| | --- |
| | base_model: aubmindlab/bert-base-arabertv2 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - recall |
| | model-index: |
| | - name: AraBert-finetuned-text-classification |
| | 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. --> |
| |
|
| | # AraBert-finetuned-text-classification |
| |
|
| | This model is a fine-tuned version of [aubmindlab/bert-base-arabertv2](https://huggingface.co/aubmindlab/bert-base-arabertv2) on the None dataset (private). |
| | The model is fine-tuned for the following classes : |
| | [سياسة، اقتصاد، رياضة] |
| |
|
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.1147 |
| | - Macro F1: 0.9623 |
| | - Accuracy: 0.9623 |
| | - Recall: 0.9622 |
| |
|
| | ## 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: 4e-05 |
| | - train_batch_size: 32 |
| | - eval_batch_size: 32 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 128 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 10 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Accuracy | Validation Loss | Macro F1 | Recall | |
| | |:-------------:|:-----:|:----:|:--------:|:---------------:|:--------:|:------:| |
| | | No log | 0.99 | 56 | 0.9430 | 0.1530 | 0.9427 | 0.9425 | |
| | | No log | 1.99 | 112 | 0.9579 | 0.1230 | 0.9577 | 0.9577 | |
| | | No log | 3.0 | 169 | 0.9607 | 0.1287 | 0.9605 | 0.9608 | |
| | | No log | 3.99 | 225 | 0.9618 | 0.1296 | 0.9616 | 0.9618 | |
| | | No log | 5.0 | 282 | 0.9623 | 0.1147 | 0.9623 | 0.9622 | |
| | | No log | 5.99 | 338 | 0.9612 | 0.1500 | 0.9611 | 0.9612 | |
| | | No log | 7.0 | 395 | 0.9601 | 0.1953 | 0.9599 | 0.9602 | |
| | | No log | 7.99 | 451 | 0.9640 | 0.1713 | 0.9639 | 0.9640 | |
| | | 0.0526 | 9.0 | 508 | 0.9646 | 0.1748 | 0.9644 | 0.9645 | |
| | | 0.0526 | 9.92 | 560 | 0.9646 | 0.1768 | 0.9644 | 0.9645 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.38.2 |
| | - Pytorch 2.1.0+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.15.2 |
| | |
