| | --- |
| | library_name: transformers |
| | base_model: aubmindlab/bert-large-arabertv02-twitter |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: improved_stance_detection_v2-fold1 |
| | 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. --> |
| |
|
| | # improved_stance_detection_v2-fold1 |
| | |
| | This model is a fine-tuned version of [aubmindlab/bert-large-arabertv02-twitter](https://huggingface.co/aubmindlab/bert-large-arabertv02-twitter) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.4010 |
| | - Accuracy: 0.5902 |
| | - Macro F1: 0.5938 |
| | - Weighted F1: 0.5921 |
| | - F1 Pro: 0.5891 |
| | - F1 Against: 0.5590 |
| | - F1 Neutral: 0.6333 |
| | |
| | ## 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: 3e-05 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 32 |
| | - 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: cosine |
| | - lr_scheduler_warmup_steps: 0.1 |
| | - num_epochs: 15 |
| | - mixed_precision_training: Native AMP |
| | - label_smoothing_factor: 0.1 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 | Weighted F1 | F1 Pro | F1 Against | F1 Neutral | |
| | |:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:-----------:|:------:|:----------:|:----------:| |
| | | 2.0675 | 1.9320 | 50 | 0.4024 | 0.5854 | 0.5880 | 0.5866 | 0.6056 | 0.5430 | 0.6154 | |
| | | 2.0157 | 3.8544 | 100 | 0.4171 | 0.5073 | 0.4646 | 0.4585 | 0.2558 | 0.4868 | 0.6512 | |
| | | 2.1266 | 5.7767 | 150 | 0.5205 | 0.3073 | 0.1567 | 0.1445 | 0.0 | 0.0 | 0.4701 | |
| | | 2.1044 | 7.6990 | 200 | 0.4990 | 0.3512 | 0.1733 | 0.1826 | 0.0 | 0.5199 | 0.0 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 5.0.0 |
| | - Pytorch 2.9.0+cu128 |
| | - Datasets 4.0.0 |
| | - Tokenizers 0.22.2 |
| |
|
