| | --- |
| | library_name: transformers |
| | base_model: cardiffnlp/twitter-xlm-roberta-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - f1 |
| | model-index: |
| | - name: binary_classification2 |
| | 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. --> |
| |
|
| | # binary_classification2 |
| | |
| | This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.7178 |
| | - F1: 0.7750 |
| | |
| | ## 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: 5 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | F1 | |
| | |:-------------:|:------:|:----:|:---------------:|:------:| |
| | | 0.4132 | 0.2625 | 100 | 0.4500 | 0.7621 | |
| | | 0.6075 | 0.5249 | 200 | 0.4293 | 0.7781 | |
| | | 0.3672 | 0.7874 | 300 | 0.3937 | 0.7964 | |
| | | 0.3682 | 1.0499 | 400 | 0.4572 | 0.7864 | |
| | | 0.3747 | 1.3123 | 500 | 0.4268 | 0.7946 | |
| | | 0.339 | 1.5748 | 600 | 0.4087 | 0.7853 | |
| | | 0.4468 | 1.8373 | 700 | 0.4649 | 0.7972 | |
| | | 0.2621 | 2.0997 | 800 | 0.4521 | 0.7889 | |
| | | 0.2443 | 2.3622 | 900 | 0.5213 | 0.7927 | |
| | | 0.289 | 2.6247 | 1000 | 0.5290 | 0.7749 | |
| | | 0.3365 | 2.8871 | 1100 | 0.4803 | 0.7835 | |
| | | 0.3744 | 3.1496 | 1200 | 0.6371 | 0.7861 | |
| | | 0.2841 | 3.4121 | 1300 | 0.6773 | 0.7881 | |
| | | 0.2847 | 3.6745 | 1400 | 0.6217 | 0.7826 | |
| | | 0.1881 | 3.9370 | 1500 | 0.6898 | 0.7807 | |
| | | 0.0901 | 4.1995 | 1600 | 0.7506 | 0.7726 | |
| | | 0.1814 | 4.4619 | 1700 | 0.7278 | 0.7760 | |
| | | 0.3393 | 4.7244 | 1800 | 0.7157 | 0.7729 | |
| | | 0.2436 | 4.9869 | 1900 | 0.7178 | 0.7750 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.45.1 |
| | - Pytorch 2.4.0 |
| | - Datasets 3.0.1 |
| | - Tokenizers 0.20.0 |
| | |
