Open VicaYang opened 2 years ago
VicaYang
commented
2 years ago One other minor issue, what is the correct way to combine the configs from models/vit_b16.yaml and eval_resnet_8gpu_transfer_in1k_linear.yaml? Currently I manually merge these two files and create a new yaml file, but I think it is a bad practice. I found How to override a training component with config files in this page, but I failed to use it
QuentinDuval
commented
2 years ago Hi @VicaYang,
First of all, thank you for using VISSL :)
So let me tackle first the question of how to combine training components. The way to do it is to use the override syntax of Hydra:
python /path/to/vissl/tools/run_distributed_engines.py
config=benchmark/linear_image_classification/imagenet1k/eval_resnet_8gpu_transfer_in1k_linear
+config/benchmark/linear_image_classification/imagenet1k/models=vit_b16
config.MODEL.WEIGHTS_INIT.PARAMS_FILE=/path/to/checkpoint.torchThe "+" syntax will deal with the merging.
Now the classification accuracy issues:
On the supervised ViT, I am not sure there is any issue. The train accuracy can sometimes be different from the test accuracy because the augmentations (especially the augmentations for ViT, because ViT lack a lot of biases that CNN have) can be pretty agressive to enforce regularisation.
On the MoCo side there is clearly a big issue. I think the model is probably not correctly loaded, and so the accuracy you get is on linear evaluation on top of a random representation (hence the 1% top-1 accuracy). So we need to debug why.
Could you please send me the logs that you got (the log.txt created by VISSL)?
Inside of it, you can grep for Extra layer and this will indicate us whether or not the weights were actually loaded. Once I have this information, I can help you correct this.
Thank you, Quentin
VicaYang
commented
2 years ago Updated: well, I checked the moco2/log.txt and found that the weight seems not correctly loaded. I am trying a different prefix to see if it works.
===================
Thank @QuentinDuval for your help! I will try your config to see how it works.
For the log data, I found that the Extra layers are not loaded in both 2/log.txt and `moco2/log.txt'. I pasted the grepped results below, the full log can be downloaded from here
cat 2/log.txt | grep Extra
INFO 2022-05-08 18:17:47,578 checkpoint.py: 901: Extra layers not loaded from checkpoint: ['trunk.blocks.0.attn.qkv.bias', 'trunk.blocks.1.attn.qkv.bias', 'trunk.blocks.2.attn.qkv.bias', 'trunk.blocks.3.attn.qkv.bias', 'trunk.blocks.4.attn.qkv.bias', 'trunk.blocks.5.attn.qkv.bias', 'trunk.blocks.6.attn.qkv.bias', 'trunk.blocks.7.attn.qkv.bias', 'trunk.blocks.8.attn.qkv.bias', 'trunk.blocks.9.attn.qkv.bias', 'trunk.blocks.10.attn.qkv.bias', 'trunk.blocks.11.attn.qkv.bias']
INFO 2022-05-08 19:07:01,192 checkpoint.py: 901: Extra layers not loaded from checkpoint: ['trunk.blocks.0.attn.qkv.bias', 'trunk.blocks.1.attn.qkv.bias', 'trunk.blocks.2.attn.qkv.bias', 'trunk.blocks.3.attn.qkv.bias', 'trunk.blocks.4.attn.qkv.bias', 'trunk.blocks.5.attn.qkv.bias', 'trunk.blocks.6.attn.qkv.bias', 'trunk.blocks.7.attn.qkv.bias', 'trunk.blocks.8.attn.qkv.bias', 'trunk.blocks.9.attn.qkv.bias', 'trunk.blocks.10.attn.qkv.bias', 'trunk.blocks.11.attn.qkv.bias']cat moco2/log.txt | grep Extra
INFO 2022-05-08 18:17:27,381 checkpoint.py: 901: Extra layers not loaded from checkpoint: ['trunk._feature_blocks.epoch', 'trunk._feature_blocks.arch', 'trunk._feature_blocks.state_dict', 'trunk._feature_blocks.optimizer', 'trunk._feature_blocks.type']
INFO 2022-05-08 19:06:36,351 checkpoint.py: 901: Extra layers not loaded from checkpoint: ['trunk._feature_blocks.epoch', 'trunk._feature_blocks.arch', 'trunk._feature_blocks.state_dict', 'trunk._feature_blocks.optimizer', 'trunk._feature_blocks.type']I spent 2 hours and still failed to load the weight from mocov3 correctly :( The weight file is structured as follow
In [3]: list(a.keys())
Out[3]: ['epoch', 'arch', 'state_dict', 'optimizer']
In [4]: list(a['state_dict'].keys())
Out[4]:
['module.base_encoder.cls_token',
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'module.predictor.1.num_batches_tracked',
'module.predictor.3.weight',
'module.predictor.4.running_mean',
'module.predictor.4.running_var',
'module.predictor.4.num_batches_tracked']So I think STATE_DICT_KEY_NAME should be state_dict and REMOVE_PREFIX should be module.base_encoder..
