|
--- |
|
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. |
|
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 |
|
|
