Instructions to use dzungpham/graphcodebert-code-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dzungpham/graphcodebert-code-classification with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dzungpham/graphcodebert-code-classification", dtype="auto") - Notebooks
- Google Colab
- Kaggle
upload best checkpoints 100 graphcodebert mixcode fft
Browse files- graphcodebert-mixcode-fft/checkpoint-100/config.json +2 -2
- graphcodebert-mixcode-fft/checkpoint-100/model.safetensors +1 -1
- graphcodebert-mixcode-fft/checkpoint-100/optimizer.pt +1 -1
- graphcodebert-mixcode-fft/checkpoint-100/trainer_state.json +3 -74
- graphcodebert-mixcode-fft/checkpoint-100/training_args.bin +1 -1
- graphcodebert-mixcode-fft/checkpoint-150/config.json +29 -0
- graphcodebert-mixcode-fft/checkpoint-150/merges.txt +0 -0
- graphcodebert-mixcode-fft/checkpoint-150/model.safetensors +3 -0
- graphcodebert-mixcode-fft/checkpoint-150/optimizer.pt +3 -0
- graphcodebert-mixcode-fft/checkpoint-150/rng_state.pth +3 -0
- graphcodebert-mixcode-fft/checkpoint-150/scaler.pt +3 -0
- graphcodebert-mixcode-fft/checkpoint-150/scheduler.pt +3 -0
- graphcodebert-mixcode-fft/checkpoint-150/special_tokens_map.json +51 -0
- graphcodebert-mixcode-fft/checkpoint-150/tokenizer.json +0 -0
- graphcodebert-mixcode-fft/checkpoint-150/tokenizer_config.json +58 -0
- graphcodebert-mixcode-fft/checkpoint-150/trainer_state.json +42 -0
- graphcodebert-mixcode-fft/checkpoint-150/training_args.bin +3 -0
- graphcodebert-mixcode-fft/checkpoint-150/vocab.json +0 -0
- graphcodebert-mixcode-fft/checkpoint-200/config.json +2 -2
- graphcodebert-mixcode-fft/checkpoint-200/model.safetensors +1 -1
- graphcodebert-mixcode-fft/checkpoint-200/optimizer.pt +1 -1
- graphcodebert-mixcode-fft/checkpoint-200/trainer_state.json +3 -144
- graphcodebert-mixcode-fft/checkpoint-200/training_args.bin +1 -1
- graphcodebert-mixcode-fft/checkpoint-50/config.json +29 -0
- graphcodebert-mixcode-fft/checkpoint-50/merges.txt +0 -0
- graphcodebert-mixcode-fft/checkpoint-50/model.safetensors +3 -0
- graphcodebert-mixcode-fft/checkpoint-50/optimizer.pt +3 -0
- graphcodebert-mixcode-fft/checkpoint-50/rng_state.pth +3 -0
- graphcodebert-mixcode-fft/checkpoint-50/scaler.pt +3 -0
- graphcodebert-mixcode-fft/checkpoint-50/scheduler.pt +3 -0
- graphcodebert-mixcode-fft/checkpoint-50/special_tokens_map.json +51 -0
- graphcodebert-mixcode-fft/checkpoint-50/tokenizer.json +0 -0
- graphcodebert-mixcode-fft/checkpoint-50/tokenizer_config.json +58 -0
- graphcodebert-mixcode-fft/checkpoint-50/trainer_state.json +42 -0
- graphcodebert-mixcode-fft/checkpoint-50/training_args.bin +3 -0
- graphcodebert-mixcode-fft/checkpoint-50/vocab.json +0 -0
- graphcodebert-mixcode-fft/training.log +48 -43
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graphcodebert-mixcode-fft/checkpoint-100/training_args.bin
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graphcodebert-mixcode-fft/checkpoint-150/config.json
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graphcodebert-mixcode-fft/checkpoint-150/merges.txt
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graphcodebert-mixcode-fft/checkpoint-150/model.safetensors
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graphcodebert-mixcode-fft/checkpoint-150/optimizer.pt
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graphcodebert-mixcode-fft/checkpoint-200/training_args.bin
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ADDED
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graphcodebert-mixcode-fft/checkpoint-50/model.safetensors
ADDED
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ADDED
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graphcodebert-mixcode-fft/checkpoint-50/tokenizer_config.json
ADDED
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graphcodebert-mixcode-fft/checkpoint-50/trainer_state.json
ADDED
|
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| 19 |
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graphcodebert-mixcode-fft/checkpoint-50/training_args.bin
ADDED
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graphcodebert-mixcode-fft/training.log
CHANGED
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RobertaForSequenceClassification(
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(roberta): RobertaModel(
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(embeddings): RobertaEmbeddings(
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@@ -71,16 +76,16 @@ RobertaForSequenceClassification(
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(classifier): RobertaClassificationHead(
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(dense): Linear(in_features=768, out_features=768, bias=True)
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(dropout): Dropout(p=0.
