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Litzy619
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PHI30515HMA2H

Safetensors
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Litzy619 commited on
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Files changed (4) hide show
  1. README.md +34 -34
  2. adapter_model.bin +1 -1
  3. model.safetensors +1 -1
  4. training_args.bin +1 -1
README.md CHANGED
@@ -15,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.0706
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  ## Model description
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@@ -50,39 +50,39 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 7.1779 | 0.09 | 10 | 2.1285 |
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- | 1.3773 | 0.18 | 20 | 0.3216 |
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- | 0.3479 | 0.27 | 30 | 0.2281 |
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- | 0.9413 | 0.36 | 40 | 0.3169 |
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- | 0.2771 | 0.45 | 50 | 0.1485 |
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- | 0.332 | 0.54 | 60 | 0.1472 |
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- | 0.2391 | 0.63 | 70 | 0.1359 |
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- | 0.1792 | 0.73 | 80 | 0.1238 |
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- | 0.1223 | 0.82 | 90 | 0.1178 |
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- | 0.1279 | 0.91 | 100 | 0.0860 |
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- | 0.109 | 1.0 | 110 | 0.0776 |
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- | 0.0986 | 1.09 | 120 | 0.0769 |
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- | 0.0989 | 1.18 | 130 | 0.0739 |
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- | 0.117 | 1.27 | 140 | 0.0712 |
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- | 0.1134 | 1.36 | 150 | 0.0686 |
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- | 0.0768 | 1.45 | 160 | 0.0661 |
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- | 0.0932 | 1.54 | 170 | 0.1176 |
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- | 0.0865 | 1.63 | 180 | 0.0759 |
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- | 0.0974 | 1.72 | 190 | 0.0680 |
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- | 0.0831 | 1.81 | 200 | 0.0715 |
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- | 0.0732 | 1.9 | 210 | 0.1637 |
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- | 0.0756 | 1.99 | 220 | 0.0676 |
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- | 0.0457 | 2.08 | 230 | 0.0696 |
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- | 0.0551 | 2.18 | 240 | 0.0779 |
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- | 0.0391 | 2.27 | 250 | 0.0772 |
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- | 0.0401 | 2.36 | 260 | 0.0749 |
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- | 0.0448 | 2.45 | 270 | 0.0707 |
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- | 0.0422 | 2.54 | 280 | 0.0731 |
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- | 0.037 | 2.63 | 290 | 0.0732 |
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- | 0.039 | 2.72 | 300 | 0.0727 |
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- | 0.0465 | 2.81 | 310 | 0.0718 |
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- | 0.051 | 2.9 | 320 | 0.0707 |
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- | 0.0416 | 2.99 | 330 | 0.0706 |
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  ### Framework versions
 
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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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  | 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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