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--- |
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license: mit |
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base_model: microsoft/phi-2 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: V0309O6 |
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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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# V0309O6 |
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This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0631 |
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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: 0.0003 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 32 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine_with_restarts |
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- lr_scheduler_warmup_steps: 20 |
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- num_epochs: 3 |
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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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| 1.9549 | 0.09 | 10 | 0.7661 | |
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| 0.3073 | 0.17 | 20 | 0.1105 | |
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| 0.1318 | 0.26 | 30 | 0.0849 | |
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| 0.1149 | 0.34 | 40 | 0.0834 | |
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| 0.1155 | 0.43 | 50 | 0.0803 | |
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| 0.1048 | 0.51 | 60 | 0.0807 | |
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| 0.0963 | 0.6 | 70 | 0.0808 | |
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| 0.0992 | 0.68 | 80 | 0.0777 | |
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| 0.0893 | 0.77 | 90 | 0.0731 | |
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| 0.1061 | 0.85 | 100 | 0.0747 | |
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| 0.098 | 0.94 | 110 | 0.0711 | |
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| 0.095 | 1.02 | 120 | 0.0699 | |
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| 0.0908 | 1.11 | 130 | 0.0743 | |
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| 0.0874 | 1.19 | 140 | 0.0734 | |
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| 0.083 | 1.28 | 150 | 0.0682 | |
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| 0.0823 | 1.37 | 160 | 0.0701 | |
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| 0.0812 | 1.45 | 170 | 0.0684 | |
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| 0.078 | 1.54 | 180 | 0.0683 | |
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| 0.0763 | 1.62 | 190 | 0.0671 | |
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| 0.0763 | 1.71 | 200 | 0.0650 | |
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| 0.08 | 1.79 | 210 | 0.0634 | |
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| 0.0686 | 1.88 | 220 | 0.0650 | |
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| 0.0685 | 1.96 | 230 | 0.0638 | |
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| 0.074 | 2.05 | 240 | 0.0644 | |
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| 0.0646 | 2.13 | 250 | 0.0630 | |
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| 0.0669 | 2.22 | 260 | 0.0675 | |
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| 0.061 | 2.3 | 270 | 0.0675 | |
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| 0.0672 | 2.39 | 280 | 0.0635 | |
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| 0.0687 | 2.47 | 290 | 0.0625 | |
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| 0.0656 | 2.56 | 300 | 0.0625 | |
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| 0.0738 | 2.65 | 310 | 0.0626 | |
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| 0.062 | 2.73 | 320 | 0.0628 | |
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| 0.0622 | 2.82 | 330 | 0.0631 | |
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| 0.0632 | 2.9 | 340 | 0.0630 | |
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| 0.0644 | 2.99 | 350 | 0.0631 | |
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### Framework versions |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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