Trained on Anima Base 1

Updated dataset with a mix of natural language and tag captions

Partitioned dataset and trained at multi-res 512, 768, 1024, 1280, 1536

Training config:

# trained using diffusion-pipe commit b0aa4f1e03169f3280c8518d37570a448420f8be
# NCCL_P2P_DISABLE="1" NCCL_IB_DISABLE="1" NCCL_CUMEM_ENABLE="0" deepspeed --num_gpus=1 train.py --deepspeed --config anima-lora.toml --i_know_what_i_am_doing

output_dir = '/mnt/d/anima/training_output/anima-base-1-niji-v4'

dataset = 'dataset-anima-niji.toml'

# training settings
epochs = 2
# Per-resolution batch sizes
micro_batch_size_per_gpu = [[512, 64], [768, 48], [1024, 32], [1280, 24], [1536, 16]]
pipeline_stages = 1
gradient_accumulation_steps = 1
gradient_clipping = 1
warmup_steps = 30
lr_scheduler = 'cosine'

# misc settings
save_every_n_epochs = 1
activation_checkpointing = true

partition_method = 'parameters'

save_dtype = 'bfloat16'
caching_batch_size = 1
map_num_proc = 8
steps_per_print = 1
compile = true

[model]
type = 'anima'
transformer_path = '/mnt/c/workspace/models/diffusion_models/anima-base-v1.0.safetensors'
vae_path = '/mnt/c/workspace/models/vae/qwen_image_vae.safetensors'
llm_path = '/mnt/c/workspace/models/text_encoders/qwen_3_06b_base.safetensors'
dtype = 'bfloat16'
#cache_text_embeddings = false
llm_adapter_lr = 0
#timestep_sample_method = 'uniform'
flux_shift = true
multiscale_loss_weight = 0.5
sigmoid_scale = 1.3

[adapter]
type = 'lora'
rank = 32
dtype = 'bfloat16'

[optimizer]
type = 'adamw_optimi'
lr = 4e-5
betas = [0.9, 0.99]
weight_decay = 0.01
eps = 1e-8

resolutions = [512, 768, 1024, 1280, 1536]

enable_ar_bucket = true
min_ar = 0.5
max_ar = 2.0
num_ar_buckets = 9

# micro_batch_size_per_gpu = [[512, 64], [768, 768, 48], [1024, 32], [1280, 24], [1536, 16]]

# images_niji\1536x1536\captions.json with 124 entries.
[[directory]]
path = '/mnt/d/training_data/images_niji/1536x1536'
resolutions = [512, 1024, 1280, 1536]

# images_niji\1280x1280\captions.json with 28 entries.
[[directory]]
path = '/mnt/d/training_data/images_niji/1280x1280'
resolutions = [512, 1024, 1280]

# images_niji\1024x1024\captions.json with 137 entries.
[[directory]]
path = '/mnt/d/training_data/images_niji/1024x1024'
resolutions = [512, 768, 1024]

# images_niji\768x768\captions.json with 43 entries.
[[directory]]
path = '/mnt/d/training_data/images_niji/768x768'
resolutions = [512, 768]

# images_niji\512x512\captions.json with 5 entries.
[[directory]]
path = '/mnt/d/training_data/images_niji/512x512'
resolutions = [512]