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Fix tr_loss rescaling factor using global_step

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This commit is contained in:
Mathieu Prouveur 2019-04-29 12:58:29 +02:00
parent ed8fad7390
commit 87b9ec3843
2 changed files with 5 additions and 5 deletions
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6
examples/run_classifier.py
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@ -845,7 +845,7 @@ def main():
else:
loss.backward()
tr_loss += loss.item() * args.gradient_accumulation_steps
tr_loss += loss.item()
nb_tr_examples += input_ids.size(0)
nb_tr_steps += 1
if (step + 1) % args.gradient_accumulation_steps == 0:
@ -936,7 +936,7 @@ def main():
elif output_mode == "regression":
preds = np.squeeze(preds)
result = compute_metrics(task_name, preds, all_label_ids.numpy())
loss = tr_loss/nb_tr_steps if args.do_train else None
loss = tr_loss/global_step if args.do_train else None
result['eval_loss'] = eval_loss
result['global_step'] = global_step
@ -1004,7 +1004,7 @@ def main():
preds = preds[0]
preds = np.argmax(preds, axis=1)
result = compute_metrics(task_name, preds, all_label_ids.numpy())
loss = tr_loss/nb_tr_steps if args.do_train else None
loss = tr_loss/global_step if args.do_train else None
result['eval_loss'] = eval_loss
result['global_step'] = global_step

4
examples/run_swag.py
View File

@ -452,7 +452,7 @@ def main():
loss = loss * args.loss_scale
if args.gradient_accumulation_steps > 1:
loss = loss / args.gradient_accumulation_steps
tr_loss += loss.item() * args.gradient_accumulation_steps
tr_loss += loss.item()
nb_tr_examples += input_ids.size(0)
nb_tr_steps += 1
@ -537,7 +537,7 @@ def main():
result = {'eval_loss': eval_loss,
'eval_accuracy': eval_accuracy,
'global_step': global_step,
'loss': tr_loss/nb_tr_steps}
'loss': tr_loss/global_step}
output_eval_file = os.path.join(args.output_dir, "eval_results.txt")
with open(output_eval_file, "w") as writer: