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

# unfortified_camel

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 the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3917
- Accuracy: 0.88

## 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        | 0.0546 | 50   | 0.5498          | 0.75     |
| No log        | 0.1092 | 100  | 0.5089          | 0.82     |
| No log        | 0.1638 | 150  | 0.4593          | 0.79     |
| No log        | 0.2183 | 200  | 0.3678          | 0.85     |
| No log        | 0.2729 | 250  | 0.4435          | 0.85     |
| No log        | 0.3275 | 300  | 0.3393          | 0.88     |
| No log        | 0.3821 | 350  | 0.3425          | 0.88     |
| No log        | 0.4367 | 400  | 0.3758          | 0.82     |
| No log        | 0.4913 | 450  | 0.4545          | 0.87     |
| 0.3339        | 0.5459 | 500  | 0.4324          | 0.87     |
| 0.3339        | 0.6004 | 550  | 0.3225          | 0.87     |
| 0.3339        | 0.6550 | 600  | 0.3307          | 0.89     |
| 0.3339        | 0.7096 | 650  | 0.2996          | 0.9      |
| 0.3339        | 0.7642 | 700  | 0.3002          | 0.89     |
| 0.3339        | 0.8188 | 750  | 0.3749          | 0.89     |
| 0.3339        | 0.8734 | 800  | 0.3242          | 0.89     |
| 0.3339        | 0.9279 | 850  | 0.2887          | 0.91     |
| 0.3339        | 0.9825 | 900  | 0.3507          | 0.87     |
| 0.3339        | 1.0371 | 950  | 0.3718          | 0.91     |
| 0.2461        | 1.0917 | 1000 | 0.3833          | 0.91     |
| 0.2461        | 1.1463 | 1050 | 0.3840          | 0.89     |
| 0.2461        | 1.2009 | 1100 | 0.3659          | 0.88     |
| 0.2461        | 1.2555 | 1150 | 0.3298          | 0.91     |
| 0.2461        | 1.3100 | 1200 | 0.3691          | 0.91     |
| 0.2461        | 1.3646 | 1250 | 0.3917          | 0.88     |


### Framework versions

- Transformers 4.42.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1