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2026-04-20 11:06:55,458 - INFO - ===== Training Configuration =====
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2026-04-20 11:06:55,460 - INFO - model_name : microsoft/graphcodebert-base
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2026-04-20 11:06:55,464 - INFO - output_dir : output_checkpoints/graphcodebert-mixcode-fft
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2026-04-20 11:06:55,466 - INFO - num_epochs : 4
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2026-04-20 11:06:55,467 - INFO - batch_size : 64
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2026-04-20 11:06:55,468 - INFO - learning_rate : 5e-05
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2026-04-20 11:06:55,471 - INFO - max_length : 512
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2026-04-20 11:06:55,472 - INFO - num_labels : 2
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| 9 |
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2026-04-20 11:06:55,474 - INFO - use_wandb : True
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| 10 |
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2026-04-20 11:06:55,475 - INFO - freeze_base : True
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2026-04-20 11:06:55,476 - INFO - loss_type : r-drop
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2026-04-20 11:06:55,478 - INFO - focal_alpha : 1.0
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2026-04-20 11:06:55,480 - INFO - focal_gamma : 2.0
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2026-04-20 11:06:55,482 - INFO - r_drop_alpha : 6.0
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2026-04-20 11:06:55,483 - INFO - infonce_temperature : 0.07
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2026-04-20 11:06:55,485 - INFO - infonce_weight : 0.5
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2026-04-20 11:06:55,487 - INFO - seed : 42
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2026-04-20 11:06:55,488 - INFO - resume_from_checkpoint : None
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2026-04-20 11:06:55,490 - INFO - save_steps : 50
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2026-04-20 11:06:55,491 - INFO - eval_steps : 1000
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2026-04-20 11:06:55,494 - INFO - label_smoothing : 0.3
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2026-04-20 11:06:55,499 - INFO - adversarial_epsilon : 0.5
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| 23 |
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2026-04-20 11:06:55,504 - INFO - use_swa : True
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| 24 |
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2026-04-20 11:06:55,508 - INFO - swa_start_epoch : 2
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| 25 |
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2026-04-20 11:06:55,510 - INFO - swa_lr : 1e-05
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| 26 |
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2026-04-20 11:06:55,511 - INFO - data_augmentation : True
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| 27 |
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2026-04-20 11:06:55,512 - INFO - aug_rename_prob : 0.6
|
| 28 |
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2026-04-20 11:06:55,514 - INFO - aug_format_prob : 0.6
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| 29 |
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2026-04-20 11:06:55,516 - INFO - hidden_dropout_prob : 0.3
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| 30 |
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2026-04-20 11:06:55,518 - INFO - attention_probs_dropout_prob : 0.3
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| 31 |
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2026-04-20 11:06:55,519 - INFO - classifier_dropout : 0.3
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| 32 |
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2026-04-20 11:06:55,521 - INFO - mixup_alpha : 1.0
|
| 33 |
+
2026-04-20 11:06:55,523 - INFO - low_pass_keep_ratio : 0.5
|
| 34 |
+
2026-04-20 11:06:55,524 - INFO - freq_consistency_weight : 0.2
|
| 35 |
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2026-04-20 11:06:55,526 - INFO - =================================
|
| 36 |
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2026-04-20 11:06:59,772 - INFO - Model placed on cuda
|
| 37 |
+
2026-04-20 11:06:59,789 - INFO - ===== Model Architecture =====
|
| 38 |
+
2026-04-20 11:06:59,794 - INFO -
|
| 39 |
RobertaForSequenceClassification(
|
| 40 |
(roberta): RobertaModel(
|
| 41 |
(embeddings): RobertaEmbeddings(
|
|
|
|
| 76 |
)
|
| 77 |
(classifier): RobertaClassificationHead(
|
| 78 |
(dense): Linear(in_features=768, out_features=768, bias=True)
|
| 79 |
+
(dropout): Dropout(p=0.3, inplace=False)
|
| 80 |
(out_proj): Linear(in_features=768, out_features=2, bias=True)
|
| 81 |
)
|
| 82 |
)
|
| 83 |
+
2026-04-20 11:06:59,803 - INFO - ===== Parameter Summary =====
|
| 84 |
+
2026-04-20 11:06:59,809 - INFO - Total Parameters: 124,647,170
|
| 85 |
+
2026-04-20 11:06:59,810 - INFO - Trainable Parameters: 592,130
|
| 86 |
+
2026-04-20 11:06:59,811 - INFO - Non-trainable Parameters: 124,055,040
|
| 87 |
+
2026-04-20 11:06:59,813 - INFO - ===== Tokenizer Summary =====
|
| 88 |
+
2026-04-20 11:06:59,908 - INFO - Vocab size: 50265 | Special tokens: ['<s>', '</s>', '<unk>', '<pad>', '<mask>']
|
| 89 |
+
2026-04-20 11:06:59,912 - INFO - ===== End of Architecture Log =====
|
| 90 |
+
2026-04-20 11:06:59,917 - INFO - Data augmentation enabled (rename=0.6, format=0.6)
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| 91 |
+
2026-04-20 11:07:10,050 - INFO - === Starting training with MixCode + FFT low-pass consistency ===
|