Then I tried several combinations for APPEND_PREFIX, including `,trunk.,trunk.base_model.,trunk._feature_blocks.,trunk.base_model._feature_blocks.,trunk._feature_blocks.base_model., but none of them works. Could you help me how to load the weight correctly (for both linear and fulltune, I read the documents and found that there are some differences for this two mode. I thought.base_model` is needed for linear and should be removed for fulltune, but I am not quite sure now)?
python run_distributed_engines.py \
config=benchmark/linear_image_classification/imagenet1k/eval_resnet_8gpu_transfer_in1k_linear \
+config/benchmark/linear_image_classification/imagenet1k/models=vit_b16 \
config.MODEL.WEIGHTS_INIT.PARAMS_FILE="../weight/mocov3-vit-b-300ep.pth.tar" \
config.MODEL.WEIGHTS_INIT.STATE_DICT_KEY_NAME="state_dict" \
config.MODEL.WEIGHTS_INIT.APPEND_PREFIX="trunk.base_model." \
config.MODEL.WEIGHTS_INIT.REMOVE_PREFIX="module.base_encoder." \
config.CHECKPOINT.DIR="linear/moco" \
python run_distributed_engines.py \
hydra.verbose=true \
config=benchmark/fulltune/imagenet1k/eval_vit_8gpu_transfer_in1k_finetune \
+config/benchmark/fulltune/imagenet1k/models=vit_b16_vica \
config.CHECKPOINT.DIR="fulltune/moco" \
config.MODEL.WEIGHTS_INIT.PARAMS_FILE="../weight/mocov3-vit-b-300ep.pth.tar" \
config.MODEL.WEIGHTS_INIT.STATE_DICT_KEY_NAME="state_dict" \
config.MODEL.WEIGHTS_INIT.REMOVE_PREFIX="module.base_encoder." \
config.MODEL.WEIGHTS_INIT.APPEND_PREFIX="trunk." \
config.DISTRIBUTED.NUM_PROC_PER_NODE=4 > log.txt 2>&1The error above is related to #550
Instructions To Reproduce the Issue:
I used the prebuilt vissl, created a new folder contains
tools/run_distributed_engines.pyand all files under folderconfigs, and created a new config to run the benchmark using vit-b16 Check https://stackoverflow.com/help/minimal-reproducible-example for how to ask good questions. Simplify the steps to reproduce the issue using suggestions from the above link, and provide them below:git diff)and my
dataset_catalog.json(I am not sure should I usetestsplit orvalsplit for "val"; thevalfolder is created using this scriptpython tools/run_distributed_engines.py \ config=benchmark/linear_image_classification/imagenet1k/2 \ config.MODEL.WEIGHTS_INIT.PARAMS_FILE="../weight/mocov3-vit-b-300ep.pth.tar" \ config.MODEL.WEIGHTS_INIT.STATE_DICT_KEY_NAME="" \ config.MODEL.WEIGHTS_INIT.APPEND_PREFIX="trunk._feature_blocks." \ config.CHECKPOINT.DIR="checkpoint/moco2"
{"iteration": 1252, "phase_idx": 0, "train_accuracy_list_meter": {"top_1": {"0": 48.6703}, "top_5": {"0": 70.0547}}, "train_phase_idx": 0} {"iteration": 1252, "phase_idx": 1, "test_accuracy_list_meter": {"top_1": {"0": 78.2}, "top_5": {"0": 95.078}}, "train_phase_idx": 0} {"iteration": 2504, "phase_idx": 2, "train_accuracy_list_meter": {"top_1": {"0": 51.3593}, "top_5": {"0": 72.7701}}, "train_phase_idx": 1} {"iteration": 2504, "phase_idx": 3, "test_accuracy_list_meter": {"top_1": {"0": 78.338}, "top_5": {"0": 94.95400000000001}}, "train_phase_idx": 1} {"iteration": 3756, "phase_idx": 4, "train_accuracy_list_meter": {"top_1": {"0": 51.6701}, "top_5": {"0": 