End of training
Browse files
README.md
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This model is a fine-tuned version of [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf) on the None dataset.
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It achieves the following results on the evaluation set:
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-
- Loss: 0.
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## Model description
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@@ -44,260 +44,211 @@ The following hyperparameters were used during training:
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.03
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- num_epochs:
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:-----:|:---------------:|
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| 0.0929 | 4.46 | 19950 | 0.2994 |
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| 0.0946 | 4.47 | 20000 | 0.2975 |
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| 0.0943 | 4.48 | 20050 | 0.2983 |
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| 0.0951 | 4.49 | 20100 | 0.3004 |
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| 0.0926 | 4.5 | 20150 | 0.2993 |
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| 0.0917 | 4.51 | 20200 | 0.2995 |
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| 0.0984 | 4.52 | 20250 | 0.2977 |
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| 0.0944 | 4.53 | 20300 | 0.2959 |
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| 0.0884 | 4.55 | 20350 | 0.2966 |
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| 0.0883 | 4.56 | 20400 | 0.2986 |
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| 0.0901 | 4.57 | 20450 | 0.2977 |
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| 0.0932 | 4.58 | 20500 | 0.2975 |
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| 0.0946 | 4.59 | 20550 | 0.2992 |
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| 0.0937 | 4.6 | 20600 | 0.2975 |
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| 0.0912 | 4.61 | 20650 | 0.2997 |
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| 0.0919 | 4.62 | 20700 | 0.2991 |
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| 0.0984 | 4.63 | 20750 | 0.2983 |
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| 0.0866 | 4.65 | 20800 | 0.2978 |
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| 0.0977 | 4.66 | 20850 | 0.2983 |
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| 0.0966 | 4.67 | 20900 | 0.2976 |
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| 0.0866 | 4.68 | 20950 | 0.2982 |
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| 0.0926 | 4.69 | 21000 | 0.2999 |
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| 0.0935 | 4.7 | 21050 | 0.2978 |
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| 0.0987 | 4.71 | 21100 | 0.2982 |
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| 0.0867 | 4.72 | 21150 | 0.2985 |
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| 0.085 | 4.74 | 21200 | 0.2992 |
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| 0.0859 | 4.75 | 21250 | 0.2989 |
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| 0.0873 | 4.76 | 21300 | 0.2996 |
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| 0.093 | 4.77 | 21350 | 0.2984 |
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| 0.0873 | 4.78 | 21400 | 0.2989 |
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| 0.0911 | 4.79 | 21450 | 0.2983 |
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| 0.0873 | 4.8 | 21500 | 0.2987 |
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| 0.0935 | 4.81 | 21550 | 0.2993 |
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| 0.0862 | 4.82 | 21600 | 0.2993 |
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| 0.093 | 4.84 | 21650 | 0.2985 |
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| 0.0877 | 4.85 | 21700 | 0.2984 |
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| 0.0808 | 4.86 | 21750 | 0.2979 |
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| 0.0892 | 4.87 | 21800 | 0.2984 |
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| 0.0855 | 4.88 | 21850 | 0.2981 |
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| 0.0866 | 4.89 | 21900 | 0.2988 |
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| 0.0837 | 4.9 | 21950 | 0.2989 |
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| 0.0917 | 4.91 | 22000 | 0.2989 |
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| 0.0818 | 4.93 | 22050 | 0.2994 |
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| 0.0985 | 4.94 | 22100 | 0.2994 |
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| 0.093 | 4.95 | 22150 | 0.2991 |
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| 0.0874 | 4.96 | 22200 | 0.2989 |
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| 0.0856 | 4.97 | 22250 | 0.2990 |
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| 0.0972 | 4.98 | 22300 | 0.2991 |
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| 0.0892 | 4.99 | 22350 | 0.2990 |
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### Framework versions
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This model is a fine-tuned version of [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf) on the None dataset.
