Note
Click here to download the full example code
Hyperparameter tuning with Ray Tune¶
Hyperparameter tuning can make the difference between an average model and a highly accurate one. Often simple things like choosing a different learning rate or changing a network layer size can have a dramatic impact on your model performance.
Fortunately, there are tools that help with finding the best combination of parameters. Ray Tune is an industry standard tool for distributed hyperparameter tuning. Ray Tune includes the latest hyperparameter search algorithms, integrates with TensorBoard and other analysis libraries, and natively supports distributed training through Ray’s distributed machine learning engine.
In this tutorial, we will show you how to integrate Ray Tune into your PyTorch training workflow. We will extend this tutorial from the PyTorch documentation for training a CIFAR10 image classifier.
As you will see, we only need to add some slight modifications. In particular, we need to
- wrap data loading and training in functions,
- make some network parameters configurable,
- add checkpointing (optional),
- and define the search space for the model tuning
To run this tutorial, please make sure the following packages are installed:
ray[tune]: Distributed hyperparameter tuning librarytorchvision: For the data transformers
Setup / Imports¶
Let’s start with the imports:
from functools import partial
import numpy as np
import os
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.utils.data import random_split
import torchvision
import torchvision.transforms as transforms
from ray import tune
from ray.tune import CLIReporter
from ray.tune.schedulers import ASHAScheduler
Most of the imports are needed for building the PyTorch model. Only the last three imports are for Ray Tune.
Data loaders¶
We wrap the data loaders in their own function and pass a global data directory. This way we can share a data directory between different trials.
def load_data(data_dir="./data"):
transform = transforms.Compose([
transforms.ToTensor(),
transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))
])
trainset = torchvision.datasets.CIFAR10(
root=data_dir, train=True, download=True, transform=transform)
testset = torchvision.datasets.CIFAR10(
root=data_dir, train=False, download=True, transform=transform)
return trainset, testset
Configurable neural network¶
We can only tune those parameters that are configurable. In this example, we can specify the layer sizes of the fully connected layers:
class Net(nn.Module):
def __init__(self, l1=120, l2=84):
super(Net, self).__init__()
self.conv1 = nn.Conv2d(3, 6, 5)
self.pool = nn.MaxPool2d(2, 2)
self.conv2 = nn.Conv2d(6, 16, 5)
self.fc1 = nn.Linear(16 * 5 * 5, l1)
self.fc2 = nn.Linear(l1, l2)
self.fc3 = nn.Linear(l2, 10)
def forward(self, x):
x = self.pool(F.relu(self.conv1(x)))
x = self.pool(F.relu(self.conv2(x)))
x = x.view(-1, 16 * 5 * 5)
x = F.relu(self.fc1(x))
x = F.relu(self.fc2(x))
x = self.fc3(x)
return x
The train function¶
Now it gets interesting, because we introduce some changes to the example from the PyTorch documentation.
We wrap the training script in a function train_cifar(config, checkpoint_dir=None, data_dir=None).
As you can guess, the config parameter will receive the hyperparameters we would like to
train with. The checkpoint_dir parameter is used to restore checkpoints. The data_dir specifies
the directory where we load and store the data, so multiple runs can share the same data source.
net = Net(config["l1"], config["l2"])
if checkpoint_dir:
model_state, optimizer_state = torch.load(
os.path.join(checkpoint_dir, "checkpoint"))
net.load_state_dict(model_state)
optimizer.load_state_dict(optimizer_state)
The learning rate of the optimizer is made configurable, too:
optimizer = optim.SGD(net.parameters(), lr=config["lr"], momentum=0.9)
We also split the training data into a training and validation subset. We thus train on 80% of the data and calculate the validation loss on the remaining 20%. The batch sizes with which we iterate through the training and test sets are configurable as well.
Adding (multi) GPU support with DataParallel¶
Image classification benefits largely from GPUs. Luckily, we can continue to use
PyTorch’s abstractions in Ray Tune. Thus, we can wrap our model in nn.DataParallel
to support data parallel training on multiple GPUs:
device = "cpu"
if torch.cuda.is_available():
device = "cuda:0"
if torch.cuda.device_count() > 1:
net = nn.DataParallel(net)
net.to(device)
By using a device variable we make sure that training also works when we have
no GPUs available. PyTorch requires us to send our data to the GPU memory explicitly,
like this:
for i, data in enumerate(trainloader, 0):
inputs, labels = data
inputs, labels = inputs.to(device), labels.to(device)
The code now supports training on CPUs, on a single GPU, and on multiple GPUs. Notably, Ray also supports fractional GPUs so we can share GPUs among trials, as long as the model still fits on the GPU memory. We’ll come back to that later.
Communicating with Ray Tune¶
The most interesting part is the communication with Ray Tune:
with tune.checkpoint_dir(epoch) as checkpoint_dir:
path = os.path.join(checkpoint_dir, "checkpoint")
torch.save((net.state_dict(), optimizer.state_dict()), path)
tune.report(loss=(val_loss / val_steps), accuracy=correct / total)
Here we first save a checkpoint and then report some metrics back to Ray Tune. Specifically, we send the validation loss and accuracy back to Ray Tune. Ray Tune can then use these metrics to decide which hyperparameter configuration lead to the best results. These metrics can also be used to stop bad performing trials early in order to avoid wasting resources on those trials.
The checkpoint saving is optional, however, it is necessary if we wanted to use advanced schedulers like Population Based Training. Also, by saving the checkpoint we can later load the trained models and validate them on a test set.
Full training function¶
The full code example looks like this:
def train_cifar(config, checkpoint_dir=None, data_dir=None):
net = Net(config["l1"], config["l2"])
device = "cpu"
if torch.cuda.is_available():
device = "cuda:0"
if torch.cuda.device_count() > 1:
net = nn.DataParallel(net)
net.to(device)
criterion = nn.CrossEntropyLoss()
optimizer = optim.SGD(net.parameters(), lr=config["lr"], momentum=0.9)
if checkpoint_dir:
model_state, optimizer_state = torch.load(
os.path.join(checkpoint_dir, "checkpoint"))
net.load_state_dict(model_state)
optimizer.load_state_dict(optimizer_state)
trainset, testset = load_data(data_dir)
test_abs = int(len(trainset) * 0.8)
train_subset, val_subset = random_split(
trainset, [test_abs, len(trainset) - test_abs])
trainloader = torch.utils.data.DataLoader(
train_subset,
batch_size=int(config["batch_size"]),
shuffle=True,
num_workers=8)
valloader = torch.utils.data.DataLoader(
val_subset,
batch_size=int(config["batch_size"]),
shuffle=True,
num_workers=8)
for epoch in range(10): # loop over the dataset multiple times
running_loss = 0.0
epoch_steps = 0
for i, data in enumerate(trainloader, 0):
# get the inputs; data is a list of [inputs, labels]
inputs, labels = data
inputs, labels = inputs.to(device), labels.to(device)
# zero the parameter gradients
optimizer.zero_grad()
# forward + backward + optimize
outputs = net(inputs)
loss = criterion(outputs, labels)
loss.backward()
optimizer.step()
# print statistics
running_loss += loss.item()
epoch_steps += 1
if i % 2000 == 1999: # print every 2000 mini-batches
print("[%d, %5d] loss: %.3f" % (epoch + 1, i + 1,
running_loss / epoch_steps))
running_loss = 0.0
# Validation loss
val_loss = 0.0
val_steps = 0
total = 0
correct = 0
for i, data in enumerate(valloader, 0):
with torch.no_grad():
inputs, labels = data
inputs, labels = inputs.to(device), labels.to(device)
outputs = net(inputs)
_, predicted = torch.max(outputs.data, 1)
total += labels.size(0)
correct += (predicted == labels).sum().item()
loss = criterion(outputs, labels)
val_loss += loss.cpu().numpy()
val_steps += 1
with tune.checkpoint_dir(epoch) as checkpoint_dir:
path = os.path.join(checkpoint_dir, "checkpoint")
torch.save((net.state_dict(), optimizer.state_dict()), path)
tune.report(loss=(val_loss / val_steps), accuracy=correct / total)
print("Finished Training")
As you can see, most of the code is adapted directly from the original example.
Test set accuracy¶
Commonly the performance of a machine learning model is tested on a hold-out test set with data that has not been used for training the model. We also wrap this in a function:
def test_accuracy(net, device="cpu"):
trainset, testset = load_data()
testloader = torch.utils.data.DataLoader(
testset, batch_size=4, shuffle=False, num_workers=2)
correct = 0
total = 0
with torch.no_grad():
for data in testloader:
images, labels = data
images, labels = images.to(device), labels.to(device)
outputs = net(images)
_, predicted = torch.max(outputs.data, 1)
total += labels.size(0)
correct += (predicted == labels).sum().item()
return correct / total
The function also expects a device parameter, so we can do the
test set validation on a GPU.
Configuring the search space¶
Lastly, we need to define Ray Tune’s search space. Here is an example:
config = {
"l1": tune.sample_from(lambda _: 2**np.random.randint(2, 9)),
"l2": tune.sample_from(lambda _: 2**np.random.randint(2, 9)),
"lr": tune.loguniform(1e-4, 1e-1),
"batch_size": tune.choice([2, 4, 8, 16])
}
The tune.sample_from() function makes it possible to define your own sample
methods to obtain hyperparameters. In this example, the l1 and l2 parameters
should be powers of 2 between 4 and 256, so either 4, 8, 16, 32, 64, 128, or 256.
The lr (learning rate) should be uniformly sampled between 0.0001 and 0.1. Lastly,
the batch size is a choice between 2, 4, 8, and 16.
At each trial, Ray Tune will now randomly sample a combination of parameters from these
search spaces. It will then train a number of models in parallel and find the best
performing one among these. We also use the ASHAScheduler which will terminate bad
performing trials early.
We wrap the train_cifar function with functools.partial to set the constant
data_dir parameter. We can also tell Ray Tune what resources should be
available for each trial:
gpus_per_trial = 2
# ...
result = tune.run(
partial(train_cifar, data_dir=data_dir),
resources_per_trial={"cpu": 8, "gpu": gpus_per_trial},
config=config,
num_samples=num_samples,
scheduler=scheduler,
progress_reporter=reporter,
checkpoint_at_end=True)
You can specify the number of CPUs, which are then available e.g.
to increase the num_workers of the PyTorch DataLoader instances. The selected
number of GPUs are made visible to PyTorch in each trial. Trials do not have access to
GPUs that haven’t been requested for them - so you don’t have to care about two trials
using the same set of resources.
Here we can also specify fractional GPUs, so something like gpus_per_trial=0.5 is
completely valid. The trials will then share GPUs among each other.
You just have to make sure that the models still fit in the GPU memory.
After training the models, we will find the best performing one and load the trained network from the checkpoint file. We then obtain the test set accuracy and report everything by printing.
