| --- |
| library_name: transformers |
| license: mit |
| base_model: roberta-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: roberta-base_LOGIC_LRTC |
| 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. --> |
|
|
| # roberta-base_LOGIC_LRTC |
|
|
| This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.9419 |
| - Accuracy: 0.6933 |
| - Macro Precision: 0.6604 |
| - Macro F1: 0.6503 |
|
|
| ## 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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 12 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro Precision | Macro F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:--------:| |
| | No log | 1.0 | 116 | 1.5639 | 0.41 | 0.4728 | 0.3904 | |
| | No log | 2.0 | 232 | 1.1501 | 0.5833 | 0.5591 | 0.5659 | |
| | No log | 3.0 | 348 | 1.1315 | 0.64 | 0.6182 | 0.6220 | |
| | No log | 4.0 | 464 | 1.2345 | 0.67 | 0.6471 | 0.6237 | |
| | 0.9897 | 5.0 | 580 | 1.3952 | 0.62 | 0.5912 | 0.5960 | |
| | 0.9897 | 6.0 | 696 | 1.5032 | 0.68 | 0.6370 | 0.6407 | |
| | 0.9897 | 7.0 | 812 | 1.6859 | 0.6833 | 0.6437 | 0.6478 | |
| | 0.9897 | 8.0 | 928 | 1.9130 | 0.69 | 0.6638 | 0.6393 | |
| | 0.0959 | 9.0 | 1044 | 1.9246 | 0.68 | 0.6526 | 0.6459 | |
| | 0.0959 | 10.0 | 1160 | 1.8800 | 0.6867 | 0.6378 | 0.6392 | |
| | 0.0959 | 11.0 | 1276 | 1.9436 | 0.69 | 0.6623 | 0.6519 | |
| | 0.0959 | 12.0 | 1392 | 1.9419 | 0.6933 | 0.6604 | 0.6503 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.0.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
| |