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It achieves the following results on the evaluation set:
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+
- Loss: 0.2781
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## Model description
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.03
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+
- num_epochs: 4
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:-----:|:---------------:|
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| 0.2411 | 1.79 | 8000 | 0.2641 |
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| 0.2531 | 1.8 | 8050 | 0.2630 |
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| 0.2648 | 1.81 | 8100 | 0.2649 |
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| 0.243 | 1.82 | 8150 | 0.2639 |
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| 0.236 | 1.83 | 8200 | 0.2633 |
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| 0.2836 | 1.84 | 8250 | 0.2635 |
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| 0.2512 | 1.85 | 8300 | 0.2616 |
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| 0.2416 | 1.87 | 8350 | 0.2609 |
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| 0.2565 | 1.88 | 8400 | 0.2608 |
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| 0.2646 | 1.89 | 8450 | 0.2612 |
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| 0.2292 | 1.9 | 8500 | 0.2614 |
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| 0.2697 | 1.91 | 8550 | 0.2620 |
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| 0.2509 | 1.92 | 8600 | 0.2607 |
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| 0.2541 | 1.93 | 8650 | 0.2588 |
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| 0.261 | 1.94 | 8700 | 0.2585 |
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| 0.2653 | 1.95 | 8750 | 0.2565 |
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| 0.2161 | 1.97 | 8800 | 0.2574 |
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| 0.2283 | 1.98 | 8850 | 0.2568 |
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| 0.2355 | 1.99 | 8900 | 0.2571 |
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| 0.2255 | 2.0 | 8950 | 0.2564 |
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| 0.1783 | 2.01 | 9000 | 0.2682 |
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| 0.1631 | 2.02 | 9050 | 0.2701 |
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| 0.1741 | 2.03 | 9100 | 0.2702 |
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| 0.1785 | 2.04 | 9150 | 0.2695 |
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| 0.1796 | 2.05 | 9200 | 0.2682 |
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| 0.1858 | 2.07 | 9250 | 0.2735 |
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| 0.197 | 2.08 | 9300 | 0.2744 |
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| 0.1838 | 2.09 | 9350 | 0.2704 |
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| 0.1812 | 2.1 | 9400 | 0.2701 |
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| 0.1771 | 2.11 | 9450 | 0.2687 |
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| 0.1877 | 2.12 | 9500 | 0.2690 |
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| 0.1713 | 2.13 | 9550 | 0.2709 |
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| 0.2012 | 2.14 | 9600 | 0.2696 |
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| 0.1886 | 2.16 | 9650 | 0.2668 |
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| 0.1803 | 2.17 | 9700 | 0.2695 |
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| 0.1736 | 2.18 | 9750 | 0.2691 |
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| 0.172 | 2.19 | 9800 | 0.2699 |