73.0482}}, "train_phase_idx": 2} {"iteration": 3756, "phase_idx": 5, "test_accuracy_list_meter": {"top_1": {"0": 78.172}, "top_5": {"0": 94.75}}, "train_phase_idx": 2} {"iteration": 5008, "phase_idx": 6, "train_accuracy_list_meter": {"top_1": {"0": 51.7722}, "top_5": {"0": 73.0847}}, "train_phase_idx": 3} {"iteration": 5008, "phase_idx": 7, "test_accuracy_list_meter": {"top_1": {"0": 78.2}, "top_5": {"0": 94.716}}, "train_phase_idx": 3} {"iteration": 6260, "phase_idx": 8, "train_accuracy_list_meter": {"top_1": {"0": 51.843799999999995}, "top_5": {"0": 73.1542}}, "train_phase_idx": 4} {"iteration": 6260, "phase_idx": 9, "test_accuracy_list_meter": {"top_1": {"0": 77.97}, "top_5": {"0": 94.678}}, "train_phase_idx": 4} {"iteration": 7512, "phase_idx": 10, "train_accuracy_list_meter": {"top_1": {"0": 51.8061}, "top_5": {"0": 73.1753}}, "train_phase_idx": 5} {"iteration": 7512, "phase_idx": 11, "test_accuracy_list_meter": {"top_1": {"0": 78.034}, "top_5": {"0": 94.726}}, "train_phase_idx": 5} {"iteration": 8764, "phase_idx": 12, "train_accuracy_list_meter": {"top_1": {"0": 51.9195}, "top_5": {"0": 73.2584}}, "train_phase_idx": 6} {"iteration": 8764, "phase_idx": 13, "test_accuracy_list_meter": {"top_1": {"0": 77.932}, "top_5": {"0": 94.738}}, "train_phase_idx": 6} {"iteration": 10016, "phase_idx": 14, "train_accuracy_list_meter": {"top_1": {"0": 51.9531}, "top_5": {"0": 73.237}}, "train_phase_idx": 7} {"iteration": 10016, "phase_idx": 15, "test_accuracy_list_meter": {"top_1": {"0": 78.038}, "top_5": {"0": 94.624}}, "train_phase_idx": 7} {"iteration": 11268, "phase_idx": 16, "train_accuracy_list_meter": {"top_1": {"0": 51.96340000000001}, "top_5": {"0": 73.311}}, "train_phase_idx": 8} {"iteration": 11268, "phase_idx": 17, "test_accuracy_list_meter": {"top_1": {"0": 78.02799999999999}, "top_5": {"0": 94.666}}, "train_phase_idx": 8} {"iteration": 12520, "phase_idx": 18, "train_accuracy_list_meter": {"top_1": {"0": 51.9783}, "top_5": {"0": 73.3279}}, "train_phase_idx": 9} {"iteration": 12520, "phase_idx": 19, "test_accuracy_list_meter": {"top_1": {"0": 78.022}, "top_5": {"0": 94.638}}, "train_phase_idx": 9} {"iteration": 13772, "phase_idx": 20, "train_accuracy_list_meter": {"top_1": {"0": 51.9991}, "top_5": {"0": 73.3466}}, "train_phase_idx": 10} {"iteration": 13772, "phase_idx": 21, "test_accuracy_list_meter": {"top_1": {"0": 78.172}, "top_5": {"0": 94.616}}, "train_phase_idx": 10} {"iteration": 15024, "phase_idx": 22, "train_accuracy_list_meter": {"top_1": {"0": 52.0532}, "top_5": {"0": 73.4346}}, "train_phase_idx": 11} {"iteration": 15024, "phase_idx": 23, "test_accuracy_list_meter": {"top_1": {"0": 78.13}, "top_5": {"0": 94.634}}, "train_phase_idx": 11} {"iteration": 16276, "phase_idx": 24, "train_accuracy_list_meter": {"top_1": {"0": 52.01090000000001}, "top_5": {"0": 73.3309}}, "train_phase_idx": 12} {"iteration": 16276, "phase_idx": 25, "test_accuracy_list_meter": {"top_1": {"0": 77.776}, "top_5": {"0": 94.574}}, "train_phase_idx": 12} {"iteration": 17528, "phase_idx": 26, "train_accuracy_list_meter": {"top_1": {"0": 52.0753}, "top_5": {"0": 73.3931}}, "train_phase_idx": 