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Litzy619
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V0305P1

Safetensors
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End of training

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  1. README.md +36 -36
  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 [yahma/llama-7b-hf](https://huggingface.co/yahma/llama-7b-hf) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0720
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  ## Model description
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@@ -50,41 +50,41 @@ 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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- | 1.3057 | 0.09 | 10 | 0.1620 |
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- | 0.1718 | 0.17 | 20 | 0.1555 |
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- | 0.1562 | 0.26 | 30 | 0.1535 |
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- | 0.1527 | 0.34 | 40 | 0.1479 |
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- | 0.1503 | 0.43 | 50 | 0.1505 |
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- | 0.1563 | 0.51 | 60 | 0.1505 |
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- | 0.1516 | 0.6 | 70 | 0.1504 |
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- | 0.1532 | 0.68 | 80 | 0.1483 |
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- | 0.149 | 0.77 | 90 | 0.1489 |
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- | 0.1522 | 0.85 | 100 | 0.1469 |
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- | 0.1515 | 0.94 | 110 | 0.1405 |
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- | 0.1372 | 1.02 | 120 | 0.1187 |
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- | 0.1257 | 1.11 | 130 | 0.1202 |
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- | 0.1133 | 1.19 | 140 | 0.1077 |
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- | 0.1099 | 1.28 | 150 | 0.0913 |
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- | 0.1033 | 1.37 | 160 | 0.0962 |
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- | 0.1027 | 1.45 | 170 | 0.0953 |
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- | 0.0909 | 1.54 | 180 | 0.0905 |
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- | 0.0926 | 1.62 | 190 | 0.0866 |
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- | 0.0948 | 1.71 | 200 | 0.0847 |
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- | 0.0949 | 1.79 | 210 | 0.0800 |
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- | 0.0877 | 1.88 | 220 | 0.0753 |
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- | 0.0858 | 1.96 | 230 | 0.0804 |
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- | 0.0711 | 2.05 | 240 | 0.0815 |
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- | 0.0597 | 2.13 | 250 | 0.0808 |
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- | 0.0598 | 2.22 | 260 | 0.0755 |
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- | 0.0586 | 2.3 | 270 | 0.0843 |
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- | 0.0609 | 2.39 | 280 | 0.0748 |
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- | 0.0648 | 2.47 | 290 | 0.0727 |
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- | 0.0622 | 2.56 | 300 | 0.0727 |
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- | 0.0652 | 2.65 | 310 | 0.0715 |
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- | 0.058 | 2.73 | 320 | 0.0711 |
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- | 0.0581 | 2.82 | 330 | 0.0717 |
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- | 0.0579 | 2.9 | 340 | 0.0720 |
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- | 0.0583 | 2.99 | 350 | 0.0720 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [yahma/llama-7b-hf](https://huggingface.co/yahma/llama-7b-hf) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0697
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 1.0736 | 0.09 | 10 | 0.1558 |
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+ | 0.1607 | 0.17 | 20 | 0.1576 |
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+ | 0.1576 | 0.26 | 30 | 0.1518 |
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+ | 0.1522 | 0.34 | 40 | 0.1504 |
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+ | 0.1506 | 0.43 | 50 | 0.1494 |
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+ | 0.1561 | 0.51 | 60 | 0.1507 |
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+ | 0.1516 | 0.6 | 70 | 0.1495 |
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+ | 0.1528 | 0.68 | 80 | 0.1480 |
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+ | 0.1481 | 0.77 | 90 | 0.1435 |
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+ | 0.1513 | 0.85 | 100 | 0.1445 |
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+ | 0.1463 | 0.94 | 110 | 0.1142 |
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+ | 0.1277 | 1.02 | 120 | 0.1126 |
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+ | 0.119 | 1.11 | 130 | 0.1112 |
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+ | 0.1092 | 1.19 | 140 | 0.0969 |
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+ | 0.1113 | 1.28 | 150 | 0.0965 |
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+ | 0.1033 | 1.37 | 160 | 0.0991 |
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+ | 0.1025 | 1.45 | 170 | 0.0881 |
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+ | 0.0922 | 1.54 | 180 | 0.0878 |
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+ | 0.0931 | 1.62 | 190 | 0.0811 |
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+ | 0.0909 | 1.71 | 200 | 0.0786 |
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+ | 0.087 | 1.79 | 210 | 0.0755 |
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+ | 0.0868 | 1.88 | 220 | 0.0745 |
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+ | 0.0825 | 1.96 | 230 | 0.0832 |
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+ | 0.0636 | 2.05 | 240 | 0.0820 |
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+ | 0.0504 | 2.13 | 250 | 0.0864 |
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+ | 0.0463 | 2.22 | 260 | 0.0876 |
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+ | 0.0449 | 2.3 | 270 | 0.0847 |
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+ | 0.0529 | 2.39 | 280 | 0.0711 |
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+ | 0.0489 | 2.47 | 290 | 0.0693 |
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+ | 0.05 | 2.56 | 300 | 0.0699 |
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+ | 0.0519 | 2.65 | 310 | 0.0686 |
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+ | 0.0411 | 2.73 | 320 | 0.0688 |
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+ | 0.0473 | 2.82 | 330 | 0.0695 |
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+ | 0.0471 | 2.9 | 340 | 0.0697 |
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+ | 0.0452 | 2.99 | 350 | 0.0697 |
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  ### Framework versions
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