| | --- |
| | base_model: aubmindlab/bert-base-arabertv02 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: 2levels_8753 |
| | 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. --> |
| |
|
| | # 2levels_8753 |
| | |
| | This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.8957 |
| | - Macro F1: 0.8037 |
| | - Macro Precision: 0.8110 |
| | - Macro Recall: 0.8056 |
| | - Accuracy: 0.8044 |
| | |
| | ## 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: 5e-05 |
| | - train_batch_size: 64 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 6 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Macro F1 | Macro Precision | Macro Recall | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:| |
| | | No log | 1.0 | 137 | 0.4537 | 0.7923 | 0.8075 | 0.7957 | 0.7940 | |
| | | No log | 2.0 | 274 | 0.4196 | 0.8096 | 0.8122 | 0.8104 | 0.8097 | |
| | | No log | 3.0 | 411 | 0.5097 | 0.8020 | 0.8117 | 0.8043 | 0.8029 | |
| | | 0.2839 | 4.0 | 548 | 0.6446 | 0.8023 | 0.8101 | 0.8043 | 0.8031 | |
| | | 0.2839 | 5.0 | 685 | 0.8924 | 0.7857 | 0.8089 | 0.7906 | 0.7885 | |
| | | 0.2839 | 6.0 | 822 | 0.8957 | 0.8037 | 0.8110 | 0.8056 | 0.8044 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.43.4 |
| | - Pytorch 2.6.0+cu124 |
| | - Datasets 3.4.1 |
| | - Tokenizers 0.19.1 |
| | |
