dzungpham/graphcodebert-code-classification
0
12026-04-24 17:13:03,934 - INFO - Loading model and tokenizer from: output_checkpoints/graphcodebert-base-lowLR-highBatchSize/checkpoint-50022026-04-24 17:13:04,114 - INFO - ===== Model Architecture =====32026-04-24 17:13:04,116 - INFO - 4RobertaForSequenceClassification(5 (roberta): RobertaModel(6 (embeddings): RobertaEmbeddings(7 (word_embeddings): Embedding(50265, 768, padding_idx=1)8 (position_embeddings): Embedding(514, 768, padding_idx=1)9 (token_type_embeddings): Embedding(1, 768)10 (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)11 (dropout): Dropout(p=0.3, inplace=False)12 )13 (encoder): RobertaEncoder(14 (layer): ModuleList(15 (0-11): 12 x RobertaLayer(16 (attention): RobertaAttention(17 (self): RobertaSdpaSelfAttention(18 (query): Linear(in_features=768, out_features=768, bias=True)19 (key): Linear(in_features=768, out_features=768, bias=True)20 (value): Linear(in_features=768, out_features=768, bias=True)21 (dropout): Dropout(p=0.3, inplace=False)22 )23 (output): RobertaSelfOutput(24 (dense): Linear(in_features=768, out_features=768, bias=True)25 (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)26 (dropout): Dropout(p=0.3, inplace=False)27 )28 )29 (intermediate): RobertaIntermediate(30 (dense): Linear(in_features=768, out_features=3072, bias=True)31 (intermediate_act_fn): GELUActivation()32 )33 (output): RobertaOutput(34 (dense): Linear(in_features=3072, out_features=768, bias=True)35 (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)36 (dropout): Dropout(p=0.3, inplace=False)37 )38 )39 )40 )41 )42 (classifier): RobertaClassificationHead(43 (dense): Linear(in_features=768, out_features=768, bias=True)44 (dropout): Dropout(p=0.3, inplace=False)45 (out_proj): Linear(in_features=768, out_features=2, bias=True)46 )47)482026-04-24 17:13:04,120 - INFO - ===== Parameter Summary =====492026-04-24 17:13:04,121 - INFO - Total Parameters: 124,647,170502026-04-24 17:13:04,123 - INFO - Trainable Parameters: 124,647,170512026-04-24 17:13:04,124 - INFO - Non-trainable Parameters: 0522026-04-24 17:13:04,126 - INFO - ===== Tokenizer Summary =====532026-04-24 17:13:04,144 - INFO - Vocab size: 50265 | Special tokens: ['<s>', '</s>', '<unk>', '<pad>', '<mask>']542026-04-24 17:13:04,146 - INFO - ===== End of Architecture Log =====552026-04-24 17:13:04,311 - INFO - Loading dataset: DaniilOr/SemEval-2026-Task13 (A)562026-04-24 17:13:04,792 - INFO - Tokenizing dataset...572026-04-24 17:13:04,829 - INFO - Running inference on 1000 examples...582026-04-24 17:13:35,339 - INFO - Calculating classification metrics...592026-04-24 17:13:35,359 - INFO - ------------------------------602026-04-24 17:13:35,361 - INFO - METRICS FOR SPLIT: test612026-04-24 17:13:35,362 - INFO - Accuracy: 0.7390622026-04-24 17:13:35,364 - INFO - Precision: 0.6762632026-04-24 17:13:35,365 - INFO - Recall: 0.7390642026-04-24 17:13:35,366 - INFO - F1-Score: 0.6959652026-04-24 17:13:35,368 - INFO - ------------------------------662026-04-24 17:13:35,370 - INFO - Confusion Matrix:67[[711 66]68 [195 28]]692026-04-24 17:13:35,372 - INFO - ✅ Metrics saved to test/inference/graphcodebert-base-lowLR-highBatchSize/checkpoint-500/metrics.json702026-04-24 17:13:35,375 - INFO - ✅ Predictions saved to test/inference/graphcodebert-base-lowLR-highBatchSize/checkpoint-500/submission.csv71