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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/darebah6700 |
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base_model: microsoft/phi-2 |
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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/darebah6700 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8023 |
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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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| 1.2748 | 0.15 | 100 | 1.1349 | |
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| 1.1095 | 0.29 | 200 | 1.0077 | |
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| 1.0138 | 0.44 | 300 | 0.9587 | |
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| 0.9506 | 0.58 | 400 | 0.9188 | |
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| 0.9047 | 0.73 | 500 | 0.8906 | |
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| 0.9017 | 0.87 | 600 | 0.8722 | |
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| 0.8872 | 1.02 | 700 | 0.8660 | |
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| 0.8744 | 1.16 | 800 | 0.8501 | |
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| 0.8221 | 1.31 | 900 | 0.8472 | |
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| 0.8356 | 1.45 | 1000 | 0.8380 | |
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| 0.8335 | 1.6 | 1100 | 0.8317 | |
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| 0.828 | 1.75 | 1200 | 0.8273 | |
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| 0.8307 | 1.89 | 1300 | 0.8231 | |
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| 0.8147 | 2.04 | 1400 | 0.8185 | |
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| 0.8012 | 2.18 | 1500 | 0.8139 | |
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| 0.7885 | 2.33 | 1600 | 0.8129 | |
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| 0.7831 | 2.47 | 1700 | 0.8102 | |
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| 0.7787 | 2.62 | 1800 | 0.8148 | |
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| 0.7921 | 2.76 | 1900 | 0.8083 | |
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| 0.7777 | 2.91 | 2000 | 0.8073 | |
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| 0.7766 | 3.05 | 2100 | 0.8045 | |
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| 0.7658 | 3.2 | 2200 | 0.8056 | |
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| 0.7651 | 3.35 | 2300 | 0.8044 | |
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| 0.7844 | 3.49 | 2400 | 0.8023 | |
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| 0.7876 | 3.64 | 2500 | 0.8023 | |
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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 |
