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: 0.1147
- 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