The full main function looks like this:
def main(num_samples=10, max_num_epochs=10, gpus_per_trial=2):
data_dir = os.path.abspath("./data")
load_data(data_dir)
config = {
"l1": tune.sample_from(lambda _: 2 ** np.random.randint(2, 9)),
"l2": tune.sample_from(lambda _: 2 ** np.random.randint(2, 9)),
"lr": tune.loguniform(1e-4, 1e-1),
"batch_size": tune.choice([2, 4, 8, 16])
}
scheduler = ASHAScheduler(
metric="loss",
mode="min",
max_t=max_num_epochs,
grace_period=1,
reduction_factor=2)
reporter = CLIReporter(
# parameter_columns=["l1", "l2", "lr", "batch_size"],
metric_columns=["loss", "accuracy", "training_iteration"])
result = tune.run(
partial(train_cifar, data_dir=data_dir),
resources_per_trial={"cpu": 2, "gpu": gpus_per_trial},
config=config,
num_samples=num_samples,
scheduler=scheduler,
progress_reporter=reporter)
best_trial = result.get_best_trial("loss", "min", "last")
print("Best trial config: {}".format(best_trial.config))
print("Best trial final validation loss: {}".format(
best_trial.last_result["loss"]))
print("Best trial final validation accuracy: {}".format(
best_trial.last_result["accuracy"]))
best_trained_model = Net(best_trial.config["l1"], best_trial.config["l2"])
device = "cpu"
if torch.cuda.is_available():
device = "cuda:0"
if gpus_per_trial > 1:
best_trained_model = nn.DataParallel(best_trained_model)
best_trained_model.to(device)
best_checkpoint_dir = best_trial.checkpoint.value
model_state, optimizer_state = torch.load(os.path.join(
best_checkpoint_dir, "checkpoint"))
best_trained_model.load_state_dict(model_state)
test_acc = test_accuracy(best_trained_model, device)
print("Best trial test set accuracy: {}".format(test_acc))
if __name__ == "__main__":
# You can change the number of GPUs per trial here:
main(num_samples=10, max_num_epochs=10, gpus_per_trial=0)
Out:
Downloading https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz to /var/lib/jenkins/workspace/beginner_source/data/cifar-10-python.tar.gz
Extracting /var/lib/jenkins/workspace/beginner_source/data/cifar-10-python.tar.gz to /var/lib/jenkins/workspace/beginner_source/data
Files already downloaded and verified
== Status ==
Memory usage on this node: 4.4/240.1 GiB
Using AsyncHyperBand: num_stopped=0
Bracket: Iter 8.000: None | Iter 4.000: None | Iter 2.000: None | Iter 1.000: None
Resources requested: 2.0/32 CPUs, 0/2 GPUs, 0.0/220.15 GiB heap, 0.0/9.31 GiB objects (0.0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-05-06_14-39-11
Number of trials: 10/10 (9 PENDING, 1 RUNNING)
+---------------------+----------+-------+--------------+------+------+-------------+
| Trial name | status | loc | batch_size | l1 | l2 | lr |
|---------------------+----------+-------+--------------+------+------+-------------|
| DEFAULT_d2654_00000 | RUNNING | | 4 | 64 | 16 | 0.0599786 |
| DEFAULT_d2654_00001 | PENDING | | 4 | 64 | 8 | 0.00349993 |
| DEFAULT_d2654_00002 | PENDING | | 16 | 16 | 256 | 0.0115781 |
| DEFAULT_d2654_00003 | PENDING | | 2 | 16 | 256 | 0.000120934 |
| DEFAULT_d2654_00004 | PENDING | | 2 | 16 | 128 | 0.00549648 |
| DEFAULT_d2654_00005 | PENDING | | 8 | 128 | 64 | 0.0655931 |
| DEFAULT_d2654_00006 | PENDING | | 8 | 256 | 16 | 0.011964 |
| DEFAULT_d2654_00007 | PENDING | | 2 | 4 | 8 | 0.000680871 |
| DEFAULT_d2654_00008 | PENDING | | 4 | 256 | 4 | 0.0336954 |
| DEFAULT_d2654_00009 | PENDING | | 4 | 32 | 128 | 0.00180151 |
+---------------------+----------+-------+--------------+------+------+-------------+
[2m[36m(pid=1463)[0m Files already downloaded and verified
[2m[36m(pid=1494)[0m Files already downloaded and verified
[2m[36m(pid=1505)[0m Files already downloaded and verified
[2m[36m(pid=1486)[0m Files already downloaded and verified
[2m[36m(pid=1496)[0m Files already downloaded and verified
[2m[36m(pid=1481)[0m Files already downloaded and verified
[2m[36m(pid=1512)[0m Files already downloaded and verified
[2m[36m(pid=1484)[0m Files already downloaded and verified
[2m[36m(pid=1461)[0m Files already downloaded and verified
[2m[36m(pid=1445)[0m Files already downloaded and verified
[2m[36m(pid=1463)[0m Files already downloaded and verified
[2m[36m(pid=1494)[0m Files already downloaded and verified
[2m[36m(pid=1505)[0m Files already downloaded and verified
[2m[36m(pid=1486)[0m Files already downloaded and verified
[2m[36m(pid=1496)[0m Files already downloaded and verified
[2m[36m(pid=1481)[0m Files already downloaded and verified
[2m[36m(pid=1512)[0m Files already downloaded and verified
[2m[36m(pid=1484)[0m Files already downloaded and verified
[2m[36m(pid=1461)[0m Files already downloaded and verified
[2m[36m(pid=1445)[0m Files already downloaded and verified
[2m[36m(pid=1505)[0m [1, 2000] loss: 2.308
[2m[36m(pid=1494)[0m [1, 2000] loss: 2.303
[2m[36m(pid=1486)[0m [1, 2000] loss: 2.137
[2m[36m(pid=1512)[0m [1, 2000] loss: 2.151
[2m[36m(pid=1461)[0m [1, 2000] loss: 2.337
[2m[36m(pid=1445)[0m [1, 2000] loss: 2.078
[2m[36m(pid=1463)[0m [1, 2000] loss: 2.319
[2m[36m(pid=1481)[0m [1, 2000] loss: 1.968
[2m[36m(pid=1484)[0m [1, 2000] loss: 2.317
[2m[36m(pid=1496)[0m [1, 2000] loss: 1.758
[2m[36m(pid=1505)[0m [1, 4000] loss: 1.148
[2m[36m(pid=1494)[0m [1, 4000] loss: 1.152
[2m[36m(pid=1486)[0m [1, 4000] loss: 1.017
[2m[36m(pid=1512)[0m [1, 4000] loss: 0.949
[2m[36m(pid=1445)[0m [1, 4000] loss: 0.863
Result for DEFAULT_d2654_00002:
accuracy: 0.4496
date: 2021-05-06_14-39-38
done: false
experiment_id: ad33da5cc5d649fe88b286a521ffc370
hostname: 9fb0856230de
iterations_since_restore: 1
loss: 1.5371887007713319
node_ip: 172.17.0.2
pid: 1496
should_checkpoint: true
time_since_restore: 25.80701780319214
time_this_iter_s: 25.80701780319214
time_total_s: 25.80701780319214
timestamp: 1620311978
timesteps_since_restore: 0
training_iteration: 1
trial_id: d2654_00002
== Status ==
Memory usage on this node: 9.5/240.1 GiB
Using AsyncHyperBand: num_stopped=0
Bracket: Iter 8.000: None | Iter 4.000: None | Iter 2.000: None | Iter 1.000: -1.5371887007713319
Resources requested: 20.0/32 CPUs, 0/2 GPUs, 0.0/220.15 GiB heap, 0.0/9.31 GiB objects (0.0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-05-06_14-39-11
Number of trials: 10/10 (10 RUNNING)
+---------------------+----------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name | status | loc | batch_size | l1 | l2 | lr | loss | accuracy | training_iteration |
|---------------------+----------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_d2654_00000 | RUNNING | | 4 | 64 | 16 | 0.0599786 | | | |
| DEFAULT_d2654_00001 | RUNNING | | 4 | 64 | 8 | 0.00349993 | | | |
| DEFAULT_d2654_00002 | RUNNING | 172.17.0.2:1496 | 16 | 16 | 256 | 0.0115781 | 1.53719 | 0.4496 | 1 |
| DEFAULT_d2654_00003 | RUNNING | | 2 | 16 | 256 | 0.000120934 | | | |
| DEFAULT_d2654_00004 | RUNNING | | 2 | 16 | 128 | 0.00549648 | | | |
| DEFAULT_d2654_00005 | RUNNING | | 8 | 128 | 64 | 0.0655931 | | | |
| DEFAULT_d2654_00006 | RUNNING | | 8 | 256 | 16 | 0.011964 | | | |
| DEFAULT_d2654_00007 | RUNNING | | 2 | 4 | 8 | 0.000680871 | | | |
| DEFAULT_d2654_00008 | RUNNING | | 4 | 256 | 4 | 0.0336954 | | | |
| DEFAULT_d2654_00009 | RUNNING | | 4 | 32 | 128 | 0.00180151 | | | |
+---------------------+----------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
[2m[36m(pid=1461)[0m [1, 4000] loss: 1.169
[2m[36m(pid=1481)[0m [1, 4000] loss: 0.863
[2m[36m(pid=1463)[0m [1, 4000] loss: 1.161
[2m[36m(pid=1484)[0m [1, 4000] loss: 1.160
[2m[36m(pid=1505)[0m [1, 6000] loss: 0.732
[2m[36m(pid=1494)[0m [1, 6000] loss: 0.767
[2m[36m(pid=1486)[0m [1, 6000] loss: 0.675
[2m[36m(pid=1512)[0m [1, 6000] loss: 0.589
[2m[36m(pid=1445)[0m [1, 6000] loss: 0.534
[2m[36m(pid=1461)[0m [1, 6000] loss: 0.779
Result for DEFAULT_d2654_00006:
accuracy: 0.3653
date: 2021-05-06_14-39-53
done: true
experiment_id: 158f34b54d99463bada3e6628e68627b
hostname: 9fb0856230de
iterations_since_restore: 1
loss: 1.7261611740589142
node_ip: 172.17.0.2
pid: 1481
should_checkpoint: true
time_since_restore: 40.4962215423584
time_this_iter_s: 40.4962215423584
time_total_s: 40.4962215423584
timestamp: 1620311993
timesteps_since_restore: 0
training_iteration: 1
trial_id: d2654_00006
== Status ==
Memory usage on this node: 9.5/240.1 GiB
Using AsyncHyperBand: num_stopped=1
Bracket: Iter 8.000: None | Iter 4.000: None | Iter 2.000: None | Iter 1.000: -1.6316749374151231
Resources requested: 20.0/32 CPUs, 0/2 GPUs, 0.0/220.15 GiB heap, 0.0/9.31 GiB objects (0.0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-05-06_14-39-11
Number of trials: 10/10 (10 RUNNING)
+---------------------+----------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name | status | loc | batch_size | l1 | l2 | lr | loss | accuracy | training_iteration |
|---------------------+----------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_d2654_00000 | RUNNING | | 4 | 64 | 16 | 0.0599786 | | | |