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| 0.1847 | 2.2 | 9850 | 0.2713 |
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| 0.1813 | 2.21 | 9900 | 0.2675 |
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| 0.162 | 2.22 | 9950 | 0.2681 |
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| 0.1759 | 2.23 | 10000 | 0.2688 |
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| 0.1785 | 2.24 | 10050 | 0.2675 |
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| 0.1794 | 2.26 | 10100 | 0.2690 |
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| 0.1724 | 2.27 | 10150 | 0.2687 |
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| 0.179 | 2.28 | 10200 | 0.2674 |
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| 0.1839 | 2.29 | 10250 | 0.2646 |
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| 0.1654 | 2.3 | 10300 | 0.2689 |
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| 0.1845 | 2.31 | 10350 | 0.2671 |
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| 0.1632 | 2.32 | 10400 | 0.2693 |
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| 0.1679 | 2.33 | 10450 | 0.2702 |
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| 0.1676 | 2.35 | 10500 | 0.2680 |
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| 0.1747 | 2.36 | 10550 | 0.2698 |
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| 0.1702 | 2.37 | 10600 | 0.2656 |
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| 0.1706 | 2.38 | 10650 | 0.2678 |
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| 0.1535 | 2.39 | 10700 | 0.2666 |
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| 0.162 | 2.4 | 10750 | 0.2640 |
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| 0.1557 | 2.41 | 10800 | 0.2664 |
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| 0.1729 | 2.42 | 10850 | 0.2658 |
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| 0.1778 | 2.43 | 10900 | 0.2672 |
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| 0.1815 | 2.45 | 10950 | 0.2651 |
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| 0.1898 | 2.46 | 11000 | 0.2637 |
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| 0.2043 | 2.47 | 11050 | 0.2636 |
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| 0.171 | 2.48 | 11100 | 0.2647 |
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| 0.1747 | 2.49 | 11150 | 0.2619 |
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| 0.1767 | 2.5 | 11200 | 0.2615 |
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| 0.192 | 2.51 | 11250 | 0.2626 |
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| 0.1636 | 2.52 | 11300 | 0.2638 |
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| 0.1823 | 2.54 | 11350 | 0.2649 |
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| 0.1913 | 2.55 | 11400 | 0.2608 |
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| 0.1719 | 2.56 | 11450 | 0.2628 |
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| 0.1721 | 2.57 | 11500 | 0.2624 |
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| 0.1721 | 2.58 | 11550 | 0.2638 |
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| 0.1788 | 2.59 | 11600 | 0.2617 |
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| 126 |
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| 0.1837 | 2.6 | 11650 | 0.2615 |
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| 127 |
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| 0.1857 | 2.61 | 11700 | 0.2606 |
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| 128 |
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| 0.158 | 2.62 | 11750 | 0.2640 |
