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--- |
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license: mit |
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base_model: microsoft/Phi-3-mini-4k-instruct |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: PHI30515HMA2H |
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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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# PHI30515HMA2H |
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This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0643 |
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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: 80 |
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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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| 7.2249 | 0.09 | 10 | 2.2001 | |
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| 1.4719 | 0.18 | 20 | 0.3359 | |
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| 0.3692 | 0.27 | 30 | 0.2930 | |
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| 0.7802 | 0.36 | 40 | 0.2417 | |
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| 0.3078 | 0.45 | 50 | 0.2185 | |
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| 0.4702 | 0.54 | 60 | 0.2195 | |
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| 0.272 | 0.63 | 70 | 0.1992 | |
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| 0.2656 | 0.73 | 80 | 0.1711 | |
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| 0.1386 | 0.82 | 90 | 0.1117 | |
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| 0.2291 | 0.91 | 100 | 0.1116 | |
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| 0.1424 | 1.0 | 110 | 0.0853 | |
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| 0.099 | 1.09 | 120 | 0.1146 | |
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| 0.1629 | 1.18 | 130 | 0.1753 | |
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| 0.6955 | 1.27 | 140 | 0.1667 | |
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| 0.226 | 1.36 | 150 | 0.1119 | |
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| 0.1085 | 1.45 | 160 | 0.0805 | |
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| 0.1083 | 1.54 | 170 | 0.0743 | |
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| 0.2197 | 1.63 | 180 | 0.9735 | |
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| 0.4915 | 1.72 | 190 | 0.0757 | |
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| 0.0954 | 1.81 | 200 | 0.0794 | |
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| 0.0696 | 1.9 | 210 | 0.0698 | |
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| 0.068 | 1.99 | 220 | 0.0711 | |
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| 0.0602 | 2.08 | 230 | 0.0702 | |
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| 0.0896 | 2.18 | 240 | 0.0871 | |
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| 0.0724 | 2.27 | 250 | 0.0720 | |
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| 0.0679 | 2.36 | 260 | 0.0688 | |
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| 0.0764 | 2.45 | 270 | 0.0683 | |
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| 0.0642 | 2.54 | 280 | 0.0665 | |
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| 0.058 | 2.63 | 290 | 0.0659 | |
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| 0.0554 | 2.72 | 300 | 0.0665 | |
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| 0.0699 | 2.81 | 310 | 0.0654 | |
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| 0.0752 | 2.9 | 320 | 0.0645 | |
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| 0.0654 | 2.99 | 330 | 0.0643 | |
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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 0.14.0 |
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