| DEFAULT_d2654_00001 | RUNNING | | 4 | 64 | 8 | 0.00349993 | | | |
| DEFAULT_d2654_00002 | RUNNING | 172.17.0.2:1496 | 16 | 16 | 256 | 0.0115781 | 1.53719 | 0.4496 | 1 |
| DEFAULT_d2654_00003 | RUNNING | | 2 | 16 | 256 | 0.000120934 | | | |
| DEFAULT_d2654_00004 | RUNNING | | 2 | 16 | 128 | 0.00549648 | | | |
| DEFAULT_d2654_00005 | RUNNING | | 8 | 128 | 64 | 0.0655931 | | | |
| DEFAULT_d2654_00006 | RUNNING | 172.17.0.2:1481 | 8 | 256 | 16 | 0.011964 | 1.72616 | 0.3653 | 1 |
| DEFAULT_d2654_00007 | RUNNING | | 2 | 4 | 8 | 0.000680871 | | | |
| DEFAULT_d2654_00008 | RUNNING | | 4 | 256 | 4 | 0.0336954 | | | |
| DEFAULT_d2654_00009 | RUNNING | | 4 | 32 | 128 | 0.00180151 | | | |
+---------------------+----------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
[2m[36m(pid=1496)[0m [2, 2000] loss: 1.486
[2m[36m(pid=1505)[0m [1, 8000] loss: 0.510
[2m[36m(pid=1494)[0m [1, 8000] loss: 0.575
[2m[36m(pid=1486)[0m [1, 8000] loss: 0.503
Result for DEFAULT_d2654_00005:
accuracy: 0.1057
date: 2021-05-06_14-39-55
done: true
experiment_id: 749ddbf1fdde447bae542cc444ab506e
hostname: 9fb0856230de
iterations_since_restore: 1
loss: 2.307231892967224
node_ip: 172.17.0.2
pid: 1484
should_checkpoint: true
time_since_restore: 42.92941236495972
time_this_iter_s: 42.92941236495972
time_total_s: 42.92941236495972
timestamp: 1620311995
timesteps_since_restore: 0
training_iteration: 1
trial_id: d2654_00005
[2m[36m(pid=1463)[0m [1, 6000] loss: 0.774
[2m[36m(pid=1512)[0m [1, 8000] loss: 0.424
[2m[36m(pid=1445)[0m [1, 8000] loss: 0.385
Result for DEFAULT_d2654_00002:
accuracy: 0.4801
date: 2021-05-06_14-40-00
done: false
experiment_id: ad33da5cc5d649fe88b286a521ffc370
hostname: 9fb0856230de
iterations_since_restore: 2
loss: 1.4437916863441467
node_ip: 172.17.0.2
pid: 1496
should_checkpoint: true
time_since_restore: 47.444332122802734
time_this_iter_s: 21.637314319610596
time_total_s: 47.444332122802734
timestamp: 1620312000
timesteps_since_restore: 0
training_iteration: 2
trial_id: d2654_00002
== Status ==
Memory usage on this node: 8.4/240.1 GiB
Using AsyncHyperBand: num_stopped=2
Bracket: Iter 8.000: None | Iter 4.000: None | Iter 2.000: -1.4437916863441467 | Iter 1.000: -1.7261611740589142
Resources requested: 16.0/32 CPUs, 0/2 GPUs, 0.0/220.15 GiB heap, 0.0/9.31 GiB objects (0.0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-05-06_14-39-11
Number of trials: 10/10 (8 RUNNING, 2 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name | status | loc | batch_size | l1 | l2 | lr | loss | accuracy | training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_d2654_00000 | RUNNING | | 4 | 64 | 16 | 0.0599786 | | | |
| DEFAULT_d2654_00001 | RUNNING | | 4 | 64 | 8 | 0.00349993 | | | |
| DEFAULT_d2654_00002 | RUNNING | 172.17.0.2:1496 | 16 | 16 | 256 | 0.0115781 | 1.44379 | 0.4801 | 2 |
| DEFAULT_d2654_00003 | RUNNING | | 2 | 16 | 256 | 0.000120934 | | | |
| DEFAULT_d2654_00004 | RUNNING | | 2 | 16 | 128 | 0.00549648 | | | |
| DEFAULT_d2654_00007 | RUNNING | | 2 | 4 | 8 | 0.000680871 | | | |
| DEFAULT_d2654_00008 | RUNNING | | 4 | 256 | 4 | 0.0336954 | | | |
| DEFAULT_d2654_00009 | RUNNING | | 4 | 32 | 128 | 0.00180151 | | | |
| DEFAULT_d2654_00005 | TERMINATED | | 8 | 128 | 64 | 0.0655931 | 2.30723 | 0.1057 | 1 |
| DEFAULT_d2654_00006 | TERMINATED | | 8 | 256 | 16 | 0.011964 | 1.72616 | 0.3653 | 1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
[2m[36m(pid=1461)[0m [1, 8000] loss: 0.584
[2m[36m(pid=1505)[0m [1, 10000] loss: 0.389
[2m[36m(pid=1494)[0m [1, 10000] loss: 0.458
[2m[36m(pid=1486)[0m [1, 10000] loss: 0.406
[2m[36m(pid=1512)[0m [1, 10000] loss: 0.327
[2m[36m(pid=1445)[0m [1, 10000] loss: 0.298
[2m[36m(pid=1463)[0m [1, 8000] loss: 0.580
[2m[36m(pid=1461)[0m [1, 10000] loss: 0.468
[2m[36m(pid=1505)[0m [1, 12000] loss: 0.313
[2m[36m(pid=1494)[0m [1, 12000] loss: 0.371
[2m[36m(pid=1486)[0m [1, 12000] loss: 0.342
[2m[36m(pid=1496)[0m [3, 2000] loss: 1.430
Result for DEFAULT_d2654_00009:
accuracy: 0.4679
date: 2021-05-06_14-40-14
done: false
experiment_id: 5f342aed5b9c4085b4b4591e9b3d7862
hostname: 9fb0856230de
iterations_since_restore: 1
loss: 1.4610946264266969
node_ip: 172.17.0.2
pid: 1445
should_checkpoint: true
time_since_restore: 62.10507845878601
time_this_iter_s: 62.10507845878601
time_total_s: 62.10507845878601
timestamp: 1620312014
timesteps_since_restore: 0
training_iteration: 1
trial_id: d2654_00009
== Status ==
Memory usage on this node: 8.5/240.1 GiB
Using AsyncHyperBand: num_stopped=2
Bracket: Iter 8.000: None | Iter 4.000: None | Iter 2.000: -1.4437916863441467 | Iter 1.000: -1.6316749374151231
Resources requested: 16.0/32 CPUs, 0/2 GPUs, 0.0/220.15 GiB heap, 0.0/9.31 GiB objects (0.0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-05-06_14-39-11
Number of trials: 10/10 (8 RUNNING, 2 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name | status | loc | batch_size | l1 | l2 | lr | loss | accuracy | training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_d2654_00000 | RUNNING | | 4 | 64 | 16 | 0.0599786 | | | |
| DEFAULT_d2654_00001 | RUNNING | | 4 | 64 | 8 | 0.00349993 | | | |
| DEFAULT_d2654_00002 | RUNNING | 172.17.0.2:1496 | 16 | 16 | 256 | 0.0115781 | 1.44379 | 0.4801 | 2 |
| DEFAULT_d2654_00003 | RUNNING | | 2 | 16 | 256 | 0.000120934 | | | |
| DEFAULT_d2654_00004 | RUNNING | | 2 | 16 | 128 | 0.00549648 | | | |
| DEFAULT_d2654_00007 | RUNNING | | 2 | 4 | 8 | 0.000680871 | | | |
| DEFAULT_d2654_00008 | RUNNING | | 4 | 256 | 4 | 0.0336954 | | | |
| DEFAULT_d2654_00009 | RUNNING | 172.17.0.2:1445 | 4 | 32 | 128 | 0.00180151 | 1.46109 | 0.4679 | 1 |
| DEFAULT_d2654_00005 | TERMINATED | | 8 | 128 | 64 | 0.0655931 | 2.30723 | 0.1057 | 1 |
| DEFAULT_d2654_00006 | TERMINATED | | 8 | 256 | 16 | 0.011964 | 1.72616 | 0.3653 | 1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
Result for DEFAULT_d2654_00001:
accuracy: 0.4048
date: 2021-05-06_14-40-14
done: false
experiment_id: 7ba6badde949462fbe9af86eaa37ae9a
hostname: 9fb0856230de
iterations_since_restore: 1
loss: 1.616072942686081
node_ip: 172.17.0.2
pid: 1512
should_checkpoint: true
time_since_restore: 62.22814702987671
time_this_iter_s: 62.22814702987671
time_total_s: 62.22814702987671
timestamp: 1620312014
timesteps_since_restore: 0
training_iteration: 1
trial_id: d2654_00001
Result for DEFAULT_d2654_00000:
accuracy: 0.1016
date: 2021-05-06_14-40-18
done: true
experiment_id: 0cd621c4022f448db6a3fc340e7dd827
hostname: 9fb0856230de
iterations_since_restore: 1
loss: 2.3339930344581603
node_ip: 172.17.0.2
pid: 1461
should_checkpoint: true
time_since_restore: 66.20879554748535
time_this_iter_s: 66.20879554748535
time_total_s: 66.20879554748535
timestamp: 1620312018
timesteps_since_restore: 0
training_iteration: 1
trial_id: d2654_00000
[2m[36m(pid=1505)[0m [1, 14000] loss: 0.260
[2m[36m(pid=1494)[0m [1, 14000] loss: 0.298
Result for DEFAULT_d2654_00002:
accuracy: 0.4755
date: 2021-05-06_14-40-20
done: false
experiment_id: ad33da5cc5d649fe88b286a521ffc370
hostname: 9fb0856230de
iterations_since_restore: 3
loss: 1.4848108874320984
node_ip: 172.17.0.2
pid: 1496
should_checkpoint: true
time_since_restore: 68.15727639198303
time_this_iter_s: 20.712944269180298
time_total_s: 68.15727639198303
timestamp: 1620312020
timesteps_since_restore: 0
training_iteration: 3
trial_id: d2654_00002
== Status ==
Memory usage on this node: 7.9/240.1 GiB
Using AsyncHyperBand: num_stopped=3
Bracket: Iter 8.000: None | Iter 4.000: None | Iter 2.000: -1.4437916863441467 | Iter 1.000: -1.6711170583724977
Resources requested: 14.0/32 CPUs, 0/2 GPUs, 0.0/220.15 GiB heap, 0.0/9.31 GiB objects (0.0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-05-06_14-39-11
Number of trials: 10/10 (7 RUNNING, 3 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name | status | loc | batch_size | l1 | l2 | lr | loss | accuracy | training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_d2654_00001 | RUNNING | 172.17.0.2:1512 | 4 | 64 | 8 | 0.00349993 | 1.61607 | 0.4048 | 1 |
| DEFAULT_d2654_00002 | RUNNING | 172.17.0.2:1496 | 16 | 16 | 256 | 0.0115781 | 1.48481 | 0.4755 | 3 |
| DEFAULT_d2654_00003 | RUNNING | | 2 | 16 | 256 | 0.000120934 | | | |
| DEFAULT_d2654_00004 | RUNNING | | 2 | 16 | 128 | 0.00549648 | | | |
| DEFAULT_d2654_00007 | RUNNING | | 2 | 4 | 8 | 0.000680871 | | | |
| DEFAULT_d2654_00008 | RUNNING | | 4 | 256 | 4 | 0.0336954 | | | |
| DEFAULT_d2654_00009 | RUNNING | 172.17.0.2:1445 | 4 | 32 | 128 | 0.00180151 | 1.46109 | 0.4679 | 1 |
| DEFAULT_d2654_00000 | TERMINATED | | 4 | 64 | 16 | 0.0599786 | 2.33399 | 0.1016 | 1 |
| DEFAULT_d2654_00005 | TERMINATED | | 8 | 128 | 64 | 0.0655931 | 2.30723 | 0.1057 | 1 |
| DEFAULT_d2654_00006 | TERMINATED | | 8 | 256 | 16 | 0.011964 | 1.72616 | 0.3653 | 1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
