Update README.md

README.md

@@ -31,26 +31,14 @@ An exemplary setup which contains everything needed:
 
 ## Training Arguments
 
-* `exp_id`: Id of the experiment
-* `suffix`: suffix placed in front of the config file name
-* `model_name`: Model used for training,validation,testing (SimCLR, deepSM, S2MC, DSCMR, DUCH, DCCA, SSCMCBIR)
-* `train_tfrecord_paths`: `TFRecord` file(s) for training.
-* `val_tfrecord_paths`: `TFRecord` file(s) for validation.
-* `test_tfrecord_paths`: `TFRecord` file(s) for testing.
-* `batch_size`: Batch size used during training.
-* `embed_dim`: Embedding dimension for projection heads
-* `learning_rate`: The initial learning rate.
-* `optimizer` : Optimizers used for training,`Adam` or `SGD` 
-* `nb_epoch`: The number of epochs for the training. 
-* `gpu`: gpu(s) used for for training, validation, retrieval
-* `dumps`:
-* `model_weights`: directory containing the trained model weights , e.g. ../dumps_paper/weights/,
-* `summaries`: directory containing the summary files (tf.event) of the training, e.g. ../dumps_paper/summaries/,
-* `configs`: directory containing the config files of the training, e.g. ../dumps_paper/configs/,   
-* `logs`: directory containing the log files of the training, e.g. ../dumps_paper/logs/,
-* `features`: directory containing the feature h5 files of the retrieval for a specific model, e.g. ../dumps_paper/features/      
-* `dataset`: Dataset used for training, validation, retrieval (BEN)
-* `nb_class`: number of classes used in the dataset, 19 for BEN
+* `epoch`: number of local training
+* `round`: number of communication rounds
+* `clients`: number of total clients
+* `lr`: learning rate
+* `batch`: local batch size
+* `decay`: weight decay
+* `optimizer`: type of optimizer
+
 
 ## Authors
 **Baris Buyuktas**