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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: bert-base-arabertv2_1
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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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# bert-base-arabertv2_1
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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: 2.6799
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- Accuracy: 0.636
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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: 8
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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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- lr_scheduler_warmup_steps: 500
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- training_steps: 5000
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- mixed_precision_training: Native AMP
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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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| 0.6125 | 4.57 | 1000 | 0.8943 | 0.65 |
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| 0.1438 | 9.13 | 2000 | 1.4417 | 0.622 |
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| 0.0537 | 13.7 | 3000 | 2.1144 | 0.62 |
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| 0.0346 | 18.26 | 4000 | 2.5203 | 0.643 |
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| 0.0013 | 22.83 | 5000 | 2.6799 | 0.636 |
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### Framework versions
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- Transformers 4.38.0.dev0
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- Pytorch 2.1.0+cu121
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- Datasets 2.16.1
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- Tokenizers 0.15.1
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model.safetensors
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runs/Feb03_14-18-09_d83aeab94bd9/events.out.tfevents.1706969893.d83aeab94bd9.14705.0
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