Should be a more suitable fit for illustrious. It is bigger than the previous versions, both in terms of training dataset (200+ images) and the number of steps. Training parameters are listed below -
"engine": "kohya",
"unetLR": 1,
"clipSkip": 1,
"loraType": "lora",
"keepTokens": 0,
"networkDim": ??,
"numRepeats": 3,
"resolution": 1024,
"lrScheduler": "cosine",
"minSnrGamma": 5,
"noiseOffset": 0.1,
"targetSteps": 3045,
"enableBucket": true,
"networkAlpha": 32,
"optimizerType": "Prodigy",
"textEncoderLR": 1,
"maxTrainEpochs": 10,
"shuffleCaption": false,
"trainBatchSize": 2,
"flipAugmentation": false,
"lrSchedulerNumCycles": 3
Description
Should be a more suitable fit for illustrious. It is bigger than the previous versions, both in terms of training dataset (200+ images) and the number of steps. Training parameters are listed below -
"engine": "kohya",
"unetLR": 1,
"clipSkip": 1,
"loraType": "lora",
"keepTokens": 0,
"networkDim": ??,
"numRepeats": 3,
"resolution": 1024,
"lrScheduler": "cosine",
"minSnrGamma": 5,
"noiseOffset": 0.1,
"targetSteps": 3045,
"enableBucket": true,
"networkAlpha": 32,
"optimizerType": "Prodigy",
"textEncoderLR": 1,
"maxTrainEpochs": 10,
"shuffleCaption": false,
"trainBatchSize": 2,
"flipAugmentation": false,
"lrSchedulerNumCycles": 3
