| --- |
| library_name: transformers |
| base_model: microsoft/codebert-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: codebert-td |
| 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. --> |
|
|
| # codebert-td |
|
|
| This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4325 |
| - Accuracy: 0.9492 |
| - F1 Macro: 0.6372 |
| - F1 Weighted: 0.9487 |
|
|
| ## 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: 1e-05 |
| - train_batch_size: 64 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 0.1 |
| - num_epochs: 10 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:| |
| | 0.3710 | 1.0 | 539 | 0.3667 | 0.9399 | 0.2785 | 0.9265 | |
| | 0.3190 | 2.0 | 1078 | 0.3273 | 0.9450 | 0.3737 | 0.9394 | |
| | 0.2832 | 3.0 | 1617 | 0.3055 | 0.9513 | 0.5054 | 0.9483 | |
| | 0.2518 | 4.0 | 2156 | 0.3008 | 0.9529 | 0.6363 | 0.9515 | |
| | 0.1736 | 5.0 | 2695 | 0.3219 | 0.9520 | 0.6821 | 0.9520 | |
| | 0.1768 | 6.0 | 3234 | 0.3548 | 0.9520 | 0.6803 | 0.9518 | |
| | 0.1445 | 7.0 | 3773 | 0.3569 | 0.9524 | 0.6808 | 0.9525 | |
| | 0.1154 | 8.0 | 4312 | 0.3944 | 0.9517 | 0.6895 | 0.9522 | |
| | 0.0974 | 9.0 | 4851 | 0.4116 | 0.9524 | 0.6966 | 0.9527 | |
| | 0.1000 | 10.0 | 5390 | 0.4149 | 0.9531 | 0.6886 | 0.9532 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 5.0.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.8.3 |
| - Tokenizers 0.22.2 |
|
|
