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--- |
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base_model: codellama/CodeLlama-7b-Instruct-hf |
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library_name: peft |
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license: llama2 |
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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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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: 0.3056 |
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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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| 0.2053 | 2.3256 | 15000 | 0.2969 | |
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| 0.1942 | 2.3333 | 15050 | 0.2944 | |
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| 0.1871 | 2.3411 | 15100 | 0.2949 | |
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| 0.1845 | 2.3488 | 15150 | 0.2954 | |
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| 0.2108 | 2.3566 | 15200 | 0.2950 | |
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| 0.2065 | 2.3643 | 15250 | 0.2951 | |
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| 0.193 | 2.3721 | 15300 | 0.2961 | |
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| 0.1947 | 2.3798 | 15350 | 0.2953 | |
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| 0.1922 | 2.3876 | 15400 | 0.2949 | |
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| 0.1777 | 2.3953 | 15450 | 0.2949 | |
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| 0.212 | 2.4031 | 15500 | 0.2949 | |
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| 0.1962 | 2.4109 | 15550 | 0.2949 | |
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| 0.1789 | 2.4186 | 15600 | 0.2951 | |
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| 0.2183 | 2.4264 | 15650 | 0.2923 | |
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| 0.1962 | 2.4341 | 15700 | 0.2947 | |
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| 0.1907 | 2.4419 | 15750 | 0.2928 | |
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| 0.1936 | 2.4496 | 15800 | 0.2956 | |
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| 0.2086 | 2.4574 | 15850 | 0.2933 | |
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| 0.1895 | 2.4651 | 15900 | 0.2959 | |
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| 0.2157 | 2.4729 | 15950 | 0.2932 | |
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| 0.1897 | 2.4806 | 16000 | 0.2926 | |
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| 0.1862 | 2.4884 | 16050 | 0.2937 | |
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| 0.1899 | 2.4961 | 16100 | 0.2955 | |
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| 0.187 | 2.5039 | 16150 | 0.2970 | |
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| 0.2126 | 2.5116 | 16200 | 0.2941 | |
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| 0.1973 | 2.5194 | 16250 | 0.2933 | |
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| 0.1743 | 2.5271 | 16300 | 0.2930 | |
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| 0.1958 | 2.5349 | 16350 | 0.2938 | |
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| 0.2162 | 2.5426 | 16400 | 0.2919 | |
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| 0.1872 | 2.5504 | 16450 | 0.2936 | |
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| 0.1821 | 2.5581 | 16500 | 0.2940 | |
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| 0.2193 | 2.5659 | 16550 | 0.2940 | |
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| 0.1983 | 2.5736 | 16600 | 0.2943 | |
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| 0.2121 | 2.5814 | 16650 | 0.2941 | |
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| 0.1969 | 2.5891 | 16700 | 0.2923 | |
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| 0.1963 | 2.5969 | 16750 | 0.2921 | |
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| 0.2042 | 2.6047 | 16800 | 0.2938 | |
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| 0.1921 | 2.6124 | 16850 | 0.2914 | |
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| 0.2081 | 2.6202 | 16900 | 0.2917 | |
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| 0.1711 | 2.6279 | 16950 | 0.2923 | |
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| 0.1897 | 2.6357 | 17000 | 0.2918 | |
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| 0.1917 | 2.6434 | 17050 | 0.2933 | |
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| 0.1991 | 2.6512 | 17100 | 0.2909 | |
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| 0.2055 | 2.6589 | 17150 | 0.2930 | |
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| 0.1932 | 2.6667 | 17200 | 0.2907 | |
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| 0.2043 | 2.6744 | 17250 | 0.2937 | |
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| 0.1922 | 2.6822 | 17300 | 0.2922 | |
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| 0.1785 | 2.6899 | 17350 | 0.2922 | |
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| 0.2337 | 2.6977 | 17400 | 0.2908 | |
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| 0.1933 | 2.7054 | 17450 | 0.2922 | |
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| 0.2012 | 2.7132 | 17500 | 0.2914 | |
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| 0.1959 | 2.7209 | 17550 | 0.2910 | |
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| 0.1933 | 2.7287 | 17600 | 0.2882 | |
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| 0.1824 | 2.7364 | 17650 | 0.2889 | |
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| 0.2016 | 2.7442 | 17700 | 0.2898 | |
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| 0.2024 | 2.7519 | 17750 | 0.2915 | |
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| 0.2101 | 2.7597 | 17800 | 0.2888 | |
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| 0.1782 | 2.7674 | 17850 | 0.2908 | |
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| 0.2047 | 2.7752 | 17900 | 0.2902 | |
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| 0.195 | 2.7829 | 17950 | 0.2895 | |
