| --- |
| library_name: transformers |
| base_model: microsoft/codebert-base-mlm |
| tags: |
| - generated_from_trainer |
| datasets: |
| - devgpt-aimotion/the-stack-v2_PlantUML_filtered |
| metrics: |
| - accuracy |
| model-index: |
| - name: codebert_base_code_uml_c |
| results: |
| - task: |
| name: Masked Language Modeling |
| type: fill-mask |
| dataset: |
| name: devgpt-aimotion/the-stack-v2_PlantUML_filtered |
| type: devgpt-aimotion/the-stack-v2_PlantUML_filtered |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.9053223443951083 |
| --- |
| |
| <!-- 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. --> |
|
|
| # codebert_base_code_uml_c |
|
|
| This model is a fine-tuned version of [microsoft/codebert-base-mlm](https://huggingface.co/microsoft/codebert-base-mlm) on the devgpt-aimotion/the-stack-v2_PlantUML_filtered dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4533 |
| - Accuracy: 0.9053 |
|
|
| ## 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: 0.0001 |
| - train_batch_size: 96 |
| - eval_batch_size: 96 |
| - seed: 10 |
| - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 10000 |
| - num_epochs: 5 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:------:|:-----:|:---------------:|:--------:| |
| | 0.5254 | 4.3592 | 10000 | 0.4521 | 0.9053 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.51.2 |
| - Pytorch 2.6.0+cu126 |
| - Datasets 3.5.0 |
| - Tokenizers 0.21.1 |
| |
