One more tweak.
@@ -113,7 +113,7 @@ lr = 0.0001 // initial learning rate
min_lr = 0.000001 // (1e-6) minimum learning rate
max_grad_norm = 5.0 // maximum gradient norm
weight_decay = 0.0000001 // weight decay value
-task_patience = 2 // patience in decaying per-task learning rate
+task_patience = 1 // patience in decaying per-task learning rate
scheduler_threshold = 0.0001 // threshold used in deciding when to lower learning rate
lr_decay_factor = 0.5 // learning rate decay factor, when validation score
// doesn't improve
@@ -145,47 +145,54 @@ rte_d_proj = 128
rte_classifier_dropout = 0.4
rte_pair_attn = 0
rte_val_interval = 100
+rte_lr = 0.0003
wnli_classifier_hid_dim = 128
wnli_d_proj = 128
wnli_classifier_dropout = 0.4
wnli_pair_attn = 0
wnli_val_interval = 100
+wnli_lr = 0.0003
mrpc_classifier_hid_dim = 256
mrpc_d_proj = 256
mrpc_classifier_dropout = 0.2
mrpc_pair_attn = 0
mrpc_val_interval = 100
-
+mrpc_lr = 0.0003
sst_classifier_hid_dim = 256
sst_d_proj = 256
sst_classifier_dropout = 0.2
sst_val_interval = 100
+sst_lr = 0.0003
cola_classifier_hid_dim = 256
cola_d_proj = 256
cola_classifier_dropout = 0.2
cola_val_interval = 100
-
+cola_lr = 0.0003
sts-b_classifier_hid_dim = 512
sts-b_classifier_dropout = 0.2
sts-b_pair_attn = 1
sts-b_val_interval = 1000
+sts-b_lr = 0.0003
qnli_classifier_hid_dim = 512
qnli_classifier_dropout = 0.2
qnli_pair_attn = 1
qnli_val_interval = 1000
+qnli_lr = 0.0003
mnli_classifier_hid_dim = 512
mnli_classifier_dropout = 0.2
mnli_pair_attn = 1
mnli_val_interval = 1000
+mnli_lr = 0.0003
qqp_classifier_hid_dim = 512
qqp_classifier_dropout = 0.2
qqp_pair_attn = 1
-qqp_val_interval = 5000
+qqp_val_interval = 2500
+qqp_lr = 0.0003
