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--- |
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license: llama2 |
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library_name: peft |
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tags: |
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- trl |
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- sft |
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- generated_from_trainer |
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base_model: codellama/CodeLlama-7b-Instruct-hf |
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model-index: |
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- name: Codellama-7b-lora-rps-adapter |
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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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# Codellama-7b-lora-rps-adapter |
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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: 0.3064 |
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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: 0.0002 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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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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| 0.2516 | 1.8549 | 10000 | 0.2925 | |
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| 0.2922 | 1.8642 | 10050 | 0.2922 | |
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| 0.266 | 1.8735 | 10100 | 0.2930 | |
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| 0.2656 | 1.8828 | 10150 | 0.2932 | |
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| 0.2594 | 1.8920 | 10200 | 0.2916 | |
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| 0.255 | 1.9013 | 10250 | 0.2915 | |
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| 0.2722 | 1.9106 | 10300 | 0.2922 | |
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| 0.2211 | 1.9199 | 10350 | 0.2921 | |
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| 0.2755 | 1.9291 | 10400 | 0.2909 | |
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| 0.2222 | 1.9384 | 10450 | 0.2919 | |
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| 0.227 | 1.9477 | 10500 | 0.2913 | |
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| 0.2264 | 1.9570 | 10550 | 0.2929 | |
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| 0.2623 | 1.9662 | 10600 | 0.2915 | |
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| 0.2488 | 1.9755 | 10650 | 0.2919 | |
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| 0.2593 | 1.9848 | 10700 | 0.2902 | |
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| 0.2277 | 1.9941 | 10750 | 0.2896 | |
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| 0.2307 | 2.0033 | 10800 | 0.2930 | |
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| 0.1822 | 2.0126 | 10850 | 0.2991 | |
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| 0.1777 | 2.0219 | 10900 | 0.2991 | |
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| 0.1916 | 2.0312 | 10950 | 0.3001 | |
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| 0.1895 | 2.0404 | 11000 | 0.3005 | |
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| 0.2034 | 2.0497 | 11050 | 0.2991 | |
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| 0.2086 | 2.0590 | 11100 | 0.2999 | |
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| 0.1951 | 2.0683 | 11150 | 0.2983 | |
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| 0.1652 | 2.0775 | 11200 | 0.2988 | |
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| 0.1861 | 2.0868 | 11250 | 0.2996 | |
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| 0.1655 | 2.0961 | 11300 | 0.3025 | |
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| 0.201 | 2.1054 | 11350 | 0.2996 | |
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| 0.1877 | 2.1146 | 11400 | 0.3011 | |
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| 0.1832 | 2.1239 | 11450 | 0.3018 | |
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| 0.18 | 2.1332 | 11500 | 0.2991 | |
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| 0.1865 | 2.1425 | 11550 | 0.3029 | |
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| 0.1918 | 2.1517 | 11600 | 0.2994 | |
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| 0.1917 | 2.1610 | 11650 | 0.2983 | |
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| 0.1722 | 2.1703 | 11700 | 0.3000 | |
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| 0.1865 | 2.1796 | 11750 | 0.2987 | |
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| 0.1997 | 2.1888 | 11800 | 0.2987 | |
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| 0.1907 | 2.1981 | 11850 | 0.3019 | |
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| 0.1981 | 2.2074 | 11900 | 0.2974 | |
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| 0.1918 | 2.2167 | 11950 | 0.2986 | |
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| 0.1839 | 2.2259 | 12000 | 0.2987 | |
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| 0.1888 | 2.2352 | 12050 | 0.2969 | |
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| 0.1763 | 2.2445 | 12100 | 0.2989 | |
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| 0.1996 | 2.2538 | 12150 | 0.2982 | |
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| 0.1917 | 2.2630 | 12200 | 0.3011 | |
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| 0.172 | 2.2723 | 12250 | 0.2997 | |
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| 0.1857 | 2.2816 | 12300 | 0.3035 | |