13} {"iteration": 17528, "phase_idx": 27, "test_accuracy_list_meter": {"top_1": {"0": 77.912}, "top_5": {"0": 94.594}}, "train_phase_idx": 13} {"iteration": 18780, "phase_idx": 28, "train_accuracy_list_meter": {"top_1": {"0": 52.162200000000006}, "top_5": {"0": 73.43990000000001}}, "train_phase_idx": 14} {"iteration": 18780, "phase_idx": 29, "test_accuracy_list_meter": {"top_1": {"0": 78.078}, "top_5": {"0": 94.648}}, "train_phase_idx": 14} {"iteration": 20032, "phase_idx": 30, "train_accuracy_list_meter": {"top_1": {"0": 52.1456}, "top_5": {"0": 73.4644}}, "train_phase_idx": 15} {"iteration": 20032, "phase_idx": 31, "test_accuracy_list_meter": {"top_1": {"0": 77.864}, "top_5": {"0": 94.64}}, "train_phase_idx": 15} {"iteration": 21284, "phase_idx": 32, "train_accuracy_list_meter": {"top_1": {"0": 52.1913}, "top_5": {"0": 73.53110000000001}}, "train_phase_idx": 16} {"iteration": 21284, "phase_idx": 33, "test_accuracy_list_meter": {"top_1": {"0": 78.208}, "top_5": {"0": 94.768}}, "train_phase_idx": 16} {"iteration": 22536, "phase_idx": 34, "train_accuracy_list_meter": {"top_1": {"0": 52.186600000000006}, "top_5": {"0": 73.53020000000001}}, "train_phase_idx": 17} {"iteration": 22536, "phase_idx": 35, "test_accuracy_list_meter": {"top_1": {"0": 78.254}, "top_5": {"0": 94.634}}, "train_phase_idx": 17} {"iteration": 23788, "phase_idx": 36, "train_accuracy_list_meter": {"top_1": {"0": 52.219300000000004}, "top_5": {"0": 73.5076}}, "train_phase_idx": 18} {"iteration": 23788, "phase_idx": 37, "test_accuracy_list_meter": {"top_1": {"0": 78.194}, "top_5": {"0": 94.76}}, "train_phase_idx": 18} {"iteration": 25040, "phase_idx": 38, "train_accuracy_list_meter": {"top_1": {"0": 52.2216}, "top_5": {"0": 73.51520000000001}}, "train_phase_idx": 19} {"iteration": 25040, "phase_idx": 39, "test_accuracy_list_meter": {"top_1": {"0": 78.102}, "top_5": {"0": 94.728}}, "train_phase_idx": 19} {"iteration": 26292, "phase_idx": 40, "train_accuracy_list_meter": {"top_1": {"0": 52.3286}, "top_5": {"0": 73.6481}}, "train_phase_idx": 20} {"iteration": 26292, "phase_idx": 41, "test_accuracy_list_meter": {"top_1": {"0": 78.244}, "top_5": {"0": 94.722}}, "train_phase_idx": 20} {"iteration": 27544, "phase_idx": 42, "train_accuracy_list_meter": {"top_1": {"0": 52.3783}, "top_5": {"0": 73.66629999999999}}, "train_phase_idx": 21} {"iteration": 27544, "phase_idx": 43, "test_accuracy_list_meter": {"top_1": {"0": 78.44200000000001}, "top_5": {"0": 94.69999999999999}}, "train_phase_idx": 21} {"iteration": 28796, "phase_idx": 44, "train_accuracy_list_meter": {"top_1": {"0": 52.3906}, "top_5": {"0": 73.714}}, "train_phase_idx": 22} {"iteration": 28796, "phase_idx": 45, "test_accuracy_list_meter": {"top_1": {"0": 78.314}, "top_5": {"0": 94.688}}, "train_phase_idx": 22} {"iteration": 30048, "phase_idx": 46, "train_accuracy_list_meter": {"top_1": {"0": 52.4285}, "top_5": {"0": 73.8044}}, "train_phase_idx": 23} {"iteration": 30048, "phase_idx": 47, "test_accuracy_list_meter": {"top_1": {"0": 78.292}, "top_5": {"0": 94.76400000000001}}, "train_phase_idx": 23} {"iteration": 31300, "phase_idx": 48, "train_accuracy_list_meter": {"top_1": {"0": 