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distributed.yaml
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distributed.yaml
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description: efficientdet_distributed
hyperparameters:
global_batch_size: 64
min_loss_scale: 16
sync_bn: False
model_ema: True
amp: True
root: '/mnt/data'
dataset: coco
model: efficientdet_d0
redundant_bias: None
val_skip: 0
num_classes: None
pretrained: False
no_pretrained_backbone: False
model_ema_decay: 0.9999
initial_checkpoint: None
dist_bn: None
output: None
decay_rate: 0.1
resume: ''
no_resume_opt: False
mean: None
std: None
interpolation: ''
fill_color: None
clip_grad: 10.0
opt: fusedmomentum
opt_eps: 0.001
momentum: 0.9
weight_decay: 4.0e-05
sched: cosine
lr: 0.06
lr_noise: 0.4 0.9
lr_noise_pct: 0.67
lr_noise_std: 1.0
lr_cycle_mul: 1.0
lr_cycle_limit: 1
warmup_lr: 0.0001
min_lr: 1.0e-5
start_epoch: None
decay_epochs: 30
warmup_epochs: 5
cooldown_epochs: 10
patience_epochs: 10
color_jitter: 0.4
aa: None
reprob: 0.
remode: pixel
recount: 1
train_interpolation: random
smoothing: None
jit_loss: None
new_focal: None
seed: 42
recovery_interval: 0
workers: 4
save_images: False
channels_last: False
pin_mem: False
no_prefetcher: False
bench_labeler: False
eval_metric: map
tta: 0
epochs: 300 # used for LR calculations:update according to max_length
fake_data: False
optimizations:
tensor_fusion_threshold: 1
tensor_fusion_cycle_time: 2
records_per_epoch: 118287
searcher:
name: single
metric: val_loss
max_length:
epochs: 300
smaller_is_better: true
resources:
slots_per_trial: 4
min_validation_period:
epochs: 1
entrypoint: model_def:EffDetTrial
bind_mounts:
- host_path: /path/to/data
container_path: /mnt/data