Update README.md

README.md

@@ -30,3 +30,55 @@ widget:
     url: images/example_1zu0awc7s.png
 
 ---
+
+<Gallery />
+
+The text encoder **was not** trained.
+You may reuse the base model text encoder for inference.
+
+## Training settings
+
+- Training epochs: 1000
+- Training steps: TBD (depends on dataset size)
+- Learning rate: Automagic (adaptive)
+  - Learning rate schedule: Automagic optimizer
+  - Warmup steps: 0 (commented out: 100)
+- Max grad value: 1.0
+- Effective batch size: 4
+  - Micro-batch size: 4
+  - Gradient accumulation steps: 1
+  - Number of GPUs: 1
+- Gradient checkpointing: True (unsloth)
+- Prediction type: logit_normal
+- Optimizer: automagic
+- Trainable parameter precision: Pure BF16
+- Base model precision: Pure BF16
+- Caption dropout probability: 0.0% (not specified)
+
+- LoRA Rank: 32
+- LoRA Alpha: 32 (auto-set to rank)
+- LoRA Dropout: 0.0
+- LoRA initialisation style: default
+- LoRA mode: Standard
+
+## Datasets
+
+### henri_rousseau-768
+- Repeats: 8
+- Total number of images: TBD
+- Total number of aspect buckets: 12 (from ar_buckets config)
+- Resolution: 640 px
+- Cropped: False
+- Crop style: aspect ratio bucketing
+- Crop aspect: [0.70, 0.74, 0.77, 0.79, 0.81, 0.83, 1.18, 1.23, 1.34, 1.38, 1.44, 1.47]
+- Used for regularisation data: No
+
+### henri_rousseau-1024
+- Repeats: 4
+- Total number of images: TBD
+- Total number of aspect buckets: 12 (from ar_buckets config)
+- Resolution: 1328 px
+- Cropped: False
+- Crop style: aspect ratio bucketing
+- Crop aspect: [0.70, 0.74, 0.77, 0.79, 0.81, 0.83, 1.18, 1.23, 1.34, 1.38, 1.44, 1.47]
+- Used for regularisation data: No