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tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: fine_tuned_mix40k_arabert_cleaned
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. -->
# fine_tuned_mix40k_arabert_cleaned
This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3804
- Accuracy: 0.8933
- Precision: 0.9219
- Recall: 0.8580
- F1: 0.8888
## 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
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.3113 | 1.0 | 10794 | 0.2831 | 0.8782 | 0.8802 | 0.8739 | 0.8770 |
| 0.2268 | 2.0 | 21588 | 0.2901 | 0.8861 | 0.9270 | 0.8369 | 0.8796 |
| 0.1788 | 3.0 | 32382 | 0.3294 | 0.8901 | 0.9086 | 0.8660 | 0.8868 |
| 0.1413 | 4.0 | 43176 | 0.3804 | 0.8933 | 0.9219 | 0.8580 | 0.8888 |
### Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
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