[2m[36m(pid=1486)[0m [1, 14000] loss: 0.289
[2m[36m(pid=1463)[0m [1, 10000] loss: 0.464
[2m[36m(pid=1445)[0m [2, 2000] loss: 1.435
[2m[36m(pid=1512)[0m [2, 2000] loss: 1.616
[2m[36m(pid=1505)[0m [1, 16000] loss: 0.222
[2m[36m(pid=1494)[0m [1, 16000] loss: 0.254
Result for DEFAULT_d2654_00008:
accuracy: 0.1004
date: 2021-05-06_14-40-30
done: true
experiment_id: 45ef9f51bc1c4c48bc2c4dc2408a2ff0
hostname: 9fb0856230de
iterations_since_restore: 1
loss: 2.315009035873413
node_ip: 172.17.0.2
pid: 1463
should_checkpoint: true
time_since_restore: 77.48415780067444
time_this_iter_s: 77.48415780067444
time_total_s: 77.48415780067444
timestamp: 1620312030
timesteps_since_restore: 0
training_iteration: 1
trial_id: d2654_00008
== Status ==
Memory usage on this node: 7.9/240.1 GiB
Using AsyncHyperBand: num_stopped=4
Bracket: Iter 8.000: None | Iter 4.000: None | Iter 2.000: -1.4437916863441467 | Iter 1.000: -1.7261611740589142
Resources requested: 14.0/32 CPUs, 0/2 GPUs, 0.0/220.15 GiB heap, 0.0/9.31 GiB objects (0.0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-05-06_14-39-11
Number of trials: 10/10 (7 RUNNING, 3 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name | status | loc | batch_size | l1 | l2 | lr | loss | accuracy | training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_d2654_00001 | RUNNING | 172.17.0.2:1512 | 4 | 64 | 8 | 0.00349993 | 1.61607 | 0.4048 | 1 |
| DEFAULT_d2654_00002 | RUNNING | 172.17.0.2:1496 | 16 | 16 | 256 | 0.0115781 | 1.48481 | 0.4755 | 3 |
| DEFAULT_d2654_00003 | RUNNING | | 2 | 16 | 256 | 0.000120934 | | | |
| DEFAULT_d2654_00004 | RUNNING | | 2 | 16 | 128 | 0.00549648 | | | |
| DEFAULT_d2654_00007 | RUNNING | | 2 | 4 | 8 | 0.000680871 | | | |
| DEFAULT_d2654_00008 | RUNNING | 172.17.0.2:1463 | 4 | 256 | 4 | 0.0336954 | 2.31501 | 0.1004 | 1 |
| DEFAULT_d2654_00009 | RUNNING | 172.17.0.2:1445 | 4 | 32 | 128 | 0.00180151 | 1.46109 | 0.4679 | 1 |
| DEFAULT_d2654_00000 | TERMINATED | | 4 | 64 | 16 | 0.0599786 | 2.33399 | 0.1016 | 1 |
| DEFAULT_d2654_00005 | TERMINATED | | 8 | 128 | 64 | 0.0655931 | 2.30723 | 0.1057 | 1 |
| DEFAULT_d2654_00006 | TERMINATED | | 8 | 256 | 16 | 0.011964 | 1.72616 | 0.3653 | 1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
[2m[36m(pid=1486)[0m [1, 16000] loss: 0.250
[2m[36m(pid=1445)[0m [2, 4000] loss: 0.706
[2m[36m(pid=1512)[0m [2, 4000] loss: 0.808
[2m[36m(pid=1496)[0m [4, 2000] loss: 1.392
[2m[36m(pid=1505)[0m [1, 18000] loss: 0.193
[2m[36m(pid=1494)[0m [1, 18000] loss: 0.219
[2m[36m(pid=1486)[0m [1, 18000] loss: 0.227
Result for DEFAULT_d2654_00002:
accuracy: 0.4994
date: 2021-05-06_14-40-40
done: false
experiment_id: ad33da5cc5d649fe88b286a521ffc370
hostname: 9fb0856230de
iterations_since_restore: 4
loss: 1.4167865670204163
node_ip: 172.17.0.2
pid: 1496
should_checkpoint: true
time_since_restore: 87.83202886581421
time_this_iter_s: 19.674752473831177
time_total_s: 87.83202886581421
timestamp: 1620312040
timesteps_since_restore: 0
training_iteration: 4
trial_id: d2654_00002
== Status ==
Memory usage on this node: 7.4/240.1 GiB
Using AsyncHyperBand: num_stopped=4
Bracket: Iter 8.000: None | Iter 4.000: -1.4167865670204163 | Iter 2.000: -1.4437916863441467 | Iter 1.000: -1.7261611740589142
Resources requested: 12.0/32 CPUs, 0/2 GPUs, 0.0/220.15 GiB heap, 0.0/9.31 GiB objects (0.0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-05-06_14-39-11
Number of trials: 10/10 (6 RUNNING, 4 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name | status | loc | batch_size | l1 | l2 | lr | loss | accuracy | training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_d2654_00001 | RUNNING | 172.17.0.2:1512 | 4 | 64 | 8 | 0.00349993 | 1.61607 | 0.4048 | 1 |
| DEFAULT_d2654_00002 | RUNNING | 172.17.0.2:1496 | 16 | 16 | 256 | 0.0115781 | 1.41679 | 0.4994 | 4 |
| DEFAULT_d2654_00003 | RUNNING | | 2 | 16 | 256 | 0.000120934 | | | |
| DEFAULT_d2654_00004 | RUNNING | | 2 | 16 | 128 | 0.00549648 | | | |
| DEFAULT_d2654_00007 | RUNNING | | 2 | 4 | 8 | 0.000680871 | | | |
| DEFAULT_d2654_00009 | RUNNING | 172.17.0.2:1445 | 4 | 32 | 128 | 0.00180151 | 1.46109 | 0.4679 | 1 |
| DEFAULT_d2654_00000 | TERMINATED | | 4 | 64 | 16 | 0.0599786 | 2.33399 | 0.1016 | 1 |
| DEFAULT_d2654_00005 | TERMINATED | | 8 | 128 | 64 | 0.0655931 | 2.30723 | 0.1057 | 1 |
| DEFAULT_d2654_00006 | TERMINATED | | 8 | 256 | 16 | 0.011964 | 1.72616 | 0.3653 | 1 |
| DEFAULT_d2654_00008 | TERMINATED | | 4 | 256 | 4 | 0.0336954 | 2.31501 | 0.1004 | 1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
[2m[36m(pid=1445)[0m [2, 6000] loss: 0.473
[2m[36m(pid=1512)[0m [2, 6000] loss: 0.530
[2m[36m(pid=1505)[0m [1, 20000] loss: 0.175
[2m[36m(pid=1494)[0m [1, 20000] loss: 0.193
[2m[36m(pid=1486)[0m [1, 20000] loss: 0.208
[2m[36m(pid=1445)[0m [2, 8000] loss: 0.351
[2m[36m(pid=1512)[0m [2, 8000] loss: 0.391
[2m[36m(pid=1496)[0m [5, 2000] loss: 1.391
Result for DEFAULT_d2654_00007:
accuracy: 0.342
date: 2021-05-06_14-40-57
done: false
experiment_id: 94907e92f16447f2a245bc213f3d9ce5
hostname: 9fb0856230de
iterations_since_restore: 1
loss: 1.6944544432878494
node_ip: 172.17.0.2
pid: 1505
should_checkpoint: true
time_since_restore: 104.46621584892273
time_this_iter_s: 104.46621584892273
time_total_s: 104.46621584892273
timestamp: 1620312057
timesteps_since_restore: 0
training_iteration: 1
trial_id: d2654_00007
== Status ==
Memory usage on this node: 7.4/240.1 GiB
Using AsyncHyperBand: num_stopped=4
Bracket: Iter 8.000: None | Iter 4.000: -1.4167865670204163 | Iter 2.000: -1.4437916863441467 | Iter 1.000: -1.7103078086733818
Resources requested: 12.0/32 CPUs, 0/2 GPUs, 0.0/220.15 GiB heap, 0.0/9.31 GiB objects (0.0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-05-06_14-39-11
Number of trials: 10/10 (6 RUNNING, 4 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name | status | loc | batch_size | l1 | l2 | lr | loss | accuracy | training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_d2654_00001 | RUNNING | 172.17.0.2:1512 | 4 | 64 | 8 | 0.00349993 | 1.61607 | 0.4048 | 1 |
| DEFAULT_d2654_00002 | RUNNING | 172.17.0.2:1496 | 16 | 16 | 256 | 0.0115781 | 1.41679 | 0.4994 | 4 |
| DEFAULT_d2654_00003 | RUNNING | | 2 | 16 | 256 | 0.000120934 | | | |
| DEFAULT_d2654_00004 | RUNNING | | 2 | 16 | 128 | 0.00549648 | | | |
| DEFAULT_d2654_00007 | RUNNING | 172.17.0.2:1505 | 2 | 4 | 8 | 0.000680871 | 1.69445 | 0.342 | 1 |
| DEFAULT_d2654_00009 | RUNNING | 172.17.0.2:1445 | 4 | 32 | 128 | 0.00180151 | 1.46109 | 0.4679 | 1 |
| DEFAULT_d2654_00000 | TERMINATED | | 4 | 64 | 16 | 0.0599786 | 2.33399 | 0.1016 | 1 |
| DEFAULT_d2654_00005 | TERMINATED | | 8 | 128 | 64 | 0.0655931 | 2.30723 | 0.1057 | 1 |
| DEFAULT_d2654_00006 | TERMINATED | | 8 | 256 | 16 | 0.011964 | 1.72616 | 0.3653 | 1 |
| DEFAULT_d2654_00008 | TERMINATED | | 4 | 256 | 4 | 0.0336954 | 2.31501 | 0.1004 | 1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
Result for DEFAULT_d2654_00003:
accuracy: 0.2891
date: 2021-05-06_14-40-58
done: true
experiment_id: 19507e2d52ef467e9a469bbcea460d9d
hostname: 9fb0856230de
iterations_since_restore: 1
loss: 1.8985807675480844
node_ip: 172.17.0.2
pid: 1494
should_checkpoint: true
time_since_restore: 105.37766122817993
time_this_iter_s: 105.37766122817993
time_total_s: 105.37766122817993
timestamp: 1620312058
timesteps_since_restore: 0
training_iteration: 1
trial_id: d2654_00003
Result for DEFAULT_d2654_00002:
accuracy: 0.5051
date: 2021-05-06_14-41-00
done: false
experiment_id: ad33da5cc5d649fe88b286a521ffc370
hostname: 9fb0856230de
iterations_since_restore: 5
loss: 1.4295518489837646
node_ip: 172.17.0.2
pid: 1496
should_checkpoint: true
time_since_restore: 107.61887645721436
time_this_iter_s: 19.786847591400146
time_total_s: 107.61887645721436
timestamp: 1620312060
timesteps_since_restore: 0
training_iteration: 5
trial_id: d2654_00002
[2m[36m(pid=1445)[0m [2, 10000] loss: 0.278
Result for DEFAULT_d2654_00004:
accuracy: 0.2025
date: 2021-05-06_14-41-00
done: true
experiment_id: 3cee83ddfde94bbf9193f2b472140532
hostname: 9fb0856230de
iterations_since_restore: 1
loss: 2.10117801476717
node_ip: 172.17.0.2
pid: 1486
should_checkpoint: true
time_since_restore: 108.1444628238678
time_this_iter_s: 108.1444628238678
time_total_s: 108.1444628238678
timestamp: 1620312060
timesteps_since_restore: 0
training_iteration: 1
trial_id: d2654_00004
[2m[36m(pid=1512)[0m [2, 10000] loss: 0.313
[2m[36m(pid=1505)[0m [2, 2000] loss: 1.690
Result for DEFAULT_d2654_00009:
accuracy: 0.5045
date: 2021-05-06_14-41-06
done: false
experiment_id: 5f342aed5b9c4085b4b4591e9b3d7862
hostname: 9fb0856230de
iterations_since_restore: 2
loss: 1.3906023013353348
node_ip: 172.17.0.2
pid: 1445
should_checkpoint: true
time_since_restore: 114.17241668701172
