ANN training progress resets every new training session using FANN
I have a standard neural network which I have trained for some time, but not until perfection. After the training session is complete, I save the network on disk.
After some time I want to resume training the network from where it left. The problem is, it seems that every time I start a new training session, the weights and biases seem to be totally reset, which means I'm training the network from scratch all over again:
Previous session:
New session:
Here is the excerpt from my training function:
void trainNet(fann *net) {
const unsigned int
max_epochs = 1000,
epochs_between_reports = 10;
const float desired_error = 0.01f;
net -> learning_momentum = 0.1f;
fann_train_on_file(net, "sessions.data", max_epochs, epochs_between_reports, desired_error);
fann_save(net, "network.net");
fann_destroy(net);
}
What am I missing? It seems so intuitive to me that you could train a network over a span of multiple sessions. Am I wrong? Is it a limitation of the library?
The training data has remained constant between sessions. This isn't limited to this specific network, either -- networks of any format seem to invoke the same issue.
c++ fann
asked Nov 23 '18 at 12:50
daedsidogdaedsidog
1,3292828
add a comment |
I have a standard neural network which I have trained for some time, but not until perfection. After the training session is complete, I save the network on disk.
After some time I want to resume training the network from where it left. The problem is, it seems that every time I start a new training session, the weights and biases seem to be totally reset, which means I'm training the network from scratch all over again:
Previous session:
New session:
Here is the excerpt from my training function:
void trainNet(fann *net) {
const unsigned int
max_epochs = 1000,
epochs_between_reports = 10;
const float desired_error = 0.01f;
net -> learning_momentum = 0.1f;
fann_train_on_file(net, "sessions.data", max_epochs, epochs_between_reports, desired_error);
fann_save(net, "network.net");
fann_destroy(net);
}
What am I missing? It seems so intuitive to me that you could train a network over a span of multiple sessions. Am I wrong? Is it a limitation of the library?
The training data has remained constant between sessions. This isn't limited to this specific network, either -- networks of any format seem to invoke the same issue.
c++ fann
asked Nov 23 '18 at 12:50
daedsidogdaedsidog
1,3292828
add a comment |
I have a standard neural network which I have trained for some time, but not until perfection. After the training session is complete, I save the network on disk.
After some time I want to resume training the network from where it left. The problem is, it seems that every time I start a new training session, the weights and biases seem to be totally reset, which means I'm training the network from scratch all over again:
Previous session:
New session:
Here is the excerpt from my training function:
void trainNet(fann *net) {
const unsigned int
max_epochs = 1000,
epochs_between_reports = 10;
const float desired_error = 0.01f;
net -> learning_momentum = 0.1f;
fann_train_on_file(net, "sessions.data", max_epochs, epochs_between_reports, desired_error);
fann_save(net, "network.net");
fann_destroy(net);
}
What am I missing? It seems so intuitive to me that you could train a network over a span of multiple sessions. Am I wrong? Is it a limitation of the library?
The training data has remained constant between sessions. This isn't limited to this specific network, either -- networks of any format seem to invoke the same issue.
c++ fann
asked Nov 23 '18 at 12:50
daedsidogdaedsidog
1,3292828
I have a standard neural network which I have trained for some time, but not until perfection. After the training session is complete, I save the network on disk.
After some time I want to resume training the network from where it left. The problem is, it seems that every time I start a new training session, the weights and biases seem to be totally reset, which means I'm training the network from scratch all over again:
Previous session:
New session:
Here is the excerpt from my training function:
void trainNet(fann *net) {
const unsigned int
max_epochs = 1000,
epochs_between_reports = 10;
const float desired_error = 0.01f;
net -> learning_momentum = 0.1f;
fann_train_on_file(net, "sessions.data", max_epochs, epochs_between_reports, desired_error);
fann_save(net, "network.net");
fann_destroy(net);
}
What am I missing? It seems so intuitive to me that you could train a network over a span of multiple sessions. Am I wrong? Is it a limitation of the library?
The training data has remained constant between sessions. This isn't limited to this specific network, either -- networks of any format seem to invoke the same issue.
c++ fann
c++ fann
asked Nov 23 '18 at 12:50
daedsidogdaedsidog
1,3292828
asked Nov 23 '18 at 12:50
daedsidogdaedsidog
1,3292828
asked Nov 23 '18 at 12:50
daedsidogdaedsidog
1,3292828
asked Nov 23 '18 at 12:50
daedsidogdaedsidog
1,3292828
asked Nov 23 '18 at 12:50
daedsidogdaedsidog
1,3292828
1,3292828
add a comment |
add a comment |
1 Answer
1
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oldest
votes
What am I missing?
As per Documentation - FANN Training > Training Data Manipulation > fann_set_training_algorithm :
Set the training algorithm.
Example :
fann_set_training_algorithm(net, FANN_TRAIN_INCREMENTAL)
answered Nov 23 '18 at 17:38
user4157124user4157124
2,21951332
Very helpful, thank you.
– daedsidog
Nov 23 '18 at 18:25
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
What am I missing?
As per Documentation - FANN Training > Training Data Manipulation > fann_set_training_algorithm :
Set the training algorithm.
Example :
fann_set_training_algorithm(net, FANN_TRAIN_INCREMENTAL)
answered Nov 23 '18 at 17:38
user4157124user4157124
2,21951332
Very helpful, thank you.
– daedsidog
Nov 23 '18 at 18:25
add a comment |
What am I missing?
As per Documentation - FANN Training > Training Data Manipulation > fann_set_training_algorithm :
Set the training algorithm.
Example :
fann_set_training_algorithm(net, FANN_TRAIN_INCREMENTAL)
answered Nov 23 '18 at 17:38
user4157124user4157124
2,21951332
Very helpful, thank you.
– daedsidog
Nov 23 '18 at 18:25
add a comment |
What am I missing?
As per Documentation - FANN Training > Training Data Manipulation > fann_set_training_algorithm :
Set the training algorithm.
Example :
fann_set_training_algorithm(net, FANN_TRAIN_INCREMENTAL)
answered Nov 23 '18 at 17:38
user4157124user4157124
2,21951332
What am I missing?
As per Documentation - FANN Training > Training Data Manipulation > fann_set_training_algorithm :
Set the training algorithm.
Example :
fann_set_training_algorithm(net, FANN_TRAIN_INCREMENTAL)
answered Nov 23 '18 at 17:38
user4157124user4157124
2,21951332
answered Nov 23 '18 at 17:38
user4157124user4157124
2,21951332
answered Nov 23 '18 at 17:38
user4157124user4157124
2,21951332
answered Nov 23 '18 at 17:38
user4157124user4157124
2,21951332
2,21951332
Very helpful, thank you.
– daedsidog
Nov 23 '18 at 18:25
add a comment |
Very helpful, thank you.
– daedsidog
Nov 23 '18 at 18:25
Very helpful, thank you.
– daedsidog
Nov 23 '18 at 18:25
Very helpful, thank you.
– daedsidog
Nov 23 '18 at 18:25
add a comment |
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