| | --- |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: Testing |
| | 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. --> |
| |
|
| | # Testing |
| |
|
| | This model is a fine-tuned version of [microsoft/codebert-base-mlm](https://huggingface.co/microsoft/codebert-base-mlm) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.4526 |
| | - Accuracy: 0.9038 |
| |
|
| | ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 10 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | | 0.7258 | 1.0 | 1373 | 0.5835 | 0.8779 | |
| | | 0.5861 | 2.0 | 2746 | 0.5315 | 0.8882 | |
| | | 0.5478 | 3.0 | 4119 | 0.5053 | 0.8941 | |
| | | 0.5338 | 4.0 | 5492 | 0.4929 | 0.8974 | |
| | | 0.5045 | 5.0 | 6865 | 0.4836 | 0.8995 | |
| | | 0.4958 | 6.0 | 8238 | 0.4662 | 0.9018 | |
| | | 0.4821 | 7.0 | 9611 | 0.4561 | 0.9035 | |
| | | 0.469 | 8.0 | 10984 | 0.4625 | 0.9034 | |
| | | 0.4718 | 9.0 | 12357 | 0.4522 | 0.9048 | |
| | | 0.4642 | 10.0 | 13730 | 0.4526 | 0.9038 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.25.1 |
| | - Pytorch 1.13.0+cu117 |
| | - Datasets 2.7.1 |
| | - Tokenizers 0.13.2 |
| |
|
