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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: arabic-dialect-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. -->
# arabic-dialect-model
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: 2.7129
- Accuracy: 0.1778
- F1: 0.1297
- Precision: 0.1777
- Recall: 0.1778
## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 3.0984 | 1.0 | 16 | 3.0297 | 0.0444 | 0.05 | 0.0593 | 0.0444 |
| 2.9882 | 2.0 | 32 | 2.9796 | 0.0889 | 0.0660 | 0.0526 | 0.0889 |
| 2.904 | 3.0 | 48 | 2.9029 | 0.1111 | 0.0577 | 0.0399 | 0.1111 |
| 2.7871 | 4.0 | 64 | 2.8040 | 0.1778 | 0.1057 | 0.1370 | 0.1778 |
| 2.6578 | 5.0 | 80 | 2.7129 | 0.1778 | 0.1297 | 0.1777 | 0.1778 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cpu
- Datasets 2.13.0
- Tokenizers 0.13.3
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