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--- |
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language: |
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- ar |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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datasets: |
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- dalyaa/darebah2400 |
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base_model: dalyaff/phi2-QA-Arabic-phi |
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model-index: |
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- name: phi-2 |
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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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# phi-2 |
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This model is a fine-tuned version of [microsoftl](https://huggingface.co/microsoftl) on the dalyaa/darebah2400 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8341 |
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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: 2.5e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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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: 5 |
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- training_steps: 2500 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.0567 | 0.4 | 100 | 1.0257 | |
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| 0.9463 | 0.8 | 200 | 0.9571 | |
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| 0.8397 | 1.2 | 300 | 0.9297 | |
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| 0.7876 | 1.6 | 400 | 0.9042 | |
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| 0.7484 | 2.0 | 500 | 0.8973 | |
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| 0.7301 | 2.4 | 600 | 0.8804 | |
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| 0.7023 | 2.8 | 700 | 0.8712 | |
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| 0.6604 | 3.2 | 800 | 0.8652 | |
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| 0.6727 | 3.6 | 900 | 0.8578 | |
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| 0.6542 | 4.0 | 1000 | 0.8549 | |
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| 0.6474 | 4.4 | 1100 | 0.8533 | |
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| 0.6208 | 4.8 | 1200 | 0.8503 | |
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| 0.6022 | 5.2 | 1300 | 0.8429 | |
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| 0.5997 | 5.6 | 1400 | 0.8488 | |
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| 0.6399 | 6.0 | 1500 | 0.8389 | |
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| 0.6273 | 6.4 | 1600 | 0.8410 | |
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| 0.5854 | 6.8 | 1700 | 0.8422 | |
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| 0.6062 | 7.2 | 1800 | 0.8360 | |
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| 0.5958 | 7.6 | 1900 | 0.8363 | |
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| 0.5933 | 8.0 | 2000 | 0.8403 | |
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| 0.5905 | 8.4 | 2100 | 0.8388 | |
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| 0.5604 | 8.8 | 2200 | 0.8366 | |
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| 0.572 | 9.2 | 2300 | 0.8349 | |
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| 0.5764 | 9.6 | 2400 | 0.8365 | |
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| 0.5926 | 10.0 | 2500 | 0.8341 | |
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### Framework versions |
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- PEFT 0.8.2 |
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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 |