metadata
base_model: aubmindlab/bert-base-arabertv2
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
model-index:
- name: AraBert-finetuned-text-classification
results: []
AraBert-finetuned-text-classification
This model is a fine-tuned version of aubmindlab/bert-base-arabertv2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1192
- Macro F1: 0.9610
- Accuracy: 0.9612
- Recall: 0.9612
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 | 0.9912 | 56 | 0.9585 | 0.1400 | 0.9582 | 0.9585 |
| No log | 2.0 | 113 | 0.9601 | 0.1324 | 0.9600 | 0.9602 |
| No log | 2.9912 | 169 | 0.9612 | 0.1192 | 0.9610 | 0.9612 |
| No log | 4.0 | 226 | 0.9623 | 0.1393 | 0.9621 | 0.9623 |
| No log | 4.9912 | 282 | 0.9596 | 0.1366 | 0.9596 | 0.9595 |
| No log | 6.0 | 339 | 0.9607 | 0.1590 | 0.9606 | 0.9607 |
| No log | 6.9912 | 395 | 0.9601 | 0.1741 | 0.9600 | 0.9602 |
| No log | 8.0 | 452 | 0.9612 | 0.1824 | 0.9611 | 0.9612 |
| 0.0099 | 8.9912 | 504 | 0.1775 | 0.9617 | 0.9618 | 0.9617 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1