End of training
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README.md
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---
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base_model: aubmindlab/bert-base-arabertv2
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: finetunning
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# finetunning
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This model is a fine-tuned version of [aubmindlab/bert-base-arabertv2](https://huggingface.co/aubmindlab/bert-base-arabertv2) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3308
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- Accuracy: 0.9494
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|
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| 0.2049 | 1.0 | 1250 | 0.1725 | 0.9478 |
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| 0.1392 | 2.0 | 2500 | 0.1712 | 0.9456 |
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| 0.0982 | 3.0 | 3750 | 0.1812 | 0.9476 |
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| 0.0769 | 4.0 | 5000 | 0.2262 | 0.9472 |
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| 0.0454 | 5.0 | 6250 | 0.2438 | 0.9504 |
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| 0.0364 | 6.0 | 7500 | 0.2611 | 0.9496 |
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| 0.0235 | 7.0 | 8750 | 0.3145 | 0.9476 |
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| 0.015 | 8.0 | 10000 | 0.3103 | 0.9494 |
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| 0.0131 | 9.0 | 11250 | 0.3279 | 0.9492 |
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| 0.0082 | 10.0 | 12500 | 0.3308 | 0.9494 |
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### Framework versions
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- Transformers 4.39.3
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- Pytorch 2.1.2
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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model.safetensors
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runs/May18_21-12-36_bfb1e88450c7/events.out.tfevents.1716066757.bfb1e88450c7.26.0
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