|
--- |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- precision |
|
- recall |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: AraBERT_token_classification__AraEval24_fixed |
|
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_token_classification__AraEval24_fixed |
|
|
|
This model is a fine-tuned version of [aubmindlab/bert-base-arabert](https://huggingface.co/aubmindlab/bert-base-arabert) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.8758 |
|
- Precision: 0.0901 |
|
- Recall: 0.0234 |
|
- F1: 0.0371 |
|
- Accuracy: 0.8606 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- 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 | Validation Loss | Precision | Recall | F1 | Accuracy | |
|
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
| 0.6563 | 1.0 | 2851 | 0.7705 | 0.0391 | 0.0006 | 0.0012 | 0.8632 | |
|
| 0.5865 | 2.0 | 5702 | 0.8071 | 0.0909 | 0.0028 | 0.0055 | 0.8636 | |
|
| 0.5382 | 3.0 | 8553 | 0.7815 | 0.0578 | 0.0012 | 0.0024 | 0.8634 | |
|
| 0.5043 | 4.0 | 11404 | 0.7883 | 0.0798 | 0.0021 | 0.0041 | 0.8633 | |
|
| 0.4445 | 5.0 | 14255 | 0.8188 | 0.0801 | 0.0031 | 0.0060 | 0.8637 | |
|
| 0.4295 | 6.0 | 17106 | 0.8070 | 0.0877 | 0.0155 | 0.0263 | 0.8610 | |
|
| 0.4096 | 7.0 | 19957 | 0.8184 | 0.0949 | 0.0135 | 0.0236 | 0.8627 | |
|
| 0.3827 | 8.0 | 22808 | 0.8362 | 0.0818 | 0.0181 | 0.0296 | 0.8600 | |
|
| 0.3525 | 9.0 | 25659 | 0.8458 | 0.0893 | 0.0254 | 0.0395 | 0.8599 | |
|
| 0.3434 | 10.0 | 28510 | 0.8758 | 0.0901 | 0.0234 | 0.0371 | 0.8606 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.30.2 |
|
- Pytorch 1.12.1 |
|
- Datasets 2.13.2 |
|
- Tokenizers 0.13.3 |
|
|
