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2026-04-28 11:00:57,792 - INFO - ===== Training Configuration =====
2026-04-28 11:00:57,793 - INFO - model_name : microsoft/graphcodebert-base
2026-04-28 11:00:57,793 - INFO - output_dir : output_checkpoints/graphcodebert-vanilla/
2026-04-28 11:00:57,794 - INFO - num_epochs : 3
2026-04-28 11:00:57,796 - INFO - max_steps : -1
2026-04-28 11:00:57,796 - INFO - batch_size : 256
2026-04-28 11:00:57,797 - INFO - learning_rate : 2e-05
2026-04-28 11:00:57,798 - INFO - max_length : 512
2026-04-28 11:00:57,799 - INFO - num_labels : 2
2026-04-28 11:00:57,800 - INFO - use_wandb : True
2026-04-28 11:00:57,800 - INFO - freeze_base : True
2026-04-28 11:00:57,801 - INFO - loss_type : ce
2026-04-28 11:00:57,801 - INFO - focal_alpha : 1.0
2026-04-28 11:00:57,802 - INFO - focal_gamma : 2.0
2026-04-28 11:00:57,803 - INFO - r_drop_alpha : 6.0
2026-04-28 11:00:57,803 - INFO - infonce_temperature : 0.07
2026-04-28 11:00:57,805 - INFO - infonce_weight : 0.5
2026-04-28 11:00:57,806 - INFO - seed : 42
2026-04-28 11:00:57,806 - INFO - wandb_run_name : graphcodebert-vanilla
2026-04-28 11:00:57,808 - INFO - resume_from_checkpoint : None
2026-04-28 11:00:57,808 - INFO - save_steps : 100
2026-04-28 11:00:57,809 - INFO - eval_steps : 50
2026-04-28 11:00:57,810 - INFO - logging_steps : 5
2026-04-28 11:00:57,810 - INFO - label_smoothing : 0
2026-04-28 11:00:57,811 - INFO - adversarial_epsilon : 0
2026-04-28 11:00:57,812 - INFO - use_swa : False
2026-04-28 11:00:57,813 - INFO - swa_start_epoch : 0
2026-04-28 11:00:57,814 - INFO - swa_lr : 1e-05
2026-04-28 11:00:57,815 - INFO - data_augmentation : False
2026-04-28 11:00:57,816 - INFO - aug_rename_prob : 0.0
2026-04-28 11:00:57,817 - INFO - aug_format_prob : 0.0
2026-04-28 11:00:57,817 - INFO - mixup_alpha : 0.0
2026-04-28 11:00:57,818 - INFO - low_pass_keep_ratio : 0.5
2026-04-28 11:00:57,819 - INFO - freq_consistency_weight : 0.0
2026-04-28 11:00:57,819 - INFO - hidden_dropout_prob : 0.3
2026-04-28 11:00:57,820 - INFO - attention_probs_dropout_prob : 0.3
2026-04-28 11:00:57,821 - INFO - classifier_dropout : 0.3
2026-04-28 11:00:57,822 - INFO - =================================
2026-04-28 11:00:58,827 - INFO - Model placed on cuda
2026-04-28 11:00:58,830 - INFO - ===== Model Architecture =====
2026-04-28 11:00:58,832 - INFO -
RobertaForSequenceClassification(
(roberta): RobertaModel(
(embeddings): RobertaEmbeddings(
(word_embeddings): Embedding(50265, 768, padding_idx=1)
(position_embeddings): Embedding(514, 768, padding_idx=1)
(token_type_embeddings): Embedding(1, 768)
(LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
(dropout): Dropout(p=0.3, inplace=False)
)
(encoder): RobertaEncoder(
(layer): ModuleList(
(0-11): 12 x RobertaLayer(
(attention): RobertaAttention(
(self): RobertaSdpaSelfAttention(
(query): Linear(in_features=768, out_features=768, bias=True)
(key): Linear(in_features=768, out_features=768, bias=True)
(value): Linear(in_features=768, out_features=768, bias=True)
(dropout): Dropout(p=0.3, inplace=False)
)
(output): RobertaSelfOutput(
(dense): Linear(in_features=768, out_features=768, bias=True)
(LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
(dropout): Dropout(p=0.3, inplace=False)
)
)
(intermediate): RobertaIntermediate(
(dense): Linear(in_features=768, out_features=3072, bias=True)
(intermediate_act_fn): GELUActivation()
)
(output): RobertaOutput(
(dense): Linear(in_features=3072, out_features=768, bias=True)
(LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
(dropout): Dropout(p=0.3, inplace=False)
)
)
)
)
)
(classifier): RobertaClassificationHead(
(dense): Linear(in_features=768, out_features=768, bias=True)
(dropout): Dropout(p=0.3, inplace=False)
(out_proj): Linear(in_features=768, out_features=2, bias=True)
)
)
2026-04-28 11:00:58,834 - INFO - ===== Parameter Summary =====
2026-04-28 11:00:58,834 - INFO - Total Parameters: 124,647,170
2026-04-28 11:00:58,835 - INFO - Trainable Parameters: 592,130
2026-04-28 11:00:58,836 - INFO - Non-trainable Parameters: 124,055,040
2026-04-28 11:00:58,836 - INFO - ===== Tokenizer Summary =====
2026-04-28 11:00:58,850 - INFO - Vocab size: 50265 | Special tokens: ['<s>', '</s>', '<unk>', '<pad>', '<mask>']
2026-04-28 11:00:58,851 - INFO - ===== End of Architecture Log =====
2026-04-28 11:04:20,159 - INFO - === Starting training with MixCode + FFT low-pass consistency ===
2026-04-28 12:00:21,592 - INFO - Training completed successfully.
2026-04-28 12:00:23,561 - INFO - Final model saved to output_checkpoints/graphcodebert-vanilla/final_model