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| 0.1844 | 2.2909 | 12350 | 0.2978 | |
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| 0.2055 | 2.3001 | 12400 | 0.2986 | |
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| 0.189 | 2.3094 | 12450 | 0.2979 | |
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| 0.1958 | 2.3187 | 12500 | 0.2977 | |
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| 0.1954 | 2.3280 | 12550 | 0.2988 | |
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| 0.1796 | 2.3372 | 12600 | 0.2983 | |
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| 0.2019 | 2.3465 | 12650 | 0.2955 | |
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| 0.1816 | 2.3558 | 12700 | 0.2962 | |
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| 0.1763 | 2.3651 | 12750 | 0.2976 | |
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| 0.1892 | 2.3743 | 12800 | 0.2968 | |
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| 0.1805 | 2.3836 | 12850 | 0.2973 | |
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| 0.1878 | 2.3929 | 12900 | 0.2958 | |
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| 0.1852 | 2.4022 | 12950 | 0.2971 | |
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| 0.1907 | 2.4114 | 13000 | 0.2985 | |
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| 0.2004 | 2.4207 | 13050 | 0.2970 | |
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| 0.1871 | 2.4300 | 13100 | 0.2965 | |
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| 0.1958 | 2.4393 | 13150 | 0.2966 | |
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| 0.2132 | 2.4485 | 13200 | 0.2940 | |
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| 0.1819 | 2.4578 | 13250 | 0.2951 | |
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| 0.1627 | 2.4671 | 13300 | 0.2965 | |
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| 0.1821 | 2.4763 | 13350 | 0.2954 | |
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| 0.1902 | 2.4856 | 13400 | 0.2939 | |
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| 0.1992 | 2.4949 | 13450 | 0.2960 | |
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| 0.1936 | 2.5042 | 13500 | 0.2946 | |
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| 0.2074 | 2.5134 | 13550 | 0.2937 | |
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| 0.1877 | 2.5227 | 13600 | 0.2959 | |
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| 0.2026 | 2.5320 | 13650 | 0.2935 | |
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| 0.1816 | 2.5413 | 13700 | 0.2961 | |
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| 0.1769 | 2.5505 | 13750 | 0.2941 | |
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| 0.175 | 2.5598 | 13800 | 0.2944 | |
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| 0.1791 | 2.5691 | 13850 | 0.2954 | |
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| 0.2015 | 2.5784 | 13900 | 0.2946 | |
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| 0.1845 | 2.5876 | 13950 | 0.2926 | |
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| 0.1699 | 2.5969 | 14000 | 0.2952 | |
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| 0.1739 | 2.6062 | 14050 | 0.2930 | |
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| 0.1817 | 2.6155 | 14100 | 0.2933 | |
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| 0.174 | 2.6247 | 14150 | 0.2943 | |
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| 0.2047 | 2.6340 | 14200 | 0.2936 | |
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| 0.1843 | 2.6433 | 14250 | 0.2939 | |
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| 0.2035 | 2.6526 | 14300 | 0.2933 | |
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| 0.2025 | 2.6618 | 14350 | 0.2935 | |
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| 0.1896 | 2.6711 | 14400 | 0.2937 | |
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| 0.2029 | 2.6804 | 14450 | 0.2938 | |
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| 0.1953 | 2.6897 | 14500 | 0.2941 | |
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| 0.1952 | 2.6989 | 14550 | 0.2930 | |
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| 0.1847 | 2.7082 | 14600 | 0.2920 | |
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| 0.1896 | 2.7175 | 14650 | 0.2935 | |
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| 0.1703 | 2.7268 | 14700 | 0.2921 | |
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| 0.1845 | 2.7360 | 14750 | 0.2923 | |
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| 0.1809 | 2.7453 | 14800 | 0.2920 | |
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| 0.1924 | 2.7546 | 14850 | 0.2929 | |
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| 0.1894 | 2.7639 | 14900 | 0.2909 | |
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| 0.1926 | 2.7731 | 14950 | 0.2908 | |
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| 0.2106 | 2.7824 | 15000 | 0.2921 | |
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| 0.1705 | 2.7917 | 15050 | 0.2903 | |
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| 0.1739 | 2.8010 | 15100 | 0.2892 | |
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| 0.1798 | 2.8102 | 15150 | 0.2921 | |
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| 0.2088 | 2.8195 | 15200 | 0.2909 | |
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| 0.1862 | 2.8288 | 15250 | 0.2920 | |
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| 0.1891 | 2.8381 | 15300 | 0.2919 | |
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| 0.2022 | 2.8473 | 15350 | 0.2899 | |
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| 0.1655 | 2.8566 | 15400 | 0.2908 | |
