| | --- |
| | base_model: aubmindlab/bert-base-arabertv02 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: 2levels_6565 |
| | 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_6565 |
| | |
| | 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: 0.8327 |
| | - Macro F1: 0.7976 |
| | - Macro Precision: 0.8038 |
| | - Macro Recall: 0.7993 |
| | - Accuracy: 0.7982 |
| | |
| | ## 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 | 103 | 0.4498 | 0.8015 | 0.8015 | 0.8016 | 0.8015 | |
| | | No log | 2.0 | 206 | 0.4532 | 0.8035 | 0.8083 | 0.8049 | 0.8039 | |
| | | No log | 3.0 | 309 | 0.5014 | 0.8066 | 0.8084 | 0.8073 | 0.8067 | |
| | | No log | 4.0 | 412 | 0.6651 | 0.7985 | 0.8048 | 0.8002 | 0.7991 | |
| | | 0.245 | 5.0 | 515 | 0.7793 | 0.8004 | 0.8050 | 0.8017 | 0.8008 | |
| | | 0.245 | 6.0 | 618 | 0.8327 | 0.7976 | 0.8038 | 0.7993 | 0.7982 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.43.4 |
| | - Pytorch 2.6.0+cu124 |
| | - Datasets 3.4.1 |
| | - Tokenizers 0.19.1 |
| | |