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| 0.2122 | 2.7907 | 18000 | 0.2884 | |
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| 0.2099 | 2.7984 | 18050 | 0.2869 | |
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| 0.2054 | 2.8062 | 18100 | 0.2882 | |
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| 0.193 | 2.8140 | 18150 | 0.2884 | |
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| 0.187 | 2.8217 | 18200 | 0.2895 | |
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| 0.1997 | 2.8295 | 18250 | 0.2883 | |
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| 0.1885 | 2.8372 | 18300 | 0.2896 | |
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| 0.1957 | 2.8450 | 18350 | 0.2871 | |
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| 0.1905 | 2.8527 | 18400 | 0.2879 | |
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| 0.1933 | 2.8605 | 18450 | 0.2880 | |
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| 0.1953 | 2.8682 | 18500 | 0.2871 | |
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| 0.205 | 2.8760 | 18550 | 0.2865 | |
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| 0.191 | 2.8837 | 18600 | 0.2870 | |
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| 0.1903 | 2.8915 | 18650 | 0.2870 | |
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| 0.1897 | 2.8992 | 18700 | 0.2873 | |
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| 0.1966 | 2.9070 | 18750 | 0.2871 | |
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| 0.228 | 2.9147 | 18800 | 0.2875 | |
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| 0.1948 | 2.9225 | 18850 | 0.2870 | |
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| 0.1843 | 2.9302 | 18900 | 0.2859 | |
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| 0.2037 | 2.9380 | 18950 | 0.2872 | |
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| 0.2087 | 2.9457 | 19000 | 0.2855 | |
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| 0.1777 | 2.9535 | 19050 | 0.2864 | |
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| 0.1852 | 2.9612 | 19100 | 0.2866 | |
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| 0.1879 | 2.9690 | 19150 | 0.2858 | |
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| 0.2096 | 2.9767 | 19200 | 0.2848 | |
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| 0.1846 | 2.9845 | 19250 | 0.2857 | |
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| 0.1782 | 2.9922 | 19300 | 0.2859 | |
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| 0.1762 | 3.0 | 19350 | 0.2864 | |
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| 0.1339 | 3.0078 | 19400 | 0.3056 | |
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| 0.1356 | 3.0155 | 19450 | 0.3067 | |
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| 0.136 | 3.0233 | 19500 | 0.3073 | |
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| 0.1389 | 3.0310 | 19550 | 0.3089 | |
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| 0.1362 | 3.0388 | 19600 | 0.3084 | |
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| 0.1384 | 3.0465 | 19650 | 0.3085 | |
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| 0.1167 | 3.0543 | 19700 | 0.3092 | |
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| 0.1291 | 3.0620 | 19750 | 0.3078 | |
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| 0.1292 | 3.0698 | 19800 | 0.3092 | |
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| 0.1257 | 3.0775 | 19850 | 0.3099 | |
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| 0.1384 | 3.0853 | 19900 | 0.3088 | |
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| 0.1355 | 3.0930 | 19950 | 0.3076 | |
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| 0.1244 | 3.1008 | 20000 | 0.3088 | |
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| 0.141 | 3.1085 | 20050 | 0.3082 | |
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| 0.1398 | 3.1163 | 20100 | 0.3080 | |
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| 0.1415 | 3.1240 | 20150 | 0.3085 | |
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| 0.1521 | 3.1318 | 20200 | 0.3067 | |
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| 0.1266 | 3.1395 | 20250 | 0.3097 | |
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| 0.1254 | 3.1473 | 20300 | 0.3101 | |
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| 0.1403 | 3.1550 | 20350 | 0.3053 | |
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| 0.1395 | 3.1628 | 20400 | 0.3085 | |
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| 0.1328 | 3.1705 | 20450 | 0.3074 | |
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| 0.1381 | 3.1783 | 20500 | 0.3090 | |
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| 0.1323 | 3.1860 | 20550 | 0.3058 | |
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| 0.1299 | 3.1938 | 20600 | 0.3092 | |
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| 0.1432 | 3.2016 | 20650 | 0.3074 | |
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| 0.1399 | 3.2093 | 20700 | 0.3071 | |
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| 0.1288 | 3.2171 | 20750 | 0.3076 | |
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| 0.1464 | 3.2248 | 20800 | 0.3060 | |
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| 0.1347 | 3.2326 | 20850 | 0.3066 | |
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| 0.1336 | 3.2403 | 20900 | 0.3080 | |
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| 0.1245 | 3.2481 | 20950 | 0.3069 | |
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| 0.1305 | 3.2558 | 21000 | 0.3080 | |
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| 0.1379 | 3.2636 | 21050 | 0.3050 | |
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| 0.1269 | 3.2713 | 21100 | 0.3074 | |
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| 0.1379 | 3.2791 | 21150 | 0.3067 | |
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| 0.1348 | 3.2868 | 21200 | 0.3077 | |
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| 0.1261 | 3.2946 | 21250 | 0.3116 | |
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| 0.1354 | 3.3023 | 21300 | 0.3064 | |
