PseudoTerminal X
commited on
Trained for 3 epochs and 83000 steps.
Browse filesTrained with datasets ['text-embeds-pixart-filter', 'photo-concept-bucket', 'midjourney-v6-520k-raw', 'sfwbooru', 'nijijourney-v6-520k-raw', 'dalle3']
Learning rate 1e-06, batch size 24, and 1 gradient accumulation steps.
Used DDPM noise scheduler for training with epsilon prediction type and rescaled_betas_zero_snr=False
Using 'linspace' timestep spacing.
Base model: ptx0/pixart-900m-1024-ft-large
VAE: madebyollin/sdxl-vae-fp16-fix
- README.md +1 -1
- optimizer.bin +1 -1
- random_states_0.pkl +2 -2
- scheduler.bin +1 -1
- training_state-dalle3.json +2 -2
- training_state-midjourney-v6-520k-raw.json +2 -2
- training_state-nijijourney-v6-520k-raw.json +2 -2
- training_state-photo-concept-bucket.json +2 -2
- training_state.json +1 -1
- transformer/diffusion_pytorch_model.safetensors +1 -1
README.md
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@@ -47,7 +47,7 @@ You may reuse the base model text encoder for inference.
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## Training settings
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- Training epochs: 3
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- Training steps:
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- Learning rate: 1e-06
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- Effective batch size: 192
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- Micro-batch size: 24
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## Training settings
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- Training epochs: 3
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- Training steps: 83000
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- Learning rate: 1e-06
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- Effective batch size: 192
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- Micro-batch size: 24
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optimizer.bin
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random_states_0.pkl
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scheduler.bin
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training_state-dalle3.json
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training_state-midjourney-v6-520k-raw.json
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training_state-photo-concept-bucket.json
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training_state.json
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{"global_step": 83000, "epoch_step": 1, "epoch": 4, "exhausted_backends": ["sfwbooru", "midjourney-v6-520k-raw", "nijijourney-v6-520k-raw"], "repeats": {"bookcovers": 0, "signs": 0, "normalnudes": 0, "nijijourney": 0, "movieposters": 0, "celebrities": 0, "pixel-art": 0, "propagandaposters": 0, "sports": 0, "moviecollection": 0, "gay": 0, "experimental": 0, "yoga": 0, "ethnic": 0, "cinemamix-1mp": 0, "architecture": 0, "mj-60": 0, "text-1mp": 65, "shutterstock": 0, "nsfw-1024": 0, "photo-aesthetics": 0, "anatomy": 0, "bg20k-1024": 0, "sfwbooru": 0, "midjourney-v6-520k-raw": 0, "nijijourney-v6-520k-raw": 0, "photo-concept-bucket": 0, "dalle3": 0}}
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