kohya-ss / kohya-ss/sd-scripts
LORA caption training: extremely long pauses between epochs
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 7.2k
- Forks
- 1.2k
- Avg merge
- 11m
- Merged PRs (30d)
- 2
Description
For some reason there is a large delay when epochs change, making training much slower, what could cause this?
My settings:
accelerate launch --num_cpu_threads_per_process 10 train_network.py --pretrained_model_name_or_path=B:\AIimages\stable-diffusion-webui\models\Stable-diffusion\model.ckpt --train_data_dir=B:\AIimages\training\data --output_dir=B:\train\out\ --in_json=B:\AIimages\training\data\meta_lat.json --resolution=512,512 --prior_loss_weight=1.0 --train_batch_size=4 --learning_rate=1e-3 --max_train_steps=15000 --use_8bit_adam --xformers --gradient_checkpointing --mixed_precision=fp16 --save_every_n_epochs=10 --network_module=networks.lora --shuffle_caption --unet_lr=3e-4 --text_encoder_lr=3e-5 --lr_scheduler=constant --save_model_as=safetensors --seed=115
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with train_network.py and reproduce the epoch transition using the command and settings in the issue, timing the pauses between epochs. Trace what runs at the transition and compare it with normal training steps. Done means identifying the cause of the delay and verifying that the resulting change removes or materially reduces it.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 24/100