52.4684}, "top_5": {"0": 73.8225}}, "train_phase_idx": 24} {"iteration": 31300, "phase_idx": 49, "test_accuracy_list_meter": {"top_1": {"0": 78.236}, "top_5": {"0": 94.704}}, "train_phase_idx": 24} {"iteration": 32552, "phase_idx": 50, "train_accuracy_list_meter": {"top_1": {"0": 52.481100000000005}, "top_5": {"0": 73.7923}}, "train_phase_idx": 25} {"iteration": 32552, "phase_idx": 51, "test_accuracy_list_meter": {"top_1": {"0": 78.33200000000001}, "top_5": {"0": 94.78999999999999}}, "train_phase_idx": 25} {"iteration": 33804, "phase_idx": 52, "train_accuracy_list_meter": {"top_1": {"0": 52.648700000000005}, "top_5": {"0": 73.9105}}, "train_phase_idx": 26} {"iteration": 33804, "phase_idx": 53, "test_accuracy_list_meter": {"top_1": {"0": 78.268}, "top_5": {"0": 94.686}}, "train_phase_idx": 26} {"iteration": 35056, "phase_idx": 54, "train_accuracy_list_meter": {"top_1": {"0": 52.635200000000005}, "top_5": {"0": 73.976}}, "train_phase_idx": 27} {"iteration": 35056, "phase_idx": 55, "test_accuracy_list_meter": {"top_1": {"0": 78.312}, "top_5": {"0": 94.67999999999999}}, "train_phase_idx": 27} {"iteration": 36308, "phase_idx": 56, "train_accuracy_list_meter": {"top_1": {"0": 52.674699999999994}, "top_5": {"0": 73.9935}}, "train_phase_idx": 28} {"iteration": 36308, "phase_idx": 57, "test_accuracy_list_meter": {"top_1": {"0": 78.194}, "top_5": {"0": 94.65599999999999}}, "train_phase_idx": 28} {"iteration": 37560, "phase_idx": 58, "train_accuracy_list_meter": {"top_1": {"0": 52.6903}, "top_5": {"0": 74.01950000000001}}, "train_phase_idx": 29} {"iteration": 37560, "phase_idx": 59, "test_accuracy_list_meter": {"top_1": {"0": 78.508}, "top_5": {"0": 94.792}}, "train_phase_idx": 29} {"iteration": 38812, "phase_idx": 60, "train_accuracy_list_meter": {"top_1": {"0": 52.7625}, "top_5": {"0": 74.0935}}, "train_phase_idx": 30} {"iteration": 38812, "phase_idx": 61, "test_accuracy_list_meter": {"top_1": {"0": 78.43}, "top_5": {"0": 94.652}}, "train_phase_idx": 30} {"iteration": 40064, "phase_idx": 62, "train_accuracy_list_meter": {"top_1": {"0": 52.8271}, "top_5": {"0": 74.12910000000001}}, "train_phase_idx": 31} {"iteration": 40064, "phase_idx": 63, "test_accuracy_list_meter": {"top_1": {"0": 78.422}, "top_5": {"0": 94.73}}, "train_phase_idx": 31} {"iteration": 41316, "phase_idx": 64, "train_accuracy_list_meter": {"top_1": {"0": 52.92210000000001}, "top_5": {"0": 74.17049999999999}}, "train_phase_idx": 32} {"iteration": 41316, "phase_idx": 65, "test_accuracy_list_meter": {"top_1": {"0": 78.47}, "top_5": {"0": 94.782}}, "train_phase_idx": 32} {"iteration": 42568, "phase_idx": 66, "train_accuracy_list_meter": {"top_1": {"0": 52.9482}, "top_5": {"0": 74.2158}}, "train_phase_idx": 33} {"iteration": 42568, "phase_idx": 67, "test_accuracy_list_meter": {"top_1": {"0": 78.50200000000001}, "top_5": {"0": 94.812}}, "train_phase_idx": 33} {"iteration": 43820, "phase_idx": 68, "train_accuracy_list_meter": {"top_1": {"0": 53.0861}, "top_5": {"0": 74.3485}}, "train_phase_idx": 34} {"iteration": 43820, "phase_idx": 69, "test_accuracy_list_meter": {"top_1": {"0": 78.604}, "top_5": {"0": 94.83}}, "train_phase_idx": 