time_this_iter_s: 52.06733822822571
time_total_s: 114.17241668701172
timestamp: 1620312066
timesteps_since_restore: 0
training_iteration: 2
trial_id: d2654_00009
== Status ==
Memory usage on this node: 6.3/240.1 GiB
Using AsyncHyperBand: num_stopped=6
Bracket: Iter 8.000: None | Iter 4.000: -1.4167865670204163 | Iter 2.000: -1.4171969938397408 | Iter 1.000: -1.8123709708034994
Resources requested: 8.0/32 CPUs, 0/2 GPUs, 0.0/220.15 GiB heap, 0.0/9.31 GiB objects (0.0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-05-06_14-39-11
Number of trials: 10/10 (4 RUNNING, 6 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name | status | loc | batch_size | l1 | l2 | lr | loss | accuracy | training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_d2654_00001 | RUNNING | 172.17.0.2:1512 | 4 | 64 | 8 | 0.00349993 | 1.61607 | 0.4048 | 1 |
| DEFAULT_d2654_00002 | RUNNING | 172.17.0.2:1496 | 16 | 16 | 256 | 0.0115781 | 1.42955 | 0.5051 | 5 |
| DEFAULT_d2654_00007 | RUNNING | 172.17.0.2:1505 | 2 | 4 | 8 | 0.000680871 | 1.69445 | 0.342 | 1 |
| DEFAULT_d2654_00009 | RUNNING | 172.17.0.2:1445 | 4 | 32 | 128 | 0.00180151 | 1.3906 | 0.5045 | 2 |
| DEFAULT_d2654_00000 | TERMINATED | | 4 | 64 | 16 | 0.0599786 | 2.33399 | 0.1016 | 1 |
| DEFAULT_d2654_00003 | TERMINATED | | 2 | 16 | 256 | 0.000120934 | 1.89858 | 0.2891 | 1 |
| DEFAULT_d2654_00004 | TERMINATED | | 2 | 16 | 128 | 0.00549648 | 2.10118 | 0.2025 | 1 |
| DEFAULT_d2654_00005 | TERMINATED | | 8 | 128 | 64 | 0.0655931 | 2.30723 | 0.1057 | 1 |
| DEFAULT_d2654_00006 | TERMINATED | | 8 | 256 | 16 | 0.011964 | 1.72616 | 0.3653 | 1 |
| DEFAULT_d2654_00008 | TERMINATED | | 4 | 256 | 4 | 0.0336954 | 2.31501 | 0.1004 | 1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
Result for DEFAULT_d2654_00001:
accuracy: 0.4321
date: 2021-05-06_14-41-07
done: true
experiment_id: 7ba6badde949462fbe9af86eaa37ae9a
hostname: 9fb0856230de
iterations_since_restore: 2
loss: 1.552844472503662
node_ip: 172.17.0.2
pid: 1512
should_checkpoint: true
time_since_restore: 114.80159831047058
time_this_iter_s: 52.57345128059387
time_total_s: 114.80159831047058
timestamp: 1620312067
timesteps_since_restore: 0
training_iteration: 2
trial_id: d2654_00001
[2m[36m(pid=1505)[0m [2, 4000] loss: 0.846
[2m[36m(pid=1496)[0m [6, 2000] loss: 1.369
[2m[36m(pid=1445)[0m [3, 2000] loss: 1.318
Result for DEFAULT_d2654_00002:
accuracy: 0.5182
date: 2021-05-06_14-41-18
done: false
experiment_id: ad33da5cc5d649fe88b286a521ffc370
hostname: 9fb0856230de
iterations_since_restore: 6
loss: 1.4147975984573364
node_ip: 172.17.0.2
pid: 1496
should_checkpoint: true
time_since_restore: 126.19647479057312
time_this_iter_s: 18.577598333358765
time_total_s: 126.19647479057312
timestamp: 1620312078
timesteps_since_restore: 0
training_iteration: 6
trial_id: d2654_00002
== Status ==
Memory usage on this node: 5.8/240.1 GiB
Using AsyncHyperBand: num_stopped=7
Bracket: Iter 8.000: None | Iter 4.000: -1.4167865670204163 | Iter 2.000: -1.4437916863441467 | Iter 1.000: -1.8123709708034994
Resources requested: 6.0/32 CPUs, 0/2 GPUs, 0.0/220.15 GiB heap, 0.0/9.31 GiB objects (0.0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-05-06_14-39-11
Number of trials: 10/10 (3 RUNNING, 7 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name | status | loc | batch_size | l1 | l2 | lr | loss | accuracy | training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_d2654_00002 | RUNNING | 172.17.0.2:1496 | 16 | 16 | 256 | 0.0115781 | 1.4148 | 0.5182 | 6 |
| DEFAULT_d2654_00007 | RUNNING | 172.17.0.2:1505 | 2 | 4 | 8 | 0.000680871 | 1.69445 | 0.342 | 1 |
| DEFAULT_d2654_00009 | RUNNING | 172.17.0.2:1445 | 4 | 32 | 128 | 0.00180151 | 1.3906 | 0.5045 | 2 |
| DEFAULT_d2654_00000 | TERMINATED | | 4 | 64 | 16 | 0.0599786 | 2.33399 | 0.1016 | 1 |
| DEFAULT_d2654_00001 | TERMINATED | | 4 | 64 | 8 | 0.00349993 | 1.55284 | 0.4321 | 2 |
| DEFAULT_d2654_00003 | TERMINATED | | 2 | 16 | 256 | 0.000120934 | 1.89858 | 0.2891 | 1 |
| DEFAULT_d2654_00004 | TERMINATED | | 2 | 16 | 128 | 0.00549648 | 2.10118 | 0.2025 | 1 |
| DEFAULT_d2654_00005 | TERMINATED | | 8 | 128 | 64 | 0.0655931 | 2.30723 | 0.1057 | 1 |
| DEFAULT_d2654_00006 | TERMINATED | | 8 | 256 | 16 | 0.011964 | 1.72616 | 0.3653 | 1 |
| DEFAULT_d2654_00008 | TERMINATED | | 4 | 256 | 4 | 0.0336954 | 2.31501 | 0.1004 | 1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
[2m[36m(pid=1505)[0m [2, 6000] loss: 0.559
[2m[36m(pid=1445)[0m [3, 4000] loss: 0.672
[2m[36m(pid=1505)[0m [2, 8000] loss: 0.408
[2m[36m(pid=1445)[0m [3, 6000] loss: 0.442
[2m[36m(pid=1496)[0m [7, 2000] loss: 1.357
[2m[36m(pid=1505)[0m [2, 10000] loss: 0.327
Result for DEFAULT_d2654_00002:
accuracy: 0.4562
date: 2021-05-06_14-41-37
done: false
experiment_id: ad33da5cc5d649fe88b286a521ffc370
hostname: 9fb0856230de
iterations_since_restore: 7
loss: 1.5811303553581237
node_ip: 172.17.0.2
pid: 1496
should_checkpoint: true
time_since_restore: 145.14386987686157
time_this_iter_s: 18.947395086288452
time_total_s: 145.14386987686157
timestamp: 1620312097
timesteps_since_restore: 0
training_iteration: 7
trial_id: d2654_00002
== Status ==
Memory usage on this node: 5.8/240.1 GiB
Using AsyncHyperBand: num_stopped=7
Bracket: Iter 8.000: None | Iter 4.000: -1.4167865670204163 | Iter 2.000: -1.4437916863441467 | Iter 1.000: -1.8123709708034994
Resources requested: 6.0/32 CPUs, 0/2 GPUs, 0.0/220.15 GiB heap, 0.0/9.31 GiB objects (0.0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-05-06_14-39-11
Number of trials: 10/10 (3 RUNNING, 7 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name | status | loc | batch_size | l1 | l2 | lr | loss | accuracy | training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_d2654_00002 | RUNNING | 172.17.0.2:1496 | 16 | 16 | 256 | 0.0115781 | 1.58113 | 0.4562 | 7 |
| DEFAULT_d2654_00007 | RUNNING | 172.17.0.2:1505 | 2 | 4 | 8 | 0.000680871 | 1.69445 | 0.342 | 1 |
| DEFAULT_d2654_00009 | RUNNING | 172.17.0.2:1445 | 4 | 32 | 128 | 0.00180151 | 1.3906 | 0.5045 | 2 |
| DEFAULT_d2654_00000 | TERMINATED | | 4 | 64 | 16 | 0.0599786 | 2.33399 | 0.1016 | 1 |
| DEFAULT_d2654_00001 | TERMINATED | | 4 | 64 | 8 | 0.00349993 | 1.55284 | 0.4321 | 2 |
| DEFAULT_d2654_00003 | TERMINATED | | 2 | 16 | 256 | 0.000120934 | 1.89858 | 0.2891 | 1 |
| DEFAULT_d2654_00004 | TERMINATED | | 2 | 16 | 128 | 0.00549648 | 2.10118 | 0.2025 | 1 |
| DEFAULT_d2654_00005 | TERMINATED | | 8 | 128 | 64 | 0.0655931 | 2.30723 | 0.1057 | 1 |
| DEFAULT_d2654_00006 | TERMINATED | | 8 | 256 | 16 | 0.011964 | 1.72616 | 0.3653 | 1 |
| DEFAULT_d2654_00008 | TERMINATED | | 4 | 256 | 4 | 0.0336954 | 2.31501 | 0.1004 | 1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
[2m[36m(pid=1445)[0m [3, 8000] loss: 0.325
[2m[36m(pid=1505)[0m [2, 12000] loss: 0.268
[2m[36m(pid=1445)[0m [3, 10000] loss: 0.270
[2m[36m(pid=1505)[0m [2, 14000] loss: 0.229
[2m[36m(pid=1496)[0m [8, 2000] loss: 1.383
Result for DEFAULT_d2654_00009:
accuracy: 0.5287
date: 2021-05-06_14-41-54
done: false
experiment_id: 5f342aed5b9c4085b4b4591e9b3d7862
hostname: 9fb0856230de
iterations_since_restore: 3
loss: 1.3108423009082675
node_ip: 172.17.0.2
pid: 1445
should_checkpoint: true
time_since_restore: 161.92914748191833
time_this_iter_s: 47.756730794906616
time_total_s: 161.92914748191833
timestamp: 1620312114
timesteps_since_restore: 0
training_iteration: 3
trial_id: d2654_00009
== Status ==
Memory usage on this node: 5.8/240.1 GiB
Using AsyncHyperBand: num_stopped=7
Bracket: Iter 8.000: None | Iter 4.000: -1.4167865670204163 | Iter 2.000: -1.4437916863441467 | Iter 1.000: -1.8123709708034994
Resources requested: 6.0/32 CPUs, 0/2 GPUs, 0.0/220.15 GiB heap, 0.0/9.31 GiB objects (0.0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-05-06_14-39-11
Number of trials: 10/10 (3 RUNNING, 7 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name | status | loc | batch_size | l1 | l2 | lr | loss | accuracy | training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_d2654_00002 | RUNNING | 172.17.0.2:1496 | 16 | 16 | 256 | 0.0115781 | 1.58113 | 0.4562 | 7 |
| DEFAULT_d2654_00007 | RUNNING | 172.17.0.2:1505 | 2 | 4 | 8 | 0.000680871 | 1.69445 | 0.342 | 1 |
| DEFAULT_d2654_00009 | RUNNING | 172.17.0.2:1445 | 4 | 32 | 128 | 0.00180151 | 1.31084 | 0.5287 | 3 |
| DEFAULT_d2654_00000 | TERMINATED | | 4 | 64 | 16 | 0.0599786 | 2.33399 | 0.1016 | 1 |
| DEFAULT_d2654_00001 | TERMINATED | | 4 | 64 | 8 | 0.00349993 | 1.55284 | 0.4321 | 2 |
| DEFAULT_d2654_00003 | TERMINATED | | 2 | 16 | 256 | 0.000120934 | 1.89858 | 0.2891 | 1 |
| DEFAULT_d2654_00004 | TERMINATED | | 2 | 16 | 128 | 0.00549648 | 2.10118 | 0.2025 | 1 |
| DEFAULT_d2654_00005 | TERMINATED | | 8 | 128 | 64 | 0.0655931 | 2.30723 | 0.1057 | 1 |
| DEFAULT_d2654_00006 | TERMINATED | | 8 | 256 | 16 | 0.011964 | 1.72616 | 0.3653 | 1 |
