
############################## Experiment details ##############################

dataset: speech_commands
dataset_dir: ../data/speech_commands/
output_dir: output/fedavg-speech_commands-2022-08-15_19:54:47/
model: m5
num_rounds: 100
eval_every: 10
ServerType: <class 'rayleaf.entities.server.Server'>
client_types: [(<class 'rayleaf.entities.client.Client'>, 1)]
clients_per_round: 1
client_lr: 0.05
batch_size: 64
seed: 0
use_val_set: False
num_epochs: 10
gpus_per_client_cluster: 1
num_client_clusters: 4
save_model: False

############################## Simulation ##############################

Spawning 4 ClientClusters using cuda device (this may take a while)
1 total clients: 1 Client

>>> Training Accuracy: Round 0 <<<
+-----------+----------+-------------------+-------------------+
|   average |   median |   10th percentile |   90th percentile |
|-----------+----------+-------------------+-------------------|
|  0.031746 | 0.031746 |          0.031746 |          0.031746 |
+-----------+----------+-------------------+-------------------+
>>> Test Accuracy: Round 0 <<<
+-----------+----------+-------------------+-------------------+
|   average |   median |   10th percentile |   90th percentile |
|-----------+----------+-------------------+-------------------|
|   0.03125 |  0.03125 |           0.03125 |           0.03125 |
+-----------+----------+-------------------+-------------------+
--- Round 1 of 100: Training 1 clients: 1 Client ---
--- Round 2 of 100: Training 1 clients: 1 Client ---
--- Round 3 of 100: Training 1 clients: 1 Client ---
--- Round 4 of 100: Training 1 clients: 1 Client ---
--- Round 5 of 100: Training 1 clients: 1 Client ---
--- Round 6 of 100: Training 1 clients: 1 Client ---
--- Round 7 of 100: Training 1 clients: 1 Client ---
--- Round 8 of 100: Training 1 clients: 1 Client ---
--- Round 9 of 100: Training 1 clients: 1 Client ---
