|
|
--- |
|
|
base_model: elnasharomar2/ANER_arabic_keyword_extraction_dataset1 |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- precision |
|
|
- recall |
|
|
- f1 |
|
|
- accuracy |
|
|
model-index: |
|
|
- name: ANER_arabic_keyword_extraction_dataset1 |
|
|
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. --> |
|
|
|
|
|
# ANER_arabic_keyword_extraction_dataset1 |
|
|
|
|
|
This model is a fine-tuned version of [elnasharomar2/ANER_arabic_keyword_extraction_dataset1](https://huggingface.co/elnasharomar2/ANER_arabic_keyword_extraction_dataset1) on the None dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.1708 |
|
|
- Precision: 0.7713 |
|
|
- Recall: 0.7690 |
|
|
- F1: 0.7701 |
|
|
- Accuracy: 0.9767 |
|
|
|
|
|
## 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: 2e-05 |
|
|
- train_batch_size: 16 |
|
|
- eval_batch_size: 8 |
|
|
- seed: 42 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: linear |
|
|
- num_epochs: 15 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
|
|
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
|
| 0.0062 | 1.0 | 675 | 0.1415 | 0.74 | 0.7404 | 0.7402 | 0.9737 | |
|
|
| 0.0074 | 2.0 | 1350 | 0.1452 | 0.7086 | 0.7726 | 0.7392 | 0.9727 | |
|
|
| 0.0061 | 3.0 | 2025 | 0.1356 | 0.7296 | 0.7447 | 0.7371 | 0.9742 | |
|
|
| 0.0051 | 4.0 | 2700 | 0.1448 | 0.7456 | 0.7374 | 0.7415 | 0.9743 | |
|
|
| 0.0038 | 5.0 | 3375 | 0.1437 | 0.7696 | 0.7453 | 0.7572 | 0.9763 | |
|
|
| 0.0029 | 6.0 | 4050 | 0.1555 | 0.7702 | 0.7562 | 0.7632 | 0.9763 | |
|
|
| 0.0028 | 7.0 | 4725 | 0.1500 | 0.7636 | 0.7483 | 0.7559 | 0.9757 | |
|
|
| 0.0028 | 8.0 | 5400 | 0.1522 | 0.7648 | 0.7574 | 0.7611 | 0.9761 | |
|
|
| 0.0019 | 9.0 | 6075 | 0.1585 | 0.7584 | 0.7671 | 0.7627 | 0.9757 | |
|
|
| 0.002 | 10.0 | 6750 | 0.1637 | 0.7567 | 0.7659 | 0.7613 | 0.9754 | |
|
|
| 0.0019 | 11.0 | 7425 | 0.1686 | 0.7783 | 0.7514 | 0.7646 | 0.9760 | |
|
|
| 0.0013 | 12.0 | 8100 | 0.1659 | 0.7877 | 0.7538 | 0.7704 | 0.9770 | |
|
|
| 0.0011 | 13.0 | 8775 | 0.1636 | 0.7759 | 0.7683 | 0.7721 | 0.9767 | |
|
|
| 0.001 | 14.0 | 9450 | 0.1720 | 0.7733 | 0.7635 | 0.7684 | 0.9765 | |
|
|
| 0.0009 | 15.0 | 10125 | 0.1708 | 0.7713 | 0.7690 | 0.7701 | 0.9767 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.35.2 |
|
|
- Pytorch 2.1.0+cu118 |
|
|
- Datasets 2.15.0 |
|
|
- Tokenizers 0.15.0 |
|
|
|