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| 0.1323 | 3.3101 | 21350 | 0.3061 | |
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| 0.1255 | 3.3178 | 21400 | 0.3078 | |
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| 0.135 | 3.3256 | 21450 | 0.3073 | |
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| 0.1354 | 3.3333 | 21500 | 0.3070 | |
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| 0.1391 | 3.3411 | 21550 | 0.3066 | |
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| 0.1295 | 3.3488 | 21600 | 0.3086 | |
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| 0.1215 | 3.3566 | 21650 | 0.3085 | |
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| 0.1411 | 3.3643 | 21700 | 0.3072 | |
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| 0.1393 | 3.3721 | 21750 | 0.3090 | |
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| 0.132 | 3.3798 | 21800 | 0.3086 | |
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| 0.1199 | 3.3876 | 21850 | 0.3089 | |
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| 0.1349 | 3.3953 | 21900 | 0.3069 | |
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| 0.1325 | 3.4031 | 21950 | 0.3084 | |
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| 0.1247 | 3.4109 | 22000 | 0.3082 | |
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| 0.1178 | 3.4186 | 22050 | 0.3062 | |
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| 0.1218 | 3.4264 | 22100 | 0.3090 | |
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| 0.131 | 3.4341 | 22150 | 0.3100 | |
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| 0.1274 | 3.4419 | 22200 | 0.3070 | |
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| 0.136 | 3.4496 | 22250 | 0.3083 | |
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| 0.1458 | 3.4574 | 22300 | 0.3076 | |
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| 0.1365 | 3.4651 | 22350 | 0.3087 | |
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| 0.1362 | 3.4729 | 22400 | 0.3071 | |
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| 0.1318 | 3.4806 | 22450 | 0.3073 | |
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| 0.138 | 3.4884 | 22500 | 0.3067 | |
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| 0.1413 | 3.4961 | 22550 | 0.3080 | |
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| 0.1365 | 3.5039 | 22600 | 0.3087 | |
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| 0.1236 | 3.5116 | 22650 | 0.3078 | |
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| 0.1503 | 3.5194 | 22700 | 0.3063 | |
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| 0.1437 | 3.5271 | 22750 | 0.3070 | |
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| 0.1338 | 3.5349 | 22800 | 0.3070 | |
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| 0.1256 | 3.5426 | 22850 | 0.3080 | |
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| 0.1296 | 3.5504 | 22900 | 0.3074 | |
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| 0.1286 | 3.5581 | 22950 | 0.3061 | |
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| 0.1334 | 3.5659 | 23000 | 0.3075 | |
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| 0.133 | 3.5736 | 23050 | 0.3058 | |
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| 0.113 | 3.5814 | 23100 | 0.3060 | |
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| 0.1238 | 3.5891 | 23150 | 0.3052 | |
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| 0.1398 | 3.5969 | 23200 | 0.3044 | |
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| 0.142 | 3.6047 | 23250 | 0.3054 | |
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| 0.1257 | 3.6124 | 23300 | 0.3059 | |
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| 0.1324 | 3.6202 | 23350 | 0.3052 | |
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| 0.1376 | 3.6279 | 23400 | 0.3039 | |
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| 0.1343 | 3.6357 | 23450 | 0.3037 | |
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| 0.1264 | 3.6434 | 23500 | 0.3054 | |
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| 0.1263 | 3.6512 | 23550 | 0.3062 | |
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| 0.127 | 3.6589 | 23600 | 0.3054 | |
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| 0.1187 | 3.6667 | 23650 | 0.3054 | |
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| 0.1204 | 3.6744 | 23700 | 0.3059 | |
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| 0.1148 | 3.6822 | 23750 | 0.3065 | |
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| 0.1205 | 3.6899 | 23800 | 0.3073 | |
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| 0.1277 | 3.6977 | 23850 | 0.3067 | |
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| 0.1356 | 3.7054 | 23900 | 0.3067 | |
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| 0.1518 | 3.7132 | 23950 | 0.3064 | |
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| 0.1307 | 3.7209 | 24000 | 0.3062 | |
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| 0.1344 | 3.7287 | 24050 | 0.3061 | |
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| 0.1326 | 3.7364 | 24100 | 0.3065 | |
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| 0.1246 | 3.7442 | 24150 | 0.3074 | |
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| 0.1319 | 3.7519 | 24200 | 0.3071 | |
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| 0.1436 | 3.7597 | 24250 | 0.3063 | |
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| 0.1389 | 3.7674 | 24300 | 0.3064 | |
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| 0.1275 | 3.7752 | 24350 | 0.3065 | |
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| 0.1353 | 3.7829 | 24400 | 0.3061 | |
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| 0.1289 | 3.7907 | 24450 | 0.3056 | |
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| 0.1326 | 3.7984 | 24500 | 0.3053 | |
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| 0.1244 | 3.8062 | 24550 | 0.3054 | |
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| 0.1287 | 3.8140 | 24600 | 0.3056 | |
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| 0.1168 | 3.8217 | 