| DEFAULT_d2654_00008 | TERMINATED | | 4 | 256 | 4 | 0.0336954 | 2.31501 | 0.1004 | 1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
[2m[36m(pid=1505)[0m [2, 16000] loss: 0.195
Result for DEFAULT_d2654_00002:
accuracy: 0.4682
date: 2021-05-06_14-41-56
done: false
experiment_id: ad33da5cc5d649fe88b286a521ffc370
hostname: 9fb0856230de
iterations_since_restore: 8
loss: 1.5100394088745117
node_ip: 172.17.0.2
pid: 1496
should_checkpoint: true
time_since_restore: 163.8398461341858
time_this_iter_s: 18.69597625732422
time_total_s: 163.8398461341858
timestamp: 1620312116
timesteps_since_restore: 0
training_iteration: 8
trial_id: d2654_00002
[2m[36m(pid=1445)[0m [4, 2000] loss: 1.259
[2m[36m(pid=1505)[0m [2, 18000] loss: 0.173
[2m[36m(pid=1496)[0m [9, 2000] loss: 1.394
[2m[36m(pid=1505)[0m [2, 20000] loss: 0.154
[2m[36m(pid=1445)[0m [4, 4000] loss: 0.638
Result for DEFAULT_d2654_00002:
accuracy: 0.5077
date: 2021-05-06_14-42-14
done: false
experiment_id: ad33da5cc5d649fe88b286a521ffc370
hostname: 9fb0856230de
iterations_since_restore: 9
loss: 1.521936821746826
node_ip: 172.17.0.2
pid: 1496
should_checkpoint: true
time_since_restore: 182.13826751708984
time_this_iter_s: 18.298421382904053
time_total_s: 182.13826751708984
timestamp: 1620312134
timesteps_since_restore: 0
training_iteration: 9
trial_id: d2654_00002
== Status ==
Memory usage on this node: 5.8/240.1 GiB
Using AsyncHyperBand: num_stopped=7
Bracket: Iter 8.000: -1.5100394088745117 | Iter 4.000: -1.4167865670204163 | Iter 2.000: -1.4437916863441467 | Iter 1.000: -1.8123709708034994
Resources requested: 6.0/32 CPUs, 0/2 GPUs, 0.0/220.15 GiB heap, 0.0/9.31 GiB objects (0.0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-05-06_14-39-11
Number of trials: 10/10 (3 RUNNING, 7 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name | status | loc | batch_size | l1 | l2 | lr | loss | accuracy | training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_d2654_00002 | RUNNING | 172.17.0.2:1496 | 16 | 16 | 256 | 0.0115781 | 1.52194 | 0.5077 | 9 |
| DEFAULT_d2654_00007 | RUNNING | 172.17.0.2:1505 | 2 | 4 | 8 | 0.000680871 | 1.69445 | 0.342 | 1 |
| DEFAULT_d2654_00009 | RUNNING | 172.17.0.2:1445 | 4 | 32 | 128 | 0.00180151 | 1.31084 | 0.5287 | 3 |
| DEFAULT_d2654_00000 | TERMINATED | | 4 | 64 | 16 | 0.0599786 | 2.33399 | 0.1016 | 1 |
| DEFAULT_d2654_00001 | TERMINATED | | 4 | 64 | 8 | 0.00349993 | 1.55284 | 0.4321 | 2 |
| DEFAULT_d2654_00003 | TERMINATED | | 2 | 16 | 256 | 0.000120934 | 1.89858 | 0.2891 | 1 |
| DEFAULT_d2654_00004 | TERMINATED | | 2 | 16 | 128 | 0.00549648 | 2.10118 | 0.2025 | 1 |
| DEFAULT_d2654_00005 | TERMINATED | | 8 | 128 | 64 | 0.0655931 | 2.30723 | 0.1057 | 1 |
| DEFAULT_d2654_00006 | TERMINATED | | 8 | 256 | 16 | 0.011964 | 1.72616 | 0.3653 | 1 |
| DEFAULT_d2654_00008 | TERMINATED | | 4 | 256 | 4 | 0.0336954 | 2.31501 | 0.1004 | 1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
[2m[36m(pid=1445)[0m [4, 6000] loss: 0.426
Result for DEFAULT_d2654_00007:
accuracy: 0.4048
date: 2021-05-06_14-42-22
done: true
experiment_id: 94907e92f16447f2a245bc213f3d9ce5
hostname: 9fb0856230de
iterations_since_restore: 2
loss: 1.5591586165577174
node_ip: 172.17.0.2
pid: 1505
should_checkpoint: true
time_since_restore: 189.69879603385925
time_this_iter_s: 85.23258018493652
time_total_s: 189.69879603385925
timestamp: 1620312142
timesteps_since_restore: 0
training_iteration: 2
trial_id: d2654_00007
== Status ==
Memory usage on this node: 5.9/240.1 GiB
Using AsyncHyperBand: num_stopped=8
Bracket: Iter 8.000: -1.5100394088745117 | Iter 4.000: -1.4167865670204163 | Iter 2.000: -1.4983180794239044 | Iter 1.000: -1.8123709708034994
Resources requested: 6.0/32 CPUs, 0/2 GPUs, 0.0/220.15 GiB heap, 0.0/9.31 GiB objects (0.0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-05-06_14-39-11
Number of trials: 10/10 (3 RUNNING, 7 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name | status | loc | batch_size | l1 | l2 | lr | loss | accuracy | training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_d2654_00002 | RUNNING | 172.17.0.2:1496 | 16 | 16 | 256 | 0.0115781 | 1.52194 | 0.5077 | 9 |
| DEFAULT_d2654_00007 | RUNNING | 172.17.0.2:1505 | 2 | 4 | 8 | 0.000680871 | 1.55916 | 0.4048 | 2 |
| DEFAULT_d2654_00009 | RUNNING | 172.17.0.2:1445 | 4 | 32 | 128 | 0.00180151 | 1.31084 | 0.5287 | 3 |
| DEFAULT_d2654_00000 | TERMINATED | | 4 | 64 | 16 | 0.0599786 | 2.33399 | 0.1016 | 1 |
| DEFAULT_d2654_00001 | TERMINATED | | 4 | 64 | 8 | 0.00349993 | 1.55284 | 0.4321 | 2 |
| DEFAULT_d2654_00003 | TERMINATED | | 2 | 16 | 256 | 0.000120934 | 1.89858 | 0.2891 | 1 |
| DEFAULT_d2654_00004 | TERMINATED | | 2 | 16 | 128 | 0.00549648 | 2.10118 | 0.2025 | 1 |
| DEFAULT_d2654_00005 | TERMINATED | | 8 | 128 | 64 | 0.0655931 | 2.30723 | 0.1057 | 1 |
| DEFAULT_d2654_00006 | TERMINATED | | 8 | 256 | 16 | 0.011964 | 1.72616 | 0.3653 | 1 |
| DEFAULT_d2654_00008 | TERMINATED | | 4 | 256 | 4 | 0.0336954 | 2.31501 | 0.1004 | 1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
[2m[36m(pid=1496)[0m [10, 2000] loss: 1.384
[2m[36m(pid=1445)[0m [4, 8000] loss: 0.325
Result for DEFAULT_d2654_00002:
accuracy: 0.5138
date: 2021-05-06_14-42-33
done: true
experiment_id: ad33da5cc5d649fe88b286a521ffc370
hostname: 9fb0856230de
iterations_since_restore: 10
loss: 1.4006739482879638
node_ip: 172.17.0.2
pid: 1496
should_checkpoint: true
time_since_restore: 200.46421599388123
time_this_iter_s: 18.325948476791382
time_total_s: 200.46421599388123
timestamp: 1620312153
timesteps_since_restore: 0
training_iteration: 10
trial_id: d2654_00002
== Status ==
Memory usage on this node: 5.3/240.1 GiB
Using AsyncHyperBand: num_stopped=9
Bracket: Iter 8.000: -1.5100394088745117 | Iter 4.000: -1.4167865670204163 | Iter 2.000: -1.4983180794239044 | Iter 1.000: -1.8123709708034994
Resources requested: 4.0/32 CPUs, 0/2 GPUs, 0.0/220.15 GiB heap, 0.0/9.31 GiB objects (0.0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-05-06_14-39-11
Number of trials: 10/10 (2 RUNNING, 8 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name | status | loc | batch_size | l1 | l2 | lr | loss | accuracy | training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_d2654_00002 | RUNNING | 172.17.0.2:1496 | 16 | 16 | 256 | 0.0115781 | 1.40067 | 0.5138 | 10 |
| DEFAULT_d2654_00009 | RUNNING | 172.17.0.2:1445 | 4 | 32 | 128 | 0.00180151 | 1.31084 | 0.5287 | 3 |
| DEFAULT_d2654_00000 | TERMINATED | | 4 | 64 | 16 | 0.0599786 | 2.33399 | 0.1016 | 1 |
| DEFAULT_d2654_00001 | TERMINATED | | 4 | 64 | 8 | 0.00349993 | 1.55284 | 0.4321 | 2 |
| DEFAULT_d2654_00003 | TERMINATED | | 2 | 16 | 256 | 0.000120934 | 1.89858 | 0.2891 | 1 |
| DEFAULT_d2654_00004 | TERMINATED | | 2 | 16 | 128 | 0.00549648 | 2.10118 | 0.2025 | 1 |
| DEFAULT_d2654_00005 | TERMINATED | | 8 | 128 | 64 | 0.0655931 | 2.30723 | 0.1057 | 1 |
| DEFAULT_d2654_00006 | TERMINATED | | 8 | 256 | 16 | 0.011964 | 1.72616 | 0.3653 | 1 |
| DEFAULT_d2654_00007 | TERMINATED | | 2 | 4 | 8 | 0.000680871 | 1.55916 | 0.4048 | 2 |
| DEFAULT_d2654_00008 | TERMINATED | | 4 | 256 | 4 | 0.0336954 | 2.31501 | 0.1004 | 1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
[2m[36m(pid=1445)[0m [4, 10000] loss: 0.257
Result for DEFAULT_d2654_00009:
accuracy: 0.5318
date: 2021-05-06_14-42-42
done: false
experiment_id: 5f342aed5b9c4085b4b4591e9b3d7862
hostname: 9fb0856230de
iterations_since_restore: 4
loss: 1.3321557600796223
node_ip: 172.17.0.2
pid: 1445
should_checkpoint: true
time_since_restore: 209.25899362564087
time_this_iter_s: 47.329846143722534
time_total_s: 209.25899362564087
timestamp: 1620312162
timesteps_since_restore: 0
training_iteration: 4
trial_id: d2654_00009
== Status ==
Memory usage on this node: 4.5/240.1 GiB
Using AsyncHyperBand: num_stopped=9
Bracket: Iter 8.000: -1.5100394088745117 | Iter 4.000: -1.3744711635500193 | Iter 2.000: -1.4983180794239044 | Iter 1.000: -1.8123709708034994
Resources requested: 2.0/32 CPUs, 0/2 GPUs, 0.0/220.15 GiB heap, 0.0/9.31 GiB objects (0.0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-05-06_14-39-11
Number of trials: 10/10 (1 RUNNING, 9 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name | status | loc | batch_size | l1 | l2 | lr | loss | accuracy | training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_d2654_00009 | RUNNING | 172.17.0.2:1445 | 4 | 32 | 128 | 0.00180151 | 1.33216 | 0.5318 | 4 |
| DEFAULT_d2654_00000 | TERMINATED | | 4 | 64 | 16 | 0.0599786 | 2.33399 | 0.1016 | 1 |
| DEFAULT_d2654_00001 | TERMINATED | | 4 | 64 | 8 | 0.00349993 | 1.55284 | 0.4321 | 2 |
| DEFAULT_d2654_00002 | TERMINATED | | 16 | 16 | 256 | 0.0115781 | 1.40067 | 0.5138 | 10 |
| DEFAULT_d2654_00003 | TERMINATED | | 2 | 16 | 256 | 0.000120934 | 1.89858 | 0.2891 | 1 |
