Comments (3)
Hi @Ggggfgjjjk, thanks for your interest in YOLO-World! You can modify the pre-training config to support your own datasets and load the pre-trained models. We suggest that the learning rate is set to 2e-4 and batch size is set to 16 for each device (8 GPUs are enough for fine-tuning). BTW, we will release the code/configs for fine-tuning YOLO-World on COCO and LVIS soon, and please stay tuned!
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Hi @Ggggfgjjjk, we provide a simple guide for fine-tuning YOLO-World in docs/fine-tuning. Hope it helps!
from yolo-world.
Thanks for your interest. If you have any questions about YOLO-World in the future, you're welcome to open a new issue.
from yolo-world.
Related Issues (20)
- the question about image_demo HOT 2
- I would like to ask how it uses YOLOv8 as the backbone in his code, and specifically in which Python file the forward computation for the backbone is performed? HOT 1
- yoloworld模型能否在Flickr30K Entities数据集上评估他的Phrase Grounding能力?就像GLIP模型那样 HOT 1
- About Pretrain Data's url.
- Question about onze-shot inference with image prompts HOT 1
- CC3M pretrain data HOT 4
- Abount CC3M Pseudo Annotations use HOT 2
- How to use zero-shot ability on Reparameterized YOLO-World?
- 微调结果上V2和V1差别很大 HOT 2
- 求救!求救!求救!求救!求救!!!!!!!如何获得推理之后的置信度,bbox坐标,类别信息 HOT 1
- ERROR [internal] load metadata for docker.io/nvidia/cuda:11.8.0-devel-ubuntu22.04
- 可以请教一下详细的环境配置流程,救救我 HOT 1
- Reparameterization need finetuning? HOT 1
- RuntimeError: CUDA error: CUDA-capable device(s) is/are busy or unavailable
- Number of Detected Bounding Boxes and Filtering Based on "score_thr", "nms_pre" and "topk" HOT 2
- Is there any difference between various ways to instantiate the model?
- 【求助】【急】基于独立数据集训练时,bbox_loss始终是0,模型无法预估 HOT 3
- Detection based on exemplary image
- Training results
- About finetune_coco config
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