| | --- |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - precision |
| | - recall |
| | - f1 |
| | model-index: |
| | - name: roberta-base-mr-6000ar |
| | results: [] |
| | --- |
| | |
| | # roberta-base-mr-6000ar |
| |
|
| | This model was trained from scratch on the Internal Selection for BDC Satria Data 2024 dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0515 |
| | - Accuracy: 0.9413 |
| | - Precision: 0.9643 |
| | - Recall: 0.9265 |
| | - F1: 0.9450 |
| |
|
| | ## Model description |
| |
|
| | Training dataset was augmented with the paraphrasing method to generate 6000 extra data. |
| |
|
| | ## Intended uses & limitations |
| |
|
| | This model was not the model used for the final submission on the internal selection. |
| |
|
| | ## Training and evaluation data |
| |
|
| | The training dataset had 1500 rows of data, and an extra 6000 augmented data. The evaluation dataset had 500 rows of data. |
| |
|
| | ## 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: 3 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | | 0.0185 | 1.0 | 821 | 0.0800 | 0.9173 | 0.8879 | 0.9706 | 0.9274 | |
| | | 0.0121 | 2.0 | 1642 | 0.0789 | 0.9147 | 0.9778 | 0.8627 | 0.9167 | |
| | | 0.0101 | 3.0 | 2463 | 0.0515 | 0.9413 | 0.9643 | 0.9265 | 0.9450 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.40.1 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.19.0 |
| | - Tokenizers 0.19.1 |
| |
|