| DEFAULT_d2654_00004 | TERMINATED | | 2 | 16 | 128 | 0.00549648 | 2.10118 | 0.2025 | 1 |
| DEFAULT_d2654_00005 | TERMINATED | | 8 | 128 | 64 | 0.0655931 | 2.30723 | 0.1057 | 1 |
| DEFAULT_d2654_00006 | TERMINATED | | 8 | 256 | 16 | 0.011964 | 1.72616 | 0.3653 | 1 |
| DEFAULT_d2654_00007 | TERMINATED | | 2 | 4 | 8 | 0.000680871 | 1.55916 | 0.4048 | 2 |
| DEFAULT_d2654_00008 | TERMINATED | | 4 | 256 | 4 | 0.0336954 | 2.31501 | 0.1004 | 1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
[2m[36m(pid=1445)[0m [5, 2000] loss: 1.219
[2m[36m(pid=1445)[0m [5, 4000] loss: 0.611
[2m[36m(pid=1445)[0m [5, 6000] loss: 0.411
[2m[36m(pid=1445)[0m [5, 8000] loss: 0.315
[2m[36m(pid=1445)[0m [5, 10000] loss: 0.254
Result for DEFAULT_d2654_00009:
accuracy: 0.5312
date: 2021-05-06_14-43-26
done: false
experiment_id: 5f342aed5b9c4085b4b4591e9b3d7862
hostname: 9fb0856230de
iterations_since_restore: 5
loss: 1.3375659304916858
node_ip: 172.17.0.2
pid: 1445
should_checkpoint: true
time_since_restore: 254.0118067264557
time_this_iter_s: 44.75281310081482
time_total_s: 254.0118067264557
timestamp: 1620312206
timesteps_since_restore: 0
training_iteration: 5
trial_id: d2654_00009
== Status ==
Memory usage on this node: 4.5/240.1 GiB
Using AsyncHyperBand: num_stopped=9
Bracket: Iter 8.000: -1.5100394088745117 | Iter 4.000: -1.3744711635500193 | Iter 2.000: -1.4983180794239044 | Iter 1.000: -1.8123709708034994
Resources requested: 2.0/32 CPUs, 0/2 GPUs, 0.0/220.15 GiB heap, 0.0/9.31 GiB objects (0.0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-05-06_14-39-11
Number of trials: 10/10 (1 RUNNING, 9 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name | status | loc | batch_size | l1 | l2 | lr | loss | accuracy | training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_d2654_00009 | RUNNING | 172.17.0.2:1445 | 4 | 32 | 128 | 0.00180151 | 1.33757 | 0.5312 | 5 |
| DEFAULT_d2654_00000 | TERMINATED | | 4 | 64 | 16 | 0.0599786 | 2.33399 | 0.1016 | 1 |
| DEFAULT_d2654_00001 | TERMINATED | | 4 | 64 | 8 | 0.00349993 | 1.55284 | 0.4321 | 2 |
| DEFAULT_d2654_00002 | TERMINATED | | 16 | 16 | 256 | 0.0115781 | 1.40067 | 0.5138 | 10 |
| DEFAULT_d2654_00003 | TERMINATED | | 2 | 16 | 256 | 0.000120934 | 1.89858 | 0.2891 | 1 |
| DEFAULT_d2654_00004 | TERMINATED | | 2 | 16 | 128 | 0.00549648 | 2.10118 | 0.2025 | 1 |
| DEFAULT_d2654_00005 | TERMINATED | | 8 | 128 | 64 | 0.0655931 | 2.30723 | 0.1057 | 1 |
| DEFAULT_d2654_00006 | TERMINATED | | 8 | 256 | 16 | 0.011964 | 1.72616 | 0.3653 | 1 |
| DEFAULT_d2654_00007 | TERMINATED | | 2 | 4 | 8 | 0.000680871 | 1.55916 | 0.4048 | 2 |
| DEFAULT_d2654_00008 | TERMINATED | | 4 | 256 | 4 | 0.0336954 | 2.31501 | 0.1004 | 1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
[2m[36m(pid=1445)[0m [6, 2000] loss: 1.182
[2m[36m(pid=1445)[0m [6, 4000] loss: 0.603
[2m[36m(pid=1445)[0m [6, 6000] loss: 0.405
[2m[36m(pid=1445)[0m [6, 8000] loss: 0.309
[2m[36m(pid=1445)[0m [6, 10000] loss: 0.250
Result for DEFAULT_d2654_00009:
accuracy: 0.564
date: 2021-05-06_14-44-12
done: false
experiment_id: 5f342aed5b9c4085b4b4591e9b3d7862
hostname: 9fb0856230de
iterations_since_restore: 6
loss: 1.2627495556876063
node_ip: 172.17.0.2
pid: 1445
should_checkpoint: true
time_since_restore: 299.3393397331238
time_this_iter_s: 45.32753300666809
time_total_s: 299.3393397331238
timestamp: 1620312252
timesteps_since_restore: 0
training_iteration: 6
trial_id: d2654_00009
== Status ==
Memory usage on this node: 4.6/240.1 GiB
Using AsyncHyperBand: num_stopped=9
Bracket: Iter 8.000: -1.5100394088745117 | Iter 4.000: -1.3744711635500193 | Iter 2.000: -1.4983180794239044 | Iter 1.000: -1.8123709708034994
Resources requested: 2.0/32 CPUs, 0/2 GPUs, 0.0/220.15 GiB heap, 0.0/9.31 GiB objects (0.0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-05-06_14-39-11
Number of trials: 10/10 (1 RUNNING, 9 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name | status | loc | batch_size | l1 | l2 | lr | loss | accuracy | training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_d2654_00009 | RUNNING | 172.17.0.2:1445 | 4 | 32 | 128 | 0.00180151 | 1.26275 | 0.564 | 6 |
| DEFAULT_d2654_00000 | TERMINATED | | 4 | 64 | 16 | 0.0599786 | 2.33399 | 0.1016 | 1 |
| DEFAULT_d2654_00001 | TERMINATED | | 4 | 64 | 8 | 0.00349993 | 1.55284 | 0.4321 | 2 |
| DEFAULT_d2654_00002 | TERMINATED | | 16 | 16 | 256 | 0.0115781 | 1.40067 | 0.5138 | 10 |
| DEFAULT_d2654_00003 | TERMINATED | | 2 | 16 | 256 | 0.000120934 | 1.89858 | 0.2891 | 1 |
| DEFAULT_d2654_00004 | TERMINATED | | 2 | 16 | 128 | 0.00549648 | 2.10118 | 0.2025 | 1 |
| DEFAULT_d2654_00005 | TERMINATED | | 8 | 128 | 64 | 0.0655931 | 2.30723 | 0.1057 | 1 |
| DEFAULT_d2654_00006 | TERMINATED | | 8 | 256 | 16 | 0.011964 | 1.72616 | 0.3653 | 1 |
| DEFAULT_d2654_00007 | TERMINATED | | 2 | 4 | 8 | 0.000680871 | 1.55916 | 0.4048 | 2 |
| DEFAULT_d2654_00008 | TERMINATED | | 4 | 256 | 4 | 0.0336954 | 2.31501 | 0.1004 | 1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
[2m[36m(pid=1445)[0m [7, 2000] loss: 1.164
[2m[36m(pid=1445)[0m [7, 4000] loss: 0.590
[2m[36m(pid=1445)[0m [7, 6000] loss: 0.404
[2m[36m(pid=1445)[0m [7, 8000] loss: 0.296
[2m[36m(pid=1445)[0m [7, 10000] loss: 0.245
Result for DEFAULT_d2654_00009:
accuracy: 0.5329
date: 2021-05-06_14-44-57
done: false
experiment_id: 5f342aed5b9c4085b4b4591e9b3d7862
hostname: 9fb0856230de
iterations_since_restore: 7
loss: 1.4005948592122643
node_ip: 172.17.0.2
pid: 1445
should_checkpoint: true
time_since_restore: 345.01376152038574
time_this_iter_s: 45.67442178726196
time_total_s: 345.01376152038574
timestamp: 1620312297
timesteps_since_restore: 0
training_iteration: 7
trial_id: d2654_00009
== Status ==
Memory usage on this node: 4.6/240.1 GiB
Using AsyncHyperBand: num_stopped=9
Bracket: Iter 8.000: -1.5100394088745117 | Iter 4.000: -1.3744711635500193 | Iter 2.000: -1.4983180794239044 | Iter 1.000: -1.8123709708034994
Resources requested: 2.0/32 CPUs, 0/2 GPUs, 0.0/220.15 GiB heap, 0.0/9.31 GiB objects (0.0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-05-06_14-39-11
Number of trials: 10/10 (1 RUNNING, 9 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name | status | loc | batch_size | l1 | l2 | lr | loss | accuracy | training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_d2654_00009 | RUNNING | 172.17.0.2:1445 | 4 | 32 | 128 | 0.00180151 | 1.40059 | 0.5329 | 7 |
| DEFAULT_d2654_00000 | TERMINATED | | 4 | 64 | 16 | 0.0599786 | 2.33399 | 0.1016 | 1 |
| DEFAULT_d2654_00001 | TERMINATED | | 4 | 64 | 8 | 0.00349993 | 1.55284 | 0.4321 | 2 |
| DEFAULT_d2654_00002 | TERMINATED | | 16 | 16 | 256 | 0.0115781 | 1.40067 | 0.5138 | 10 |
| DEFAULT_d2654_00003 | TERMINATED | | 2 | 16 | 256 | 0.000120934 | 1.89858 | 0.2891 | 1 |
| DEFAULT_d2654_00004 | TERMINATED | | 2 | 16 | 128 | 0.00549648 | 2.10118 | 0.2025 | 1 |
| DEFAULT_d2654_00005 | TERMINATED | | 8 | 128 | 64 | 0.0655931 | 2.30723 | 0.1057 | 1 |
| DEFAULT_d2654_00006 | TERMINATED | | 8 | 256 | 16 | 0.011964 | 1.72616 | 0.3653 | 1 |
| DEFAULT_d2654_00007 | TERMINATED | | 2 | 4 | 8 | 0.000680871 | 1.55916 | 0.4048 | 2 |
| DEFAULT_d2654_00008 | TERMINATED | | 4 | 256 | 4 | 0.0336954 | 2.31501 | 0.1004 | 1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
[2m[36m(pid=1445)[0m [8, 2000] loss: 1.146
[2m[36m(pid=1445)[0m [8, 4000] loss: 0.591
[2m[36m(pid=1445)[0m [8, 6000] loss: 0.391
[2m[36m(pid=1445)[0m [8, 8000] loss: 0.297
[2m[36m(pid=1445)[0m [8, 10000] loss: 0.243
Result for DEFAULT_d2654_00009:
accuracy: 0.5557
date: 2021-05-06_14-45-43
done: false
experiment_id: 5f342aed5b9c4085b4b4591e9b3d7862
hostname: 9fb0856230de
iterations_since_restore: 8
loss: 1.2884210534013807
node_ip: 172.17.0.2
pid: 1445
should_checkpoint: true
time_since_restore: 390.74146819114685
time_this_iter_s: 45.72770667076111
time_total_s: 390.74146819114685
timestamp: 1620312343
timesteps_since_restore: 0
training_iteration: 8
trial_id: d2654_00009
== Status ==
Memory usage on this node: 4.6/240.1 GiB
Using AsyncHyperBand: num_stopped=9
Bracket: Iter 8.000: -1.3992302311379463 | Iter 4.000: -1.3744711635500193 | Iter 2.000: -1.4983180794239044 | Iter 1.000: -1.8123709708034994
Resources requested: 2.0/32 CPUs, 0/2 GPUs, 0.0/220.15 GiB heap, 0.0/9.31 GiB objects (0.0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-05-06_14-39-11
Number of trials: 10/10 (1 RUNNING, 9 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name | status | loc | batch_size | l1 | l2 | lr | loss | accuracy | training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_d2654_00009 | RUNNING | 172.17.0.2:1445 | 4 | 32 | 128 | 0.00180151 | 1.28842 | 0.5557 | 8 |
| DEFAULT_d2654_00000 | TERMINATED | | 4 | 64 | 16 | 0.0599786 | 2.33399 | 0.1016 | 1 |
| DEFAULT_d2654_00001 | TERMINATED | | 4 | 64 | 8 | 0.00349993 | 1.55284 | 0.4321 | 2 |
