deit-b16-food101 / config /config.yaml
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dataset:
name: food101
img_size: 224
img_chls: 3
aug:
hor_flip_aug: true
auto_augment: false
rand_augment: true
n_class: 101
model:
name: DeiT-B-16
img_size: ${dataset.img_size}
patch_size: 16
img_chls: ${dataset.img_chls}
n_class: ${dataset.n_class}
n_layer: 12
n_heads: 12
n_embd: 768
mlp_dim: 3072
drop_rate: 0.1
attn_drop_rate: 0.1
stoch_depth_drop_rate: 0.1
use_dist_token: true
rng_seed: 31415
interactive: true
model_name: ${model.name}-${dataset.name}
n_epochs: 100
save_every_epoch: 20
val_every_epoch: 10
init_from: scratch
device_type: cuda
torch_compile: true
enable_tf32: true
clip_grad_norm_1: true
autocast_dtype: bf16
wandb: true
dataloader:
batch_size: 256
num_workers: 4
pin_memory: true
drop_last: true
optimizer:
_target_: torch.optim.AdamW
lr: 0.0003
betas:
- 0.9
- 0.99
weight_decay: 0.1
eps: 1.0e-08
fused: true
lr_scheduler:
name: cosine-with-linear-warmup
min_lr_pct: 0.1
warmup_pct: 0.1
decay_step_pct: 0.6
deit:
enable: true
teacher_name: hf_hub:anonauthors/food101-resnet50
logging:
log_dir: ./logs
wandb:
enable: ${wandb}
project: vit