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--- |
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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: M12-BERT-SIMILIARITY |
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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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# M12-BERT-SIMILIARITY |
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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: 0.2225 |
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- Accuracy: 0.9344 |
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- Precision: 0.8927 |
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- Recall: 0.9873 |
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- F1: 0.9377 |
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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: 16 |
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- eval_batch_size: 16 |
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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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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:------:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.2303 | 1.0 | 49975 | 0.2080 | 0.9372 | 0.9036 | 0.9787 | 0.9397 | |
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| 0.2109 | 2.0 | 99950 | 0.2342 | 0.9337 | 0.8952 | 0.9825 | 0.9368 | |
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| 0.203 | 3.0 | 149925 | 0.2192 | 0.9375 | 0.9070 | 0.9749 | 0.9397 | |
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| 0.1962 | 4.0 | 199900 | 0.2225 | 0.9344 | 0.8927 | 0.9873 | 0.9377 | |
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### Framework versions |
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- Transformers 4.21.3 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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