revise ijepa config file

Author: vahid0001

projects/ijepa/configs/experiment/run_ijepa.yaml

@@ -5,10 +5,8 @@ defaults:
   - /datasets/transforms@datasets.train.transform: med_clip_vision_transform
   - /datasets@datasets.val: ImageNet
   - /datasets/transforms@datasets.val.transform: med_clip_vision_transform
-  - /modules/encoders@task.encoder: vit_tiny
+  - /modules/encoders@task.encoder: vit_base
   - /modules/encoders@task.predictor: vit_predictor
-  - /modules/optimizers@task.optimizer: AdamW
-  - /modules/lr_schedulers@task.lr_scheduler.scheduler: CosineAnnealingLR
   - /trainer/callbacks@trainer.callbacks.lr_monitor: LearningRateMonitor
   - /trainer/callbacks@trainer.callbacks.model_checkpoint: ModelCheckpoint
   - /trainer/callbacks@trainer.callbacks.early_stopping: EarlyStopping
@@ -20,8 +18,14 @@ defaults:
 seed: 0
 
 datasets:
+  train:
+    root_dir: /datasets/imagenet
+    split: train
+    transform:
+      job_type: train
   val:
-    split: valid
+    root_dir: /datasets/imagenet
+    split: val
     transform:
       job_type: eval
 
@@ -33,26 +37,12 @@ dataloader:
     batch_size: 32
     num_workers: 4
 
-task:
-  optimizer:
-    betas:
-    - 0.9
-    - 0.98
-    lr: 5.0e-5
-    weight_decay: 0.1
-    eps: 1.0e-6
-  lr_scheduler:
-    scheduler:
-      T_max: 107_559 # make sure to change this if max_epochs or accumulate_grad_batches is changed
-    extras:
-      interval: step
-
 trainer:
   max_epochs: 20
-  precision: 16-mixed
+  precision: 16
   deterministic: False
   benchmark: True
-  sync_batchnorm: False # set to True if using DDP with batchnorm
+  sync_batchnorm: False  # Set to True if using DDP with batchnorm
   log_every_n_steps: 100
   accumulate_grad_batches: 4
   check_val_every_n_epoch: 1