34} {"iteration": 45072, "phase_idx": 70, "train_accuracy_list_meter": {"top_1": {"0": 53.040299999999995}, "top_5": {"0": 74.3432}}, "train_phase_idx": 35} {"iteration": 45072, "phase_idx": 71, "test_accuracy_list_meter": {"top_1": {"0": 78.494}, "top_5": {"0": 94.914}}, "train_phase_idx": 35} {"iteration": 46324, "phase_idx": 72, "train_accuracy_list_meter": {"top_1": {"0": 53.1142}, "top_5": {"0": 74.3947}}, "train_phase_idx": 36} {"iteration": 46324, "phase_idx": 73, "test_accuracy_list_meter": {"top_1": {"0": 78.66}, "top_5": {"0": 94.868}}, "train_phase_idx": 36} {"iteration": 47576, "phase_idx": 74, "train_accuracy_list_meter": {"top_1": {"0": 53.2202}, "top_5": {"0": 74.47409999999999}}, "train_phase_idx": 37} {"iteration": 47576, "phase_idx": 75, "test_accuracy_list_meter": {"top_1": {"0": 78.556}, "top_5": {"0": 94.808}}, "train_phase_idx": 37} {"iteration": 48828, "phase_idx": 76, "train_accuracy_list_meter": {"top_1": {"0": 53.3245}, "top_5": {"0": 74.5382}}, "train_phase_idx": 38} {"iteration": 48828, "phase_idx": 77, "test_accuracy_list_meter": {"top_1": {"0": 78.61}, "top_5": {"0": 94.878}}, "train_phase_idx": 38} {"iteration": 50080, "phase_idx": 78, "train_accuracy_list_meter": {"top_1": {"0": 53.376599999999996}, "top_5": {"0": 74.6219}}, "train_phase_idx": 39} {"iteration": 50080, "phase_idx": 79, "test_accuracy_list_meter": {"top_1": {"0": 78.73400000000001}, "top_5": {"0": 94.86}}, "train_phase_idx": 39} {"iteration": 51332, "phase_idx": 80, "train_accuracy_list_meter": {"top_1": {"0": 53.5072}, "top_5": {"0": 74.66380000000001}}, "train_phase_idx": 40} {"iteration": 51332, "phase_idx": 81, "test_accuracy_list_meter": {"top_1": {"0": 78.728}, "top_5": {"0": 94.772}}, "train_phase_idx": 40} {"iteration": 52584, "phase_idx": 82, "train_accuracy_list_meter": {"top_1": {"0": 53.455600000000004}, "top_5": {"0": 74.7445}}, "train_phase_idx": 41} {"iteration": 52584, "phase_idx": 83, "test_accuracy_list_meter": {"top_1": {"0": 78.678}, "top_5": {"0": 94.882}}, "train_phase_idx": 41} {"iteration": 53836, "phase_idx": 84, "train_accuracy_list_meter": {"top_1": {"0": 53.6231}, "top_5": {"0": 74.7963}}, "train_phase_idx": 42} {"iteration": 53836, "phase_idx": 85, "test_accuracy_list_meter": {"top_1": {"0": 78.61399999999999}, "top_5": {"0": 94.87400000000001}}, "train_phase_idx": 42} {"iteration": 55088, "phase_idx": 86, "train_accuracy_list_meter": {"top_1": {"0": 53.71510000000001}, "top_5": {"0": 74.8763}}, "train_phase_idx": 43} {"iteration": 55088, "phase_idx": 87, "test_accuracy_list_meter": {"top_1": {"0": 78.786}, "top_5": {"0": 94.948}}, "train_phase_idx": 43} {"iteration": 56340, "phase_idx": 88, "train_accuracy_list_meter": {"top_1": {"0": 53.782799999999995}, "top_5": {"0": 74.9507}}, "train_phase_idx": 44} {"iteration": 56340, "phase_idx": 89, "test_accuracy_list_meter": {"top_1": {"0": 78.78}, "top_5": {"0": 94.932}}, "train_phase_idx": 44} {"iteration": 57592, "phase_idx": 90, "train_accuracy_list_meter": {"top_1": {"0": 53.7792}, "top_5": {"0": 75.0033}}, "train_phase_idx": 45} {"iteration": 57592, "phase_idx": 91, "test_accuracy_list_meter": {"top_1": {"0": 