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Add option "auto_lr_drop" that specifies the amount of positions from previous lr drop after which to reduce lr by newbob_decay.

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This commit is contained in:
Tomasz Sobczyk
2020-10-12 11:46:50 +02:00
committed by nodchip
parent 7d62b3f799
commit 4a2bf16b30
1 changed files with 22 additions and 1 deletions
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23
src/learn/learn.cpp
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@@ -744,6 +744,8 @@ namespace Learner
newbob_decay = 1.0;
newbob_num_trials = 2;
auto_lr_drop = 0;
last_lr_drop = 0;
best_loss = std::numeric_limits<double>::infinity();
latest_loss_sum = 0.0;
latest_loss_count = 0;
@@ -797,6 +799,8 @@ namespace Learner
shared_timed_mutex nn_mutex;
double newbob_decay;
int newbob_num_trials;
uint64_t auto_lr_drop;
uint64_t last_lr_drop;
double best_loss;
double latest_loss_sum;
uint64_t latest_loss_count;
@@ -1295,7 +1299,21 @@ namespace Learner
latest_loss_sum = 0.0;
latest_loss_count = 0;
cout << "loss: " << latest_loss;
if (latest_loss < best_loss)
auto tot = sr.total_done.load();
if (auto_lr_drop)
{
cout << " < best (" << best_loss << "), accepted" << endl;
best_loss = latest_loss;
best_nn_directory = Path::Combine((std::string)Options["EvalSaveDir"], dir_name);
trials = newbob_num_trials;
if (tot >= last_lr_drop + auto_lr_drop)
{
last_lr_drop = tot;
global_learning_rate *= newbob_decay;
}
}
else if (latest_loss < best_loss)
{
cout << " < best (" << best_loss << "), accepted" << endl;
best_loss = latest_loss;
@@ -1647,6 +1665,7 @@ namespace Learner
uint64_t nn_batch_size = 1000;
double newbob_decay = 0.5;
int newbob_num_trials = 4;
uint64_t auto_lr_drop = 0;
string nn_options;
uint64_t eval_save_interval = LEARN_EVAL_SAVE_INTERVAL;
@@ -1729,6 +1748,7 @@ namespace Learner
else if (option == "newbob_decay") is >> newbob_decay;
else if (option == "newbob_num_trials") is >> newbob_num_trials;
else if (option == "nn_options") is >> nn_options;
else if (option == "auto_lr_drop") is >> auto_lr_drop;
else if (option == "eval_save_interval") is >> eval_save_interval;
else if (option == "loss_output_interval") is >> loss_output_interval;
@@ -1972,6 +1992,7 @@ namespace Learner
learn_think.newbob_decay = newbob_decay;
learn_think.newbob_num_trials = newbob_num_trials;
learn_think.auto_lr_drop = auto_lr_drop;
learn_think.eval_save_interval = eval_save_interval;
learn_think.loss_output_interval = loss_output_interval;