---
license: apache-2.0
base_model: CAMeL-Lab/bert-base-arabic-camelbert-da
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Improved-CAMEL-attempt2
  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. -->

# Improved-CAMEL-attempt2

This model is a fine-tuned version of [CAMeL-Lab/bert-base-arabic-camelbert-da](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-da) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7469
- Accuracy: 0.86

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.07  | 50   | 0.3638          | 0.85     |
| No log        | 0.14  | 100  | 0.3945          | 0.79     |
| No log        | 0.21  | 150  | 0.3206          | 0.87     |
| No log        | 0.27  | 200  | 0.6859          | 0.64     |
| No log        | 0.34  | 250  | 0.3078          | 0.84     |
| No log        | 0.41  | 300  | 0.4524          | 0.79     |
| No log        | 0.48  | 350  | 0.3414          | 0.84     |
| No log        | 0.55  | 400  | 0.3479          | 0.85     |
| No log        | 0.62  | 450  | 0.3317          | 0.83     |
| 0.3497        | 0.68  | 500  | 0.3214          | 0.85     |
| 0.3497        | 0.75  | 550  | 0.2614          | 0.87     |
| 0.3497        | 0.82  | 600  | 0.4143          | 0.84     |
| 0.3497        | 0.89  | 650  | 0.3211          | 0.88     |
| 0.3497        | 0.96  | 700  | 0.2593          | 0.89     |
| 0.3497        | 1.03  | 750  | 0.7586          | 0.77     |
| 0.3497        | 1.1   | 800  | 0.3171          | 0.91     |
| 0.3497        | 1.16  | 850  | 0.5458          | 0.84     |
| 0.3497        | 1.23  | 900  | 0.7450          | 0.83     |
| 0.3497        | 1.3   | 950  | 0.2748          | 0.86     |
| 0.2194        | 1.37  | 1000 | 0.5666          | 0.81     |
| 0.2194        | 1.44  | 1050 | 0.9014          | 0.82     |
| 0.2194        | 1.51  | 1100 | 0.4580          | 0.86     |
| 0.2194        | 1.58  | 1150 | 0.4560          | 0.87     |
| 0.2194        | 1.64  | 1200 | 0.2445          | 0.9      |
| 0.2194        | 1.71  | 1250 | 0.4808          | 0.87     |
| 0.2194        | 1.78  | 1300 | 0.5491          | 0.86     |
| 0.2194        | 1.85  | 1350 | 0.3435          | 0.87     |
| 0.2194        | 1.92  | 1400 | 0.4169          | 0.87     |
| 0.2194        | 1.99  | 1450 | 0.4190          | 0.86     |
| 0.1739        | 2.05  | 1500 | 0.6567          | 0.87     |
| 0.1739        | 2.12  | 1550 | 0.9203          | 0.84     |
| 0.1739        | 2.19  | 1600 | 0.6931          | 0.85     |
| 0.1739        | 2.26  | 1650 | 0.8531          | 0.83     |
| 0.1739        | 2.33  | 1700 | 0.6863          | 0.87     |
| 0.1739        | 2.4   | 1750 | 0.7469          | 0.86     |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1