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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: V0316MP1 |
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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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# V0316MP1 |
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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: 1.5025 |
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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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| 2.4218 | 0.09 | 10 | 2.3701 | |
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| 2.3588 | 0.17 | 20 | 2.3216 | |
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| 2.2547 | 0.26 | 30 | 2.2504 | |
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| 2.0897 | 0.34 | 40 | 2.1789 | |
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| 1.9766 | 0.43 | 50 | 2.1106 | |
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| 1.8207 | 0.51 | 60 | 2.0495 | |
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| 1.7309 | 0.6 | 70 | 2.0001 | |
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| 1.666 | 0.68 | 80 | 1.9488 | |
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| 1.5586 | 0.77 | 90 | 1.9120 | |
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| 1.4977 | 0.85 | 100 | 1.8712 | |
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| 1.422 | 0.94 | 110 | 1.8324 | |
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| 1.3569 | 1.02 | 120 | 1.7940 | |
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| 1.2811 | 1.11 | 130 | 1.7640 | |
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| 1.2312 | 1.19 | 140 | 1.7329 | |
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| 1.1463 | 1.28 | 150 | 1.7065 | |
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| 1.1087 | 1.37 | 160 | 1.6802 | |
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| 1.0139 | 1.45 | 170 | 1.6581 | |
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| 0.968 | 1.54 | 180 | 1.6377 | |
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| 0.9078 | 1.62 | 190 | 1.6183 | |
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| 0.871 | 1.71 | 200 | 1.6013 | |
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| 0.8252 | 1.79 | 210 | 1.5863 | |
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| 0.7983 | 1.88 | 220 | 1.5675 | |
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| 0.7561 | 1.96 | 230 | 1.5566 | |
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| 0.7413 | 2.05 | 240 | 1.5443 | |
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| 0.7156 | 2.13 | 250 | 1.5348 | |
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| 0.701 | 2.22 | 260 | 1.5243 | |
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| 0.673 | 2.3 | 270 | 1.5174 | |
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| 0.6627 | 2.39 | 280 | 1.5126 | |
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| 0.648 | 2.47 | 290 | 1.5119 | |
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| 0.6553 | 2.56 | 300 | 1.5088 | |
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| 0.6447 | 2.65 | 310 | 1.5051 | |
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| 0.6227 | 2.73 | 320 | 1.5045 | |
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| 0.6338 | 2.82 | 330 | 1.5023 | |
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| 0.6224 | 2.9 | 340 | 1.5017 | |
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| 0.6115 | 2.99 | 350 | 1.5025 | |
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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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