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  1. README.md +12 -12
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@@ -153,18 +153,18 @@ VAE: Changed, new VAE - [EQB7](https://huggingface.co/Anzhc/MS-LC-EQ-D-VR_VAE) w
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  (Base / quality-tuned)
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  **Samples seen**(unbatched steps): ~2kk / ~400k
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- **Learning Rate**: 2e-5 / 2e-5
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- **Effective Batch size**: 1280 (40 real * 4 accum * 8 devices) / 1280 (40 * 4 * 8)
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- **Precision**: Full BF16
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- **Optimizer**: AdamW8bit with Kahan Summation
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  **Weight Decay**: 0.01
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- **Schedule**: Constant with warmup
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  **Timestep Sampling Strategy**: Logit-Normal (sometimes referred to as Lognorm), Shift 2.5
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- **Text Encoders**: Frozen
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  **Keep Token**: False (Used "Protected Tags" instead), all tags are shuffled.
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- **Tag Dropout**: 10%
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  **Uncond Dropout**: 10%
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- **Optimal Transport**: True
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@@ -193,13 +193,13 @@ My current style training settings (Anzhc):
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  **Schedule**: ReREX (Use REX for simplicity)
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  **Precision**: Full BF16
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  **Weight Decay**: 0.02
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- **Timestep Sampling Strategy**: Logit-Normal, Shift 2.5 (Closest to what i use result-wise)
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- **Dim/Alpha/Conv/Alpha**: 24/24/24/24 (Lycoris/Locon)
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- **Text Encoders**: Frozen
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- **Optimal Transport**: True
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  **Expected Dataset Size**: 100 images (Can be even 10, but balance with repeats to roughly this target.)
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  **Epochs**: 50 (Yes, even with 10 repeats. 500 effective epochs works just fine and doesn't break from my tests.)
 
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  (Base / quality-tuned)
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  **Samples seen**(unbatched steps): ~2kk / ~400k
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+ **Learning Rate**: 2e-5 / 2e-5
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+ **Effective Batch size**: 1280 (40 real * 4 accum * 8 devices) / 1280 (40 * 4 * 8)
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+ **Precision**: Full BF16
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+ **Optimizer**: AdamW8bit with Kahan Summation
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  **Weight Decay**: 0.01
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+ **Schedule**: Constant with warmup
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  **Timestep Sampling Strategy**: Logit-Normal (sometimes referred to as Lognorm), Shift 2.5
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+ **Text Encoders**: Frozen
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  **Keep Token**: False (Used "Protected Tags" instead), all tags are shuffled.
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+ **Tag Dropout**: 10%
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  **Uncond Dropout**: 10%
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+ **Optimal Transport**: True
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  **Schedule**: ReREX (Use REX for simplicity)
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  **Precision**: Full BF16
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  **Weight Decay**: 0.02
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+ **Timestep Sampling Strategy**: Logit-Normal, Shift 2.5 (Closest to what i use result-wise)
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+ **Dim/Alpha/Conv/Alpha**: 24/24/24/24 (Lycoris/Locon)
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+ **Text Encoders**: Frozen
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+ **Optimal Transport**: True
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  **Expected Dataset Size**: 100 images (Can be even 10, but balance with repeats to roughly this target.)
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  **Epochs**: 50 (Yes, even with 10 repeats. 500 effective epochs works just fine and doesn't break from my tests.)