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conplag1_graphcodebert_ep30_bs16_lr2e-05_l512_s42_ppy_loss
buelfhood/conplag1_graphcodebert_ep30_bs16_lr2e-05_l512_s42_ppy_loss
conplag1_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 16, 2025
- Updated
- Nov 16, 2025
- SHA
- 778938d4
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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. -->
conplag1_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: 0.4769
- Accuracy: 0.8321
- Recall: 0.6316
- Precision: 0.7273
- F1: 0.6761
- F Beta Score: 0.6582
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 |
|---|---|---|---|---|---|---|---|---|
| 0.6532 | 1.0 | 40 | 0.5811 | 0.6277 | 0.8684 | 0.4177 | 0.5641 | 0.6520 |
| 0.5415 | 2.0 | 80 | 0.4769 | 0.8321 | 0.6316 | 0.7273 | 0.6761 | 0.6582 |
| 0.4812 | 3.0 | 120 | 0.6863 | 0.8321 | 0.4737 | 0.8571 | 0.6102 | 0.5493 |
| 0.2384 | 4.0 | 160 | 0.6612 | 0.8467 | 0.5263 | 0.8696 | 0.6557 | 0.5991 |
| 0.2433 | 5.0 | 200 | 0.6021 | 0.8394 | 0.5526 | 0.8077 | 0.6562 | 0.6121 |
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 16, 2025
- Updated
- Nov 16, 2025