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| 129 |
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| 0.1593 | 2.64 | 11800 | 0.2612 |
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| 130 |
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| 0.1738 | 2.65 | 11850 | 0.2606 |
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| 0.1767 | 2.66 | 11900 | 0.2604 |
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| 132 |
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| 0.1685 | 2.67 | 11950 | 0.2612 |
|
| 133 |
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| 0.1724 | 2.68 | 12000 | 0.2596 |
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| 134 |
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| 0.1889 | 2.69 | 12050 | 0.2580 |
|
| 135 |
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| 0.1967 | 2.7 | 12100 | 0.2607 |
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| 136 |
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| 0.1557 | 2.71 | 12150 | 0.2604 |
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| 137 |
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| 0.1643 | 2.73 | 12200 | 0.2593 |
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| 138 |
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| 0.1618 | 2.74 | 12250 | 0.2606 |
|
| 139 |
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| 0.1847 | 2.75 | 12300 | 0.2573 |
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| 140 |
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| 0.1761 | 2.76 | 12350 | 0.2584 |
|
| 141 |
+
| 0.1802 | 2.77 | 12400 | 0.2578 |
|
| 142 |
+
| 0.1651 | 2.78 | 12450 | 0.2582 |
|
| 143 |
+
| 0.1698 | 2.79 | 12500 | 0.2579 |
|
| 144 |
+
| 0.1621 | 2.8 | 12550 | 0.2570 |
|
| 145 |
+
| 0.1768 | 2.81 | 12600 | 0.2582 |
|
| 146 |
+
| 0.1629 | 2.83 | 12650 | 0.2596 |
|
| 147 |
+
| 0.1592 | 2.84 | 12700 | 0.2592 |
|
| 148 |
+
| 0.179 | 2.85 | 12750 | 0.2574 |
|
| 149 |
+
| 0.1539 | 2.86 | 12800 | 0.2577 |
|
| 150 |
+
| 0.1752 | 2.87 | 12850 | 0.2590 |
|
| 151 |
+
| 0.1615 | 2.88 | 12900 | 0.2570 |
|
| 152 |
+
| 0.1711 | 2.89 | 12950 | 0.2579 |
|
| 153 |
+
| 0.1718 | 2.9 | 13000 | 0.2570 |
|
| 154 |
+
| 0.1626 | 2.91 | 13050 | 0.2570 |
|
| 155 |
+
| 0.1595 | 2.93 | 13100 | 0.2583 |
|
| 156 |
+
| 0.1537 | 2.94 | 13150 | 0.2568 |
|
| 157 |
+
| 0.164 | 2.95 | 13200 | 0.2571 |
|
| 158 |
+
| 0.1591 | 2.96 | 13250 | 0.2562 |
|
| 159 |
+
| 0.1661 | 2.97 | 13300 | 0.2575 |
|
| 160 |
+
| 0.16 | 2.98 | 13350 | 0.2570 |
|
| 161 |
+
| 0.1803 | 2.99 | 13400 | 0.2568 |
|
| 162 |
+
| 0.16 | 3.0 | 13450 | 0.2644 |
|
| 163 |
+
| 0.1143 | 3.02 | 13500 | 0.2766 |
|
| 164 |
+
| 0.1218 | 3.03 | 13550 | 0.2799 |
|
| 165 |
+
| 0.1106 | 3.04 | 13600 | 0.2765 |
|
| 166 |
+
| 0.1174 | 3.05 | 13650 | 0.2776 |
|
| 167 |
+
| 0.1167 | 3.06 | 13700 | 0.2783 |
|
| 168 |
+
| 0.1175 | 3.07 | 13750 | 0.2834 |
|
| 169 |
+
| 0.1165 | 3.08 | 13800 | 0.2797 |
|
| 170 |
+
| 0.1117 | 3.09 | 13850 | 0.2810 |
|
| 171 |
+
| 0.1178 | 3.1 | 13900 | 0.2821 |
|
| 172 |
+
| 0.1089 | 3.12 | 13950 | 0.2784 |
|
| 173 |
+
| 0.1108 | 3.13 | 14000 | 0.2824 |
|
| 174 |
+
| 0.1174 | 3.14 | 14050 | 0.2820 |
|
| 175 |
+
| 0.1202 | 3.15 | 14100 | 0.2808 |
|
| 176 |
+
| 0.1198 | 3.16 | 14150 | 0.2817 |
|
| 177 |
+
| 0.1178 | 3.17 | 14200 | 0.2799 |
|
| 178 |
+
| 0.1047 | 3.18 | 14250 | 0.2802 |
|
| 179 |
+
| 0.1159 | 3.19 | 14300 | 0.2815 |
|
| 180 |
+
| 0.1263 | 3.21 | 14350 | 0.2785 |
|
| 181 |
+
| 0.1148 | 3.22 | 14400 | 0.2792 |
|
| 182 |
+
| 0.1242 | 3.23 | 14450 | 0.2779 |
|
| 183 |
+
| 0.1148 | 3.24 | 14500 | 0.2775 |
|
| 184 |
+
| 0.1178 | 3.25 | 14550 | 0.2775 |
|
| 185 |
+
| 0.1189 | 3.26 | 14600 | 0.2789 |
