How to train using custom model

[LeMosquitar]

Alright, I have seen the threads in issues before coming here. And, thank you everyone for your efforts.
Here is the thing, I consulted https://yolo-docs.readthedocs.io/en/latest/1_tutorials/0_allIn1.html. Followed the folder structure and run the training with lazy.py (use_wandb=False). However, I keep getting the output below, things do not seem to progress, there was even a time I waited for an hour. I used Google Colab for T4 GPU, same results, I used my own PC, CPU, same results. I also tried to export and used dataset format YOLOv9, same result, stuck in the first progress. Any help is appreciated on how to train. Thank you.

Command:

python yolo\lazy.py task=train dataset=v9-aug use_wandb=False device=cpu task.data.batch_size=12 name=t002

config.py:

hydra:
  run:
    dir: runs

name: v9-dev

defaults:
  - _self_
  - task: train
  - dataset: v9-aug
  - model: v9-c
  - general

I am using COCO export format of my dataset from ROBOFLOW, I have the following yaml file in yolo/config/dataset/v9-aug.yaml:

path: C:\Users\LM\Downloads\v9-v1_aug.coco
train: C:\Users\LM\Downloads\v9-v1_aug.coco\images\train
validation: C:\Users\LM\Downloads\v9-v1_aug.coco\images\validation
test: C:\Users\LM\Downloads\v9-v1_aug.coco\images\test

class_num: 3
class_list: ['A', 'B', 'C']

Output is:

                    INFO     🈶 Found stride of model [8, 16, 32]                                                                    
                    INFO     ✅ Success load loss function                                                                               
┏━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━┓
┃   ┃ Name   ┃ Type                 ┃ Params ┃ Mode  ┃
┡━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━┩
│ 0 │ model  │ YOLO                 │ 51.0 M │ train │
│ 1 │ metric │ MeanAveragePrecision │      0 │ train │
│ 2 │ ema    │ YOLO                 │ 51.0 M │ train │
└───┴────────┴──────────────────────┴────────┴───────┘
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━┓
┃ Attributes                             ┃ Value      ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━┩
│ Trainable params                       │ 51.0 M     │
│ Non-trainable params                   │ 51.0 M     │
│ Total params                           │ 102 M      │
│ Total estimated model params size (MB) │ 408        │
│ Modules in train mode                  │ 2443       │
│ Modules in eval mode                   │ 0          │
└────────────────────────────────────────┴────────────┘

I also have the following output log on runs/train:

:chart_with_upwards_trend: Enable Model EMA
:tractor: Building YOLO
  :building_construction:  Building backbone
  :building_construction:  Building neck
  :building_construction:  Building head
  :building_construction:  Building detection
  :building_construction:  Building auxiliary
:warning: Weight Mismatch for key: 22.heads.0.class_conv
:warning: Weight Mismatch for key: 38.heads.0.class_conv
:warning: Weight Mismatch for key: 22.heads.2.class_conv
:warning: Weight Mismatch for key: 22.heads.1.class_conv
:warning: Weight Mismatch for key: 38.heads.1.class_conv
:warning: Weight Mismatch for key: 38.heads.2.class_conv
:white_check_mark: Success load model & weight
:package: Loaded C:\Users\LM\Downloads\v9-v1_aug.coco\images\validation cache
:package: Loaded C:\Users\LM\Downloads\v9-v1_aug.coco\images\train cache
:japanese_not_free_of_charge_button: Found stride of model [8, 16, 32]
:white_check_mark: Success load loss function

[pharaon-dev]

Hello sir, have you found a solution to see the progress of learning?

[Rhroan]

I think this is bug
you can try
python yolo\lazy.py task=train dataset=v9-aug device=gpu task.data.batch_size=12 name=t002

wandb=true,then when ask

INFO 🌐 (1) Create a W&B account logging_utils.py:268
INFO 🌐 (2) Use an existing W&B account logging_utils.py:268
INFO 🌐 (3) Don't visualize my results logging_utils.py:268

select (3)

[darinhitchings]

device=cuda or device=gpu? I haven't seen the latter thus far.