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conplag2_graphcodebert_ep30_bs16_lr2e-05_l512_s42_ppy_loss
buelfhood/conplag2_graphcodebert_ep30_bs16_lr2e-05_l512_s42_ppy_loss
conplag2_graphcodebert_ep30_bs16_lr2e-05_l512_s42_ppy_loss is a text classification model from buelfhood. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Nov 17, 2025
- Updated
- Nov 17, 2025
- SHA
- 44e54170
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Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
conplag2_graphcodebert_ep30_bs16_lr2e-05_l512_s42_ppy_loss
This model is a fine-tuned version of microsoft/graphcodebert-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4788
- Accuracy: 0.8175
- Recall: 0.6053
- Precision: 0.6970
- F1: 0.6479
- F Beta Score: 0.6308
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1 | F Beta Score |
|---|---|---|---|---|---|---|---|---|
| 0.6841 | 1.0 | 40 | 0.6333 | 0.4453 | 0.8947 | 0.3208 | 0.4722 | 0.5770 |
| 0.6037 | 2.0 | 80 | 0.4788 | 0.8175 | 0.6053 | 0.6970 | 0.6479 | 0.6308 |
| 0.4394 | 3.0 | 120 | 0.5023 | 0.8613 | 0.5526 | 0.9130 | 0.6885 | 0.6290 |
| 0.2871 | 4.0 | 160 | 0.5148 | 0.8394 | 0.6316 | 0.75 | 0.6857 | 0.6638 |
| 0.3375 | 5.0 | 200 | 0.7170 | 0.8321 | 0.4737 | 0.8571 | 0.6102 | 0.5493 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.8.0+cu128
- Datasets 3.1.0
- Tokenizers 0.21.4
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Created
- Nov 17, 2025
- Updated
- Nov 17, 2025