| DEFAULT_d2654_00002 | TERMINATED | | 16 | 16 | 256 | 0.0115781 | 1.40067 | 0.5138 | 10 |
| DEFAULT_d2654_00003 | TERMINATED | | 2 | 16 | 256 | 0.000120934 | 1.89858 | 0.2891 | 1 |
| DEFAULT_d2654_00004 | TERMINATED | | 2 | 16 | 128 | 0.00549648 | 2.10118 | 0.2025 | 1 |
| DEFAULT_d2654_00005 | TERMINATED | | 8 | 128 | 64 | 0.0655931 | 2.30723 | 0.1057 | 1 |
| DEFAULT_d2654_00006 | TERMINATED | | 8 | 256 | 16 | 0.011964 | 1.72616 | 0.3653 | 1 |
| DEFAULT_d2654_00007 | TERMINATED | | 2 | 4 | 8 | 0.000680871 | 1.55916 | 0.4048 | 2 |
| DEFAULT_d2654_00008 | TERMINATED | | 4 | 256 | 4 | 0.0336954 | 2.31501 | 0.1004 | 1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
[2m[36m(pid=1445)[0m [9, 2000] loss: 1.126
[2m[36m(pid=1445)[0m [9, 4000] loss: 0.584
[2m[36m(pid=1445)[0m [9, 6000] loss: 0.390
[2m[36m(pid=1445)[0m [9, 8000] loss: 0.291
[2m[36m(pid=1445)[0m [9, 10000] loss: 0.233
Result for DEFAULT_d2654_00009:
accuracy: 0.5339
date: 2021-05-06_14-46-28
done: false
experiment_id: 5f342aed5b9c4085b4b4591e9b3d7862
hostname: 9fb0856230de
iterations_since_restore: 9
loss: 1.3169714092940092
node_ip: 172.17.0.2
pid: 1445
should_checkpoint: true
time_since_restore: 435.55882120132446
time_this_iter_s: 44.81735301017761
time_total_s: 435.55882120132446
timestamp: 1620312388
timesteps_since_restore: 0
training_iteration: 9
trial_id: d2654_00009
== Status ==
Memory usage on this node: 4.6/240.1 GiB
Using AsyncHyperBand: num_stopped=9
Bracket: Iter 8.000: -1.3992302311379463 | Iter 4.000: -1.3744711635500193 | Iter 2.000: -1.4983180794239044 | Iter 1.000: -1.8123709708034994
Resources requested: 2.0/32 CPUs, 0/2 GPUs, 0.0/220.15 GiB heap, 0.0/9.31 GiB objects (0.0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-05-06_14-39-11
Number of trials: 10/10 (1 RUNNING, 9 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name | status | loc | batch_size | l1 | l2 | lr | loss | accuracy | training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_d2654_00009 | RUNNING | 172.17.0.2:1445 | 4 | 32 | 128 | 0.00180151 | 1.31697 | 0.5339 | 9 |
| DEFAULT_d2654_00000 | TERMINATED | | 4 | 64 | 16 | 0.0599786 | 2.33399 | 0.1016 | 1 |
| DEFAULT_d2654_00001 | TERMINATED | | 4 | 64 | 8 | 0.00349993 | 1.55284 | 0.4321 | 2 |
| DEFAULT_d2654_00002 | TERMINATED | | 16 | 16 | 256 | 0.0115781 | 1.40067 | 0.5138 | 10 |
| DEFAULT_d2654_00003 | TERMINATED | | 2 | 16 | 256 | 0.000120934 | 1.89858 | 0.2891 | 1 |
| DEFAULT_d2654_00004 | TERMINATED | | 2 | 16 | 128 | 0.00549648 | 2.10118 | 0.2025 | 1 |
| DEFAULT_d2654_00005 | TERMINATED | | 8 | 128 | 64 | 0.0655931 | 2.30723 | 0.1057 | 1 |
| DEFAULT_d2654_00006 | TERMINATED | | 8 | 256 | 16 | 0.011964 | 1.72616 | 0.3653 | 1 |
| DEFAULT_d2654_00007 | TERMINATED | | 2 | 4 | 8 | 0.000680871 | 1.55916 | 0.4048 | 2 |
| DEFAULT_d2654_00008 | TERMINATED | | 4 | 256 | 4 | 0.0336954 | 2.31501 | 0.1004 | 1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
[2m[36m(pid=1445)[0m [10, 2000] loss: 1.133
[2m[36m(pid=1445)[0m [10, 4000] loss: 0.558
[2m[36m(pid=1445)[0m [10, 6000] loss: 0.385
[2m[36m(pid=1445)[0m [10, 8000] loss: 0.288
[2m[36m(pid=1445)[0m [10, 10000] loss: 0.233
Result for DEFAULT_d2654_00009:
accuracy: 0.5681
date: 2021-05-06_14-47-13
done: true
experiment_id: 5f342aed5b9c4085b4b4591e9b3d7862
hostname: 9fb0856230de
iterations_since_restore: 10
loss: 1.2805275422930718
node_ip: 172.17.0.2
pid: 1445
should_checkpoint: true
time_since_restore: 480.4494676589966
time_this_iter_s: 44.89064645767212
time_total_s: 480.4494676589966
timestamp: 1620312433
timesteps_since_restore: 0
training_iteration: 10
trial_id: d2654_00009
== Status ==
Memory usage on this node: 4.6/240.1 GiB
Using AsyncHyperBand: num_stopped=10
Bracket: Iter 8.000: -1.3992302311379463 | Iter 4.000: -1.3744711635500193 | Iter 2.000: -1.4983180794239044 | Iter 1.000: -1.8123709708034994
Resources requested: 2.0/32 CPUs, 0/2 GPUs, 0.0/220.15 GiB heap, 0.0/9.31 GiB objects (0.0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-05-06_14-39-11
Number of trials: 10/10 (1 RUNNING, 9 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name | status | loc | batch_size | l1 | l2 | lr | loss | accuracy | training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_d2654_00009 | RUNNING | 172.17.0.2:1445 | 4 | 32 | 128 | 0.00180151 | 1.28053 | 0.5681 | 10 |
| DEFAULT_d2654_00000 | TERMINATED | | 4 | 64 | 16 | 0.0599786 | 2.33399 | 0.1016 | 1 |
| DEFAULT_d2654_00001 | TERMINATED | | 4 | 64 | 8 | 0.00349993 | 1.55284 | 0.4321 | 2 |
| DEFAULT_d2654_00002 | TERMINATED | | 16 | 16 | 256 | 0.0115781 | 1.40067 | 0.5138 | 10 |
| DEFAULT_d2654_00003 | TERMINATED | | 2 | 16 | 256 | 0.000120934 | 1.89858 | 0.2891 | 1 |
| DEFAULT_d2654_00004 | TERMINATED | | 2 | 16 | 128 | 0.00549648 | 2.10118 | 0.2025 | 1 |
| DEFAULT_d2654_00005 | TERMINATED | | 8 | 128 | 64 | 0.0655931 | 2.30723 | 0.1057 | 1 |
| DEFAULT_d2654_00006 | TERMINATED | | 8 | 256 | 16 | 0.011964 | 1.72616 | 0.3653 | 1 |
| DEFAULT_d2654_00007 | TERMINATED | | 2 | 4 | 8 | 0.000680871 | 1.55916 | 0.4048 | 2 |
| DEFAULT_d2654_00008 | TERMINATED | | 4 | 256 | 4 | 0.0336954 | 2.31501 | 0.1004 | 1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
== Status ==
Memory usage on this node: 4.5/240.1 GiB
Using AsyncHyperBand: num_stopped=10
Bracket: Iter 8.000: -1.3992302311379463 | Iter 4.000: -1.3744711635500193 | Iter 2.000: -1.4983180794239044 | Iter 1.000: -1.8123709708034994
Resources requested: 0/32 CPUs, 0/2 GPUs, 0.0/220.15 GiB heap, 0.0/9.31 GiB objects (0.0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-05-06_14-39-11
Number of trials: 10/10 (10 TERMINATED)
+---------------------+------------+-------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name | status | loc | batch_size | l1 | l2 | lr | loss | accuracy | training_iteration |
|---------------------+------------+-------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_d2654_00000 | TERMINATED | | 4 | 64 | 16 | 0.0599786 | 2.33399 | 0.1016 | 1 |
| DEFAULT_d2654_00001 | TERMINATED | | 4 | 64 | 8 | 0.00349993 | 1.55284 | 0.4321 | 2 |
| DEFAULT_d2654_00002 | TERMINATED | | 16 | 16 | 256 | 0.0115781 | 1.40067 | 0.5138 | 10 |
| DEFAULT_d2654_00003 | TERMINATED | | 2 | 16 | 256 | 0.000120934 | 1.89858 | 0.2891 | 1 |
| DEFAULT_d2654_00004 | TERMINATED | | 2 | 16 | 128 | 0.00549648 | 2.10118 | 0.2025 | 1 |
| DEFAULT_d2654_00005 | TERMINATED | | 8 | 128 | 64 | 0.0655931 | 2.30723 | 0.1057 | 1 |
| DEFAULT_d2654_00006 | TERMINATED | | 8 | 256 | 16 | 0.011964 | 1.72616 | 0.3653 | 1 |
| DEFAULT_d2654_00007 | TERMINATED | | 2 | 4 | 8 | 0.000680871 | 1.55916 | 0.4048 | 2 |
| DEFAULT_d2654_00008 | TERMINATED | | 4 | 256 | 4 | 0.0336954 | 2.31501 | 0.1004 | 1 |
| DEFAULT_d2654_00009 | TERMINATED | | 4 | 32 | 128 | 0.00180151 | 1.28053 | 0.5681 | 10 |
+---------------------+------------+-------+--------------+------+------+-------------+---------+------------+----------------------+
Best trial config: {'l1': 32, 'l2': 128, 'lr': 0.0018015051193173892, 'batch_size': 4}
Best trial final validation loss: 1.2805275422930718
Best trial final validation accuracy: 0.5681
Files already downloaded and verified
Files already downloaded and verified
Best trial test set accuracy: 0.5629
If you run the code, an example output could look like this:
Number of trials: 10 (10 TERMINATED)
+-----+------+------+-------------+--------------+---------+------------+--------------------+
| ... | l1 | l2 | lr | batch_size | loss | accuracy | training_iteration |
|-----+------+------+-------------+--------------+---------+------------+--------------------|
| ... | 64 | 4 | 0.00011629 | 2 | 1.87273 | 0.244 | 2 |
| ... | 32 | 64 | 0.000339763 | 8 | 1.23603 | 0.567 | 8 |
| ... | 8 | 16 | 0.00276249 | 16 | 1.1815 | 0.5836 | 10 |
| ... | 4 | 64 | 0.000648721 | 4 | 1.31131 | 0.5224 | 8 |
| ... | 32 | 16 | 0.000340753 | 8 | 1.26454 | 0.5444 | 8 |
| ... | 8 | 4 | 0.000699775 | 8 | 1.99594 | 0.1983 | 2 |
| ... | 256 | 8 | 0.0839654 | 16 | 2.3119 | 0.0993 | 1 |
| ... | 16 | 128 | 0.0758154 | 16 | 2.33575 | 0.1327 | 1 |
| ... | 16 | 8 | 0.0763312 | 16 | 2.31129 | 0.1042 | 4 |
| ... | 128 | 16 | 0.000124903 | 4 | 2.26917 | 0.1945 | 1 |
+-----+------+------+-------------+--------------+---------+------------+--------------------+
Best trial config: {'l1': 8, 'l2': 16, 'lr': 0.00276249, 'batch_size': 16, 'data_dir': '...'}
Best trial final validation loss: 1.181501
Best trial final validation accuracy: 0.5836
Best trial test set accuracy: 0.5806
Most trials have been stopped early in order to avoid wasting resources. The best performing trial achieved a validation accuracy of about 58%, which could be confirmed on the test set.
So that’s it! You can now tune the parameters of your PyTorch models.
Total running time of the script: ( 8 minutes 26.974 seconds)
