The exact training time will depend on a number of factors, including the size of the dataset, the quality of the images, and the settings you use. However, as a general rule of thumb, you can expect to train a Dreambooth model for Stable Diffusion on an RTX 3060 with 12GB of VRAM for about 1 day per 100,000 images.

For example, if you are using a dataset of 1 million images, you can expect the training to take about 10 days. If you are using a dataset of 10 million images, you can expect the training to take about 100 days.

Of course, these are just rough estimates. The actual training time may be longer or shorter, depending on the factors mentioned above.

Here are some additional things to keep in mind:

* The training time will be longer if you use the 8bit AdamW optimizer or fp16 mixed precision.
* The training time will be shorter if you use a smaller dataset or lower-quality images.
* You can speed up the training by using a more powerful GPU.
spam fails_task lang_mismatch pii not_appropriate hate_speech sexual_content quality toxicity humor helpfulness creativity violence