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pretrained models/vit_small_100ep/vit_small_100ep.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:eb2fbbf3a8743a2a6e49df8c9d9458891515d5c1a1e2c3ada00238c4b31a049b
+size 1697879403

pretrained models/vit_small_100ep/vit_small_100ep_args.txt

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+#!/bin/bash
+DATASET_ROOT=/dataset/imageNet100_sicy/train/ #/raid/common/imagenet-raw/
+
+## train ViT-small for 100 epochs
+OUTPUT_ROOT=./exps/vit_small_100ep
+NPROC_PER_NODE=8 # GPU numbers
+BATCH_SIZE_PER_GPU=64
+DEBUG=false # debug = true, then we only load subset of the whole training dataset
+python -m torch.distributed.launch --nproc_per_node=$NPROC_PER_NODE main.py \
+    --data_path $DATASET_ROOT \
+    --output_dir $OUTPUT_ROOT \
+    --arch vit_small \
+    --instance_queue_size 65536 \
+    --local_group_queue_size 65536 \
+    --use_bn_in_head false \
+    --instance_out_dim 256 \
+    --instance_temp 0.2 \
+    --local_group_out_dim 256 \
+    --local_group_temp 0.2 \
+    --local_group_knn_top_n 8 \
+    --group_out_dim 65536 \
+    --group_student_temp 0.1 \
+    --group_warmup_teacher_temp 0.04 \
+    --group_teacher_temp 0.04 \
+    --group_warmup_teacher_temp_epochs 0 \
+    --norm_last_layer false \
+    --norm_before_pred true \
+    --batch_size_per_gpu $BATCH_SIZE_PER_GPU \
+    --epochs 100 \
+    --warmup_epochs 10 \
+    --clip_grad 3.0 \
+    --lr 0.0008 \
+    --min_lr 1e-06 \
+    --patch_embed_lr_mult 0.2 \
+    --drop_path_rate 0.1 \
+    --weight_decay 0.04 \
+    --weight_decay_end 0.2 \
+    --freeze_last_layer 1 \
+    --momentum_teacher 0.996 \
+    --use_fp16 false \
+    --local_crops_number 10 \
+    --size_crops 96 \
+    --global_crops_scale 0.25 1 \
+    --local_crops_scale 0.05 0.25 \
+    --timm_auto_augment_par rand-m9-mstd0.5-inc1 \
+    --prob 0.5 \
+    --use_prefetcher true \
+    --debug $DEBUG

pretrained models/vit_small_100ep/vit_small_100ep_linear_probing_log.txt

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pretrained models/vit_small_100ep/vit_small_100ep_log.txt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b39a98060fa2b6f407fd348deec54c1b2fbdd2f625cb58966c9bfd9e709aa902
+size 93810389

pretrained models/vit_small_300ep/vit_small_300ep.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b04480cfb644370fb4a78694554b4b232f328d36b0d58f3118446827a6ddafe3
+size 1697878842

pretrained models/vit_small_300ep/vit_small_300ep_args.txt

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+#!/bin/bash
+DATASET_ROOT=/dataset/imageNet100_sicy/train/ #/raid/common/imagenet-raw/
+
+## train ViT-small for 300 epochs
+OUTPUT_ROOT=./exps/vit_small_300ep
+NPROC_PER_NODE=16 # GPU numbers
+BATCH_SIZE_PER_GPU=64
+DEBUG=false # debug = true, then we only load subset of the whole training dataset
+python -m torch.distributed.launch --nproc_per_node=$NPROC_PER_NODE main.py \
+    --data_path $DATASET_ROOT \
+    --output_dir $OUTPUT_ROOT \
+    --arch vit_small \
+    --instance_queue_size 65536 \
+    --local_group_queue_size 65536 \
+    --use_bn_in_head false \
+    --instance_out_dim 256 \
+    --instance_temp 0.2 \
+    --local_group_out_dim 256 \
+    --local_group_temp 0.2 \
+    --local_group_knn_top_n 8 \
+    --group_out_dim 65536 \
+    --group_student_temp 0.1 \
+    --group_warmup_teacher_temp 0.04 \
+    --group_teacher_temp 0.07 \
+    --group_warmup_teacher_temp_epochs 30 \
+    --norm_last_layer false \
+    --norm_before_pred true \
+    --batch_size_per_gpu $BATCH_SIZE_PER_GPU \
+    --epochs 300 \
+    --warmup_epochs 10 \
+    --clip_grad 3.0 \
+    --lr 0.0008 \
+    --min_lr 1e-06 \
+    --patch_embed_lr_mult 0.2 \
+    --drop_path_rate 0.1 \
+    --weight_decay 0.04 \
+    --weight_decay_end 0.1 \
+    --freeze_last_layer 1 \
+    --momentum_teacher 0.996 \
+    --use_fp16 false \
+    --local_crops_number 10 \
+    --size_crops 96 \
+    --global_crops_scale 0.25 1 \
+    --local_crops_scale 0.05 0.25 \
+    --timm_auto_augment_par rand-m9-mstd0.5-inc1 \
+    --prob 0.5 \
+    --use_prefetcher true \
+    --debug $DEBUG

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