Very very urgent help required Yolov8 classification issue about ultralytics HOT 5 OPEN

Hi there! It looks like your classification model is experiencing some inconsistency with the predictions. Here are a few suggestions that might help improve the stability of your results:

1. Review your dataset: Ensure that the labels are correctly assigned and that your dataset is balanced in terms of the distribution between the two classes.

2. Modify the Image Size: You might want to experiment with a larger image size than imgsz=64 if your computational resources allow. This can sometimes help the model capture more details and improve accuracy.

3. Fine-tune the Model: Since you have already trained for many epochs, consider using a slightly lower learning rate to fine-tune the model, which can sometimes help refine the predictions.

4. Model Evaluation: Evaluate your model’s confusion matrix to see if there's a pattern in misclassifications that can give more insights.

Here's a modified training command you might consider using:

!yolo task=classify mode=train model=yolov8m-cls.pt data='{DATA_DIR}' epochs=120 imgsz=128 optimizer=Adam dropout=0.2 lr=0.001

This uses a larger image size and a reduced learning rate, which might help in your case. Let's see if these changes influence the consistency of your predictions! 🚀

from ultralytics.

i have run the training command the command you gave to run it ----> !yolo task=classify mode=train model=yolov8m-cls.pt data='{DATA_DIR}' epochs=120 imgsz=128 optimizer=Adam dropout=0.2 lr=0.001 after using this command i am getting this error Traceback (most recent call last):
File "/usr/local/bin/yolo", line 8, in
sys.exit(entrypoint())
File "/usr/local/lib/python3.10/dist-packages/ultralytics/cfg/init.py", line 516, in entrypoint
check_dict_alignment(full_args_dict, overrides)
File "/usr/local/lib/python3.10/dist-packages/ultralytics/cfg/init.py", line 323, in check_dict_alignment
raise SyntaxError(string + CLI_HELP_MSG) from e
SyntaxError: 'lr' is not a valid YOLO argument. Similar arguments are i.e. ['lrf=0.01', 'lr0=0.01'].

Arguments received: ['yolo', 'task=classify', 'mode=train', 'model=yolov8m-cls.pt', 'data=/content/sheep_data', 'epochs=120', 'imgsz=128', 'optimizer=Adam', 'dropout=0.2', 'lr=0.001']. Ultralytics 'yolo' commands use the following syntax:

    yolo TASK MODE ARGS

    Where   TASK (optional) is one of {'segment', 'detect', 'classify', 'obb', 'pose'}
            MODE (required) is one of {'track', 'train', 'benchmark', 'export', 'val', 'predict'}
            ARGS (optional) are any number of custom 'arg=value' pairs like 'imgsz=320' that override defaults.
                See all ARGS at https://docs.ultralytics.com/usage/cfg or with 'yolo cfg'

1. Train a detection model for 10 epochs with an initial learning_rate of 0.01
    yolo train data=coco8.yaml model=yolov8n.pt epochs=10 lr0=0.01

2. Predict a YouTube video using a pretrained segmentation model at image size 320:
    yolo predict model=yolov8n-seg.pt source='https://youtu.be/LNwODJXcvt4' imgsz=320

3. Val a pretrained detection model at batch-size 1 and image size 640:
    yolo val model=yolov8n.pt data=coco8.yaml batch=1 imgsz=640

4. Export a YOLOv8n classification model to ONNX format at image size 224 by 128 (no TASK required)
    yolo export model=yolov8n-cls.pt format=onnx imgsz=224,128

6. Explore your datasets using semantic search and SQL with a simple GUI powered by Ultralytics Explorer API
    yolo explorer

5. Run special commands:
    yolo help
    yolo checks
    yolo version
    yolo settings
    yolo copy-cfg
    yolo cfg

@glenn-jocher @RizwanMunawar @AyushExel kindly help as earliest as possible because currently my work has been stucked it would be grateful if you could help me out with this

from ultralytics.

Hey there! 👋 It looks like there’s a small mix-up with the argument for the learning rate. In YOLOv8 CLI, the learning rate should be specified as lr0 instead of lr.

You can correct your command as follows:

!yolo task=classify mode=train model=yolov8m-cls.pt data='{DATA_DIR}' epochs=120 imgsz=128 optimizer=Adam dropout=0.2 lr0=0.001

Give this a try and let me know if it resolves the issue! If you run into anything else, feel free to reach out. Happy training! 🚀

from ultralytics.

Okay sure I will try and let you know @glenn-jocher

from ultralytics.

@anut123 great! Looking forward to hearing how it goes! If you have any more questions or need further assistance, don't hesitate to ask. Happy coding! 😊

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