ar_specific_model / README.md
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---
base_model: ZeyadAhmed/AraElectra-Arabic-SQuADv2-QA
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: ar_specific_model
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. -->
# ar_specific_model
This model is a fine-tuned version of [ZeyadAhmed/AraElectra-Arabic-SQuADv2-QA](https://huggingface.co/ZeyadAhmed/AraElectra-Arabic-SQuADv2-QA) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1789
- Accuracy: 0.9437
- F1: 0.9452
- Precision: 0.9212
- Recall: 0.9706
## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.202 | 1.0 | 1850 | 0.1789 | 0.9437 | 0.9452 | 0.9212 | 0.9706 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1