78.74600000000001}, "top_5": {"0": 95.012}}, "train_phase_idx": 45} {"iteration": 58844, "phase_idx": 92, "train_accuracy_list_meter": {"top_1": {"0": 53.9329}, "top_5": {"0": 75.1015}}, "train_phase_idx": 46} {"iteration": 58844, "phase_idx": 93, "test_accuracy_list_meter": {"top_1": {"0": 78.716}, "top_5": {"0": 94.928}}, "train_phase_idx": 46} {"iteration": 60096, "phase_idx": 94, "train_accuracy_list_meter": {"top_1": {"0": 54.000499999999995}, "top_5": {"0": 75.1875}}, "train_phase_idx": 47} {"iteration": 60096, "phase_idx": 95, "test_accuracy_list_meter": {"top_1": {"0": 79.07600000000001}, "top_5": {"0": 94.95599999999999}}, "train_phase_idx": 47} {"iteration": 61348, "phase_idx": 96, "train_accuracy_list_meter": {"top_1": {"0": 54.0794}, "top_5": {"0": 75.2159}}, "train_phase_idx": 48} {"iteration": 61348, "phase_idx": 97, "test_accuracy_list_meter": {"top_1": {"0": 79.066}, "top_5": {"0": 95.028}}, "train_phase_idx": 48} {"iteration": 62600, "phase_idx": 98, "train_accuracy_list_meter": {"top_1": {"0": 54.1452}, "top_5": {"0": 75.3116}}, "train_phase_idx": 49} {"iteration": 62600, "phase_idx": 99, "test_accuracy_list_meter": {"top_1": {"0": 78.99000000000001}, "top_5": {"0": 95.02000000000001}}, "train_phase_idx": 49} {"iteration": 63852, "phase_idx": 100, "train_accuracy_list_meter": {"top_1": {"0": 54.2848}, "top_5": {"0": 75.4063}}, "train_phase_idx": 50} {"iteration": 63852, "phase_idx": 101, "test_accuracy_list_meter": {"top_1": {"0": 78.934}, "top_5": {"0": 95.06599999999999}}, "train_phase_idx": 50} {"iteration": 65104, "phase_idx": 102, "train_accuracy_list_meter": {"top_1": {"0": 54.315000000000005}, "top_5": {"0": 75.4286}}, "train_phase_idx": 51} {"iteration": 65104, "phase_idx": 103, "test_accuracy_list_meter": {"top_1": {"0": 78.938}, "top_5": {"0": 95.06599999999999}}, "train_phase_idx": 51} {"iteration": 66356, "phase_idx": 104, "train_accuracy_list_meter": {"top_1": {"0": 54.443200000000004}, "top_5": {"0": 75.4973}}, "train_phase_idx": 52} {"iteration": 66356, "phase_idx": 105, "test_accuracy_list_meter": {"top_1": {"0": 79.012}, "top_5": {"0": 95.06400000000001}}, "train_phase_idx": 52} {"iteration": 67608, "phase_idx": 106, "train_accuracy_list_meter": {"top_1": {"0": 54.4863}, "top_5": {"0": 75.60510000000001}}, "train_phase_idx": 53} {"iteration": 67608, "phase_idx": 107, "test_accuracy_list_meter": {"top_1": {"0": 79.026}, "top_5": {"0": 95.002}}, "train_phase_idx": 53} {"iteration": 68860, "phase_idx": 108, "train_accuracy_list_meter": {"top_1": {"0": 54.500400000000006}, "top_5": {"0": 75.61630000000001}}, "train_phase_idx": 54} {"iteration": 68860, "phase_idx": 109, "test_accuracy_list_meter": {"top_1": {"0": 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diff --git a/exp/checkpoint/2/train_config.yaml b/exp/checkpoint/moco2/train_config.yaml index 6a98f31..3eb04fa 100644 --- a/exp/checkpoint/2/train_config.yaml +++ b/exp/checkpoint/moco2/train_config.yaml @@ -4,7 +4,7 @@ CHECKPOINT: BACKEND: disk CHECKPOINT_FREQUENCY: 10 CHECKPOINT_ITER_FREQUENCY: -1
Provide your environment information using the following command: