Trained for 13 epochs and 23000 steps.

Trained with datasets ['text-embeds-sdxl-nofilter', 'photo-concept-bucket']
Learning rate 4e-07, batch size 32, and 2 gradient accumulation steps.
Used DDPM noise scheduler for training with v_prediction prediction type and rescaled_betas_zero_snr=True
Using 'trailing' timestep spacing.
Base model: ptx0/terminus-xl-velocity-v2
VAE: madebyollin/sdxl-vae-fp16-fix

README.md

@@ -1003,8 +1003,8 @@ You may reuse the base model text encoder for inference.
 
 ## Training settings
 
-- Training epochs: 12
-- Training steps: 22000
+- Training epochs: 13
+- Training steps: 23000
 - Learning rate: 4e-07
 - Effective batch size: 512
   - Micro-batch size: 32

optimizer.bin

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random_states_0.pkl

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scheduler.bin

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training_state-photo-concept-bucket.json

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training_state.json

@@ -1 +1 @@
-{"global_step": 22000, "epoch_step": 421, "epoch": 13, "exhausted_backends": [], "repeats": {"celebrities": 0, "pixel-art": 0, "movieposters": 0, "moviecollection": 0, "training-test": 0, "dalle3": 0, "photo-concept-bucket": 0}}
+{"global_step": 23000, "epoch_step": 332, "epoch": 14, "exhausted_backends": [], "repeats": {"celebrities": 0, "pixel-art": 0, "movieposters": 0, "moviecollection": 0, "training-test": 0, "dalle3": 0, "photo-concept-bucket": 0}}

unet/config.json

@@ -1,7 +1,7 @@
 {
   "_class_name": "UNet2DConditionModel",
-  "_diffusers_version": "0.22.0.dev0",
-  "_name_or_path": "/notebooks/datasets/models/checkpoint-17400",
+  "_diffusers_version": "0.29.0.dev0",
+  "_name_or_path": "/home/user/training/lite-models/checkpoint-19000",
   "act_fn": "silu",
   "addition_embed_type": "text_time",
   "addition_embed_type_num_heads": 64,
@@ -51,6 +51,7 @@
   "resnet_out_scale_factor": 1.0,
   "resnet_skip_time_act": false,
   "resnet_time_scale_shift": "default",
+  "reverse_transformer_layers_per_block": null,
   "sample_size": 128,
   "time_cond_proj_dim": null,
   "time_embedding_act_fn": null,

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