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| 0.1771 | 2.8659 | 15450 | 0.2905 | |
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| 0.1747 | 2.8752 | 15500 | 0.2886 | |
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| 0.1904 | 2.8844 | 15550 | 0.2891 | |
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| 0.1821 | 2.8937 | 15600 | 0.2892 | |
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| 0.1687 | 2.9030 | 15650 | 0.2892 | |
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| 0.1837 | 2.9123 | 15700 | 0.2904 | |
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| 0.1643 | 2.9215 | 15750 | 0.2898 | |
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| 0.1897 | 2.9308 | 15800 | 0.2882 | |
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| 0.2062 | 2.9401 | 15850 | 0.2885 | |
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| 0.178 | 2.9494 | 15900 | 0.2881 | |
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| 0.1719 | 2.9586 | 15950 | 0.2902 | |
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| 0.1866 | 2.9679 | 16000 | 0.2881 | |
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| 0.1678 | 2.9772 | 16050 | 0.2878 | |
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| 0.1794 | 2.9865 | 16100 | 0.2889 | |
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| 0.1805 | 2.9957 | 16150 | 0.2878 | |
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| 0.161 | 3.0050 | 16200 | 0.2981 | |
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| 0.1198 | 3.0143 | 16250 | 0.3084 | |
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| 0.1213 | 3.0236 | 16300 | 0.3084 | |
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| 0.144 | 3.0328 | 16350 | 0.3076 | |
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| 0.1362 | 3.0421 | 16400 | 0.3092 | |
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| 0.1315 | 3.0514 | 16450 | 0.3089 | |
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| 0.1358 | 3.0607 | 16500 | 0.3094 | |
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| 0.1276 | 3.0699 | 16550 | 0.3087 | |
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| 0.125 | 3.0792 | 16600 | 0.3114 | |
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| 0.1203 | 3.0885 | 16650 | 0.3112 | |
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| 0.1295 | 3.0978 | 16700 | 0.3100 | |
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| 0.1191 | 3.1070 | 16750 | 0.3092 | |
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| 0.1379 | 3.1163 | 16800 | 0.3087 | |
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| 0.1175 | 3.1256 | 16850 | 0.3122 | |
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| 0.1314 | 3.1349 | 16900 | 0.3066 | |
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| 0.1266 | 3.1441 | 16950 | 0.3077 | |
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| 0.1158 | 3.1534 | 17000 | 0.3088 | |
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| 0.128 | 3.1627 | 17050 | 0.3106 | |
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| 0.1368 | 3.1720 | 17100 | 0.3095 | |
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| 0.1334 | 3.1812 | 17150 | 0.3055 | |
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| 0.1265 | 3.1905 | 17200 | 0.3104 | |
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| 0.133 | 3.1998 | 17250 | 0.3068 | |
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| 0.1263 | 3.2091 | 17300 | 0.3078 | |
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| 0.1269 | 3.2183 | 17350 | 0.3091 | |
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| 0.1372 | 3.2276 | 17400 | 0.3083 | |
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| 0.122 | 3.2369 | 17450 | 0.3083 | |
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| 0.1403 | 3.2462 | 17500 | 0.3087 | |
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| 0.1331 | 3.2554 | 17550 | 0.3086 | |
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| 0.1296 | 3.2647 | 17600 | 0.3079 | |
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| 0.1248 | 3.2740 | 17650 | 0.3056 | |
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| 0.1299 | 3.2832 | 17700 | 0.3088 | |
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| 0.1283 | 3.2925 | 17750 | 0.3086 | |
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| 0.1286 | 3.3018 | 17800 | 0.3077 | |
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| 0.1165 | 3.3111 | 17850 | 0.3088 | |
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| 0.1228 | 3.3203 | 17900 | 0.3082 | |
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| 0.1258 | 3.3296 | 17950 | 0.3096 | |
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| 0.1246 | 3.3389 | 18000 | 0.3124 | |
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| 0.1238 | 3.3482 | 18050 | 0.3111 | |
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| 0.1211 | 3.3574 | 18100 | 0.3088 | |
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| 0.1345 | 3.3667 | 18150 | 0.3069 | |
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| 0.1362 | 3.3760 | 18200 | 0.3066 | |
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| 0.1199 | 3.3853 | 18250 | 0.3065 | |
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| 0.1252 | 3.3945 | 18300 | 0.3064 | |
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| 0.1209 | 3.4038 | 18350 | 0.3096 | |
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| 0.1414 | 3.4131 | 18400 | 0.3062 | |
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| 0.1496 | 3.4224 | 18450 | 0.3059 | |
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| 0.1163 | 3.4316 | 18500 | 0.3064 | |
