| --- |
| library_name: transformers |
| base_model: microsoft/codebert-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: gpad-v1-full-taskA-sample |
| results: [] |
| --- |
| |
| <!-- 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. --> |
|
|
| # gpad-v1-full-taskA-sample |
|
|
| This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 41.9177 |
| - Accuracy: 0.195 |
| - F1 Macro: 0.3264 |
| - F1 Weighted: 0.0636 |
| - Precision Macro: 0.195 |
| - Recall Macro: 1.0 |
|
|
| ## 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 |
| - lr_scheduler_warmup_steps: 500 |
| - num_epochs: 3 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted | Precision Macro | Recall Macro | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|:---------------:|:------------:| |
| | No log | 1.0 | 13 | 42.3584 | 0.195 | 0.3264 | 0.0636 | 0.195 | 1.0 | |
| | No log | 2.0 | 26 | 42.1852 | 0.195 | 0.3264 | 0.0636 | 0.195 | 1.0 | |
| | No log | 3.0 | 39 | 41.9177 | 0.195 | 0.3264 | 0.0636 | 0.195 | 1.0 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.53.3 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 4.0.0 |
| - Tokenizers 0.21.2 |
| |
