<p>I have a question about training object detection models especially using the YOLOv7 algorithm.</p>
<p>I use a <a href="https://universe.roboflow.com/roboflow-100/soccer-players-5fuqs" rel="nofollow noreferrer">Soccer Players Dataset</a> from the Roboflow. The dataset is very unbalanced.</p>
<p>I trained the model using basic hyperparameters and it detects all objects on images but the predicted label is invalid. The model predicts everything as a player (but for example one person on an image is a referee).</p>
<p>How can I improve label prediction accuracy?</p>

CC BY-SA 4.0
2023-01-29T23:52:00.707Z
Maybe you should explain for how long you trained your model and what these basic hyper-parameters are.
nbro
CC BY-SA 4.0
2023-01-30T08:24:19.533Z
I trained for 100 epochs, Basic hyperparameters are from the hyp.scratch.custom.yaml, but I wasn't changed values in this file.
ofevy
<object-detection><pytorch><object-recognition><yolo>
YOLOv7 fine tuning with unbalanced dataset
ofevy
# YOLOv7 fine tuning with unbalanced dataset

(Asked by: username_0 on 2023-01-29)

I have a question about training object detection models especially using the YOLOv7 algorithm.

I use a [Soccer Players Dataset](https://universe.roboflow.com/roboflow-100/soccer-players-5fuqs) from the Roboflow. The dataset is very unbalanced.

I trained the model using basic hyperparameters and it detects all objects on images but the predicted label is invalid. The model predicts everything as a player (but for example one person on an image is a referee).

How can I improve label prediction accuracy?

**Tags:** object-detection, pytorch, object-recognition, yolo

> **Comments:**
> **username_1**: Maybe you should explain for how long you trained your model and what these basic hyper-parameters are.  
> **username_0**: I trained for 100 epochs, Basic hyperparameters are from the hyp.scratch.custom.yaml, but I wasn't changed values in this file.  

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## 0 answers

