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--- |
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library_name: transformers |
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base_model: malmarjeh/mbert2mbert-arabic-text-summarization |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: resultmbert2mbert |
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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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# resultmbert2mbert |
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This model is a fine-tuned version of [malmarjeh/mbert2mbert-arabic-text-summarization](https://huggingface.co/malmarjeh/mbert2mbert-arabic-text-summarization) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8701 |
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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: 5e-05 |
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- train_batch_size: 32 |
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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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- lr_scheduler_warmup_steps: 500 |
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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 | |
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|:-------------:|:------:|:-----:|:---------------:| |
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| 2.551 | 0.4263 | 500 | 1.0592 | |
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| 1.1939 | 0.8525 | 1000 | 0.9787 | |
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| 1.0979 | 1.2788 | 1500 | 0.9425 | |
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| 1.0436 | 1.7050 | 2000 | 0.9134 | |
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| 1.0132 | 2.1313 | 2500 | 0.9038 | |
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| 0.9645 | 2.5575 | 3000 | 0.8905 | |
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| 0.9608 | 2.9838 | 3500 | 0.8857 | |
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| 0.9526 | 3.4101 | 4000 | 0.8931 | |
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| 0.96 | 3.8363 | 4500 | 0.8838 | |
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| 0.9254 | 4.2626 | 5000 | 0.8804 | |
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| 0.9023 | 4.6888 | 5500 | 0.8724 | |
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| 0.884 | 5.1151 | 6000 | 0.8754 | |
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| 0.8496 | 5.5413 | 6500 | 0.8656 | |
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| 0.85 | 5.9676 | 7000 | 0.8653 | |
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| 0.8076 | 6.3939 | 7500 | 0.8668 | |
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| 0.8119 | 6.8201 | 8000 | 0.8655 | |
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| 0.7953 | 7.2464 | 8500 | 0.8676 | |
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| 0.7719 | 7.6726 | 9000 | 0.8656 | |
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| 0.7657 | 8.0989 | 9500 | 0.8710 | |
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| 0.7446 | 8.5251 | 10000 | 0.8694 | |
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| 0.7524 | 8.9514 | 10500 | 0.8658 | |
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| 0.729 | 9.3777 | 11000 | 0.8699 | |
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| 0.7338 | 9.8039 | 11500 | 0.8701 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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