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| 0.1459 | 3.4409 | 18550 | 0.3067 | |
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| 0.1299 | 3.4502 | 18600 | 0.3088 | |
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| 0.1285 | 3.4595 | 18650 | 0.3064 | |
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| 0.1252 | 3.4687 | 18700 | 0.3076 | |
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| 0.1208 | 3.4780 | 18750 | 0.3074 | |
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| 0.1194 | 3.4873 | 18800 | 0.3080 | |
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| 0.1308 | 3.4966 | 18850 | 0.3061 | |
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| 0.1137 | 3.5058 | 18900 | 0.3061 | |
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| 0.1119 | 3.5151 | 18950 | 0.3081 | |
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| 0.1251 | 3.5244 | 19000 | 0.3080 | |
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| 0.1259 | 3.5337 | 19050 | 0.3063 | |
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| 0.1311 | 3.5429 | 19100 | 0.3066 | |
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| 0.1123 | 3.5522 | 19150 | 0.3075 | |
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| 0.1255 | 3.5615 | 19200 | 0.3082 | |
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| 0.1259 | 3.5708 | 19250 | 0.3072 | |
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| 0.1279 | 3.5800 | 19300 | 0.3057 | |
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| 0.1397 | 3.5893 | 19350 | 0.3048 | |
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| 0.1179 | 3.5986 | 19400 | 0.3060 | |
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| 0.1412 | 3.6079 | 19450 | 0.3057 | |
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| 0.1151 | 3.6171 | 19500 | 0.3069 | |
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| 0.1138 | 3.6264 | 19550 | 0.3076 | |
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| 0.1357 | 3.6357 | 19600 | 0.3077 | |
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| 0.114 | 3.6450 | 19650 | 0.3086 | |
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| 0.118 | 3.6542 | 19700 | 0.3085 | |
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| 0.1388 | 3.6635 | 19750 | 0.3074 | |
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| 0.1253 | 3.6728 | 19800 | 0.3081 | |
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| 0.1243 | 3.6821 | 19850 | 0.3069 | |
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| 0.1241 | 3.6913 | 19900 | 0.3068 | |
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| 0.1336 | 3.7006 | 19950 | 0.3067 | |
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| 0.1252 | 3.7099 | 20000 | 0.3079 | |
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| 0.1198 | 3.7192 | 20050 | 0.3077 | |
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| 0.1416 | 3.7284 | 20100 | 0.3054 | |
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| 0.1268 | 3.7377 | 20150 | 0.3071 | |
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| 0.126 | 3.7470 | 20200 | 0.3073 | |
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| 0.1123 | 3.7563 | 20250 | 0.3076 | |
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| 0.1228 | 3.7655 | 20300 | 0.3070 | |
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| 0.1199 | 3.7748 | 20350 | 0.3082 | |
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| 0.1307 | 3.7841 | 20400 | 0.3079 | |
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| 0.1234 | 3.7934 | 20450 | 0.3071 | |
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| 0.1346 | 3.8026 | 20500 | 0.3074 | |
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| 0.1115 | 3.8119 | 20550 | 0.3074 | |
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| 0.1183 | 3.8212 | 20600 | 0.3067 | |
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| 0.1185 | 3.8305 | 20650 | 0.3066 | |
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| 0.1203 | 3.8397 | 20700 | 0.3074 | |
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| 0.1262 | 3.8490 | 20750 | 0.3078 | |
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| 0.1232 | 3.8583 | 20800 | 0.3077 | |
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| 0.1196 | 3.8676 | 20850 | 0.3075 | |
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| 0.1217 | 3.8768 | 20900 | 0.3071 | |
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| 0.1392 | 3.8861 | 20950 | 0.3068 | |
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| 0.117 | 3.8954 | 21000 | 0.3065 | |
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| 0.1396 | 3.9047 | 21050 | 0.3058 | |
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| 0.1149 | 3.9139 | 21100 | 0.3061 | |
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| 0.1235 | 3.9232 | 21150 | 0.3062 | |
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| 0.125 | 3.9325 | 21200 | 0.3064 | |
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| 0.1272 | 3.9418 | 21250 | 0.3060 | |
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| 0.1189 | 3.9510 | 21300 | 0.3062 | |
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| 0.1132 | 3.9603 | 21350 | 0.3064 | |
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| 0.1221 | 3.9696 | 21400 | 0.3063 | |
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| 0.1283 | 3.9789 | 21450 | 0.3064 | |
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| 0.135 | 3.9881 | 21500 | 0.3063 | |
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| 0.1207 | 3.9974 | 21550 | 0.3064 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