|
| 186 |
+
| 0.1251 | 3.27 | 14650 | 0.2783 |
|
| 187 |
+
| 0.1177 | 3.28 | 14700 | 0.2802 |
|
| 188 |
+
| 0.1195 | 3.29 | 14750 | 0.2792 |
|
| 189 |
+
| 0.1191 | 3.31 | 14800 | 0.2787 |
|
| 190 |
+
| 0.1194 | 3.32 | 14850 | 0.2776 |
|
| 191 |
+
| 0.1239 | 3.33 | 14900 | 0.2800 |
|
| 192 |
+
| 0.1124 | 3.34 | 14950 | 0.2806 |
|
| 193 |
+
| 0.1132 | 3.35 | 15000 | 0.2789 |
|
| 194 |
+
| 0.1124 | 3.36 | 15050 | 0.2815 |
|
| 195 |
+
| 0.1155 | 3.37 | 15100 | 0.2781 |
|
| 196 |
+
| 0.1124 | 3.38 | 15150 | 0.2805 |
|
| 197 |
+
| 0.1149 | 3.4 | 15200 | 0.2787 |
|
| 198 |
+
| 0.1236 | 3.41 | 15250 | 0.2796 |
|
| 199 |
+
| 0.1151 | 3.42 | 15300 | 0.2795 |
|
| 200 |
+
| 0.1355 | 3.43 | 15350 | 0.2794 |
|
| 201 |
+
| 0.1142 | 3.44 | 15400 | 0.2779 |
|
| 202 |
+
| 0.112 | 3.45 | 15450 | 0.2798 |
|
| 203 |
+
| 0.1124 | 3.46 | 15500 | 0.2805 |
|
| 204 |
+
| 0.1117 | 3.47 | 15550 | 0.2793 |
|
| 205 |
+
| 0.1195 | 3.48 | 15600 | 0.2788 |
|
| 206 |
+
| 0.1078 | 3.5 | 15650 | 0.2817 |
|
| 207 |
+
| 0.1085 | 3.51 | 15700 | 0.2802 |
|
| 208 |
+
| 0.1137 | 3.52 | 15750 | 0.2808 |
|
| 209 |
+
| 0.1094 | 3.53 | 15800 | 0.2803 |
|
| 210 |
+
| 0.139 | 3.54 | 15850 | 0.2773 |
|
| 211 |
+
| 0.107 | 3.55 | 15900 | 0.2766 |
|
| 212 |
+
| 0.1161 | 3.56 | 15950 | 0.2781 |
|
| 213 |
+
| 0.1202 | 3.57 | 16000 | 0.2777 |
|
| 214 |
+
| 0.1132 | 3.58 | 16050 | 0.2783 |
|
| 215 |
+
| 0.113 | 3.6 | 16100 | 0.2776 |
|
| 216 |
+
| 0.1109 | 3.61 | 16150 | 0.2790 |
|
| 217 |
+
| 0.1125 | 3.62 | 16200 | 0.2783 |
|
| 218 |
+
| 0.1096 | 3.63 | 16250 | 0.2784 |
|
| 219 |
+
| 0.1093 | 3.64 | 16300 | 0.2774 |
|
| 220 |
+
| 0.1082 | 3.65 | 16350 | 0.2768 |
|
| 221 |
+
| 0.1204 | 3.66 | 16400 | 0.2764 |
|
| 222 |
+
| 0.1059 | 3.67 | 16450 | 0.2783 |
|
| 223 |
+
| 0.1072 | 3.69 | 16500 | 0.2775 |
|
| 224 |
+
| 0.1248 | 3.7 | 16550 | 0.2771 |
|
| 225 |
+
| 0.1171 | 3.71 | 16600 | 0.2766 |
|
| 226 |
+
| 0.1297 | 3.72 | 16650 | 0.2767 |
|
| 227 |
+
| 0.118 | 3.73 | 16700 | 0.2770 |
|
| 228 |
+
| 0.1217 | 3.74 | 16750 | 0.2764 |
|
| 229 |
+
| 0.1208 | 3.75 | 16800 | 0.2781 |
|
| 230 |
+
| 0.1117 | 3.76 | 16850 | 0.2775 |
|
| 231 |
+
| 0.1098 | 3.77 | 16900 | 0.2789 |
|
| 232 |
+
| 0.1124 | 3.79 | 16950 | 0.2804 |
|
| 233 |
+
| 0.1065 | 3.8 | 17000 | 0.2799 |
|
| 234 |
+
| 0.1041 | 3.81 | 17050 | 0.2786 |
|
| 235 |
+
| 0.1112 | 3.82 | 17100 | 0.2776 |
|
| 236 |
+
| 0.1086 | 3.83 | 17150 | 0.2775 |
|
| 237 |
+
| 0.1229 | 3.84 | 17200 | 0.2777 |
|
| 238 |
+
| 0.1099 | 3.85 | 17250 | 0.2778 |
|
| 239 |
+
| 0.1121 | 3.86 | 17300 | 0.2780 |
|
| 240 |
+
| 0.1175 | 3.88 | 17350 | 0.2784 |
|
| 241 |
+
| 0.1131 | 3.89 | 17400 | 0.2780 |
|
| 242 |
+
| 0.1031 | 3.9 | 17450 | 0.2781 |
|
| 243 |
+
| 0.1123 | 3.91 | 17500 | 0.2782 |
|
| 244 |
+
| 0.1113 | 3.92 | 17550 | 0.2783 |
|
| 245 |
+
| 0.1126 | 3.93 | 17600 | 0.2781 |
|
| 246 |
+
| 0.1068 | 3.94 | 17650 | 0.2779 |
|
| 247 |
+
| 0.1095 | 3.95 | 17700 | 0.2782 |
|
| 248 |
+
| 0.1058 | 3.96 | 17750 | 0.2782 |
|
| 249 |
+
| 0.1105 | 3.98 | 17800 | 0.2781 |
|
| 250 |
+
| 0.1108 | 3.99 | 17850 | 0.2781 |
|
| 251 |
+
| 0.1071 | 4.0 | 17900 | 0.2781 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 252 |
|
| 253 |
|
| 254 |
### Framework versions
|
adapter_model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 3611357976
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:8c34726792d36e94ef7947692dec5d4bb0113d89451ce1eda08b7e5a700115cb
|
| 3 |
size 3611357976
|
runs/Apr04_08-41-59_b562675953c9/events.out.tfevents.1712220131.b562675953c9.118101.0
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:7c4cd4793fe06f84a579f32137d8365d058b0c87e506672f45b9b497da88a5e1
|
| 3 |
+
size 135301
|