---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: ABSA-SentencePair-corrected-domainAdapt-Stack-Semeval-Adapter-houlsby-run3
  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. -->

# ABSA-SentencePair-corrected-domainAdapt-Stack-Semeval-Adapter-houlsby-run3

This model is a fine-tuned version of [CAMeL-Lab/bert-base-arabic-camelbert-msa](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3204
- Accuracy: 0.8752
- F1: 0.8752
- Precision: 0.8752
- Recall: 0.8752

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 23
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4834        | 1.0   | 265  | 0.3768          | 0.8677   | 0.8677 | 0.8677    | 0.8677 |
| 0.3888        | 2.0   | 530  | 0.3437          | 0.8719   | 0.8719 | 0.8719    | 0.8719 |
| 0.3592        | 3.0   | 795  | 0.3512          | 0.8738   | 0.8738 | 0.8738    | 0.8738 |
| 0.3312        | 4.0   | 1060 | 0.3288          | 0.8677   | 0.8677 | 0.8677    | 0.8677 |
| 0.322         | 5.0   | 1325 | 0.3393          | 0.8677   | 0.8677 | 0.8677    | 0.8677 |
| 0.3052        | 6.0   | 1590 | 0.3245          | 0.8790   | 0.8790 | 0.8790    | 0.8790 |
| 0.2962        | 7.0   | 1855 | 0.3204          | 0.8752   | 0.8752 | 0.8752    | 0.8752 |
| 0.2834        | 8.0   | 2120 | 0.3324          | 0.8828   | 0.8828 | 0.8828    | 0.8828 |
| 0.2687        | 9.0   | 2385 | 0.3211          | 0.8743   | 0.8743 | 0.8743    | 0.8743 |
| 0.2647        | 10.0  | 2650 | 0.3453          | 0.8648   | 0.8648 | 0.8648    | 0.8648 |
| 0.2502        | 11.0  | 2915 | 0.3282          | 0.8743   | 0.8743 | 0.8743    | 0.8743 |
| 0.2441        | 12.0  | 3180 | 0.3430          | 0.8700   | 0.8700 | 0.8700    | 0.8700 |
| 0.2353        | 13.0  | 3445 | 0.3519          | 0.8767   | 0.8767 | 0.8767    | 0.8767 |
| 0.2286        | 14.0  | 3710 | 0.3481          | 0.8738   | 0.8738 | 0.8738    | 0.8738 |
| 0.2197        | 15.0  | 3975 | 0.3649          | 0.8771   | 0.8771 | 0.8771    | 0.8771 |
| 0.2191        | 16.0  | 4240 | 0.3608          | 0.8729   | 0.8729 | 0.8729    | 0.8729 |
| 0.2145        | 17.0  | 4505 | 0.3587          | 0.8724   | 0.8724 | 0.8724    | 0.8724 |
| 0.2075        | 18.0  | 4770 | 0.3577          | 0.8762   | 0.8762 | 0.8762    | 0.8762 |
| 0.2032        | 19.0  | 5035 | 0.3630          | 0.8724   | 0.8724 | 0.8724    | 0.8724 |
| 0.1975        | 20.0  | 5300 | 0.3636          | 0.8719   | 0.8719 | 0.8719    | 0.8719 |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3