--- a +++ b/configs/config_toan_resume.yml @@ -0,0 +1,99 @@ +model_params: + model: &model CNNFinetuneModels + model_name: &model_name densenet169 + num_classes: 6 + + +args: + expdir: "src" + logdir: &logdir "./logs/rsna" + baselogdir: "./logs/rsna" + +distributed_params: + opt_level: O1 + +stages: + + state_params: + main_metric: &reduce_metric loss + minimize_metric: True + + criterion_params: + criterion: &criterion LogLoss + weight: [1,1,1,1,1,2] + + data_params: + batch_size: 32 + num_workers: 4 + drop_last: False + + image_size: &image_size [512, 512] + train_csv: "./csv/stratified_kfold/train_0.csv.gz" + valid_csv: "./csv/stratified_kfold/valid_0.csv.gz" +# dataset_type: "RSNAMultiWindowsDataset" + with_any: True + root: "../stage_1_train_images_jpg_preprocessing/" + image_type: "jpg" + + # warmup: + # optimizer_params: + # optimizer: AdamW + # lr: 0.001 + + # scheduler_params: + # scheduler: MultiStepLR + # milestones: [10] + # gamma: 0.3 + + # state_params: + # num_epochs: 3 + + # callbacks_params: &callbacks_params + # loss: + # callback: CriterionCallback + + # optimizer: + # callback: OptimizerCallback + # accumulation_steps: 1 + # scheduler: + # callback: SchedulerCallback + # reduce_metric: *reduce_metric + # saver: + # callback: CheckpointCallback + # save_n_best: 5 + + stage1: + + optimizer_params: + optimizer: AdamW + lr: 0.00001 + + scheduler_params: + scheduler: MultiStepLR + milestones: [10] + gamma: 0.3 + + state_params: + num_epochs: 5 + + callbacks_params: + loss: + callback: CriterionCallback + + optimizer: + callback: OptimizerCallback + accumulation_steps: 1 + scheduler: + callback: SchedulerCallback + reduce_metric: *reduce_metric + saver: + callback: CheckpointCallback + save_n_best: 5 + + early_stoping: + callback: EarlyStoppingCallback + patience: 2 + +monitoring_params: + project: "Kaggle-RSNA" + tags: [*model, *model_name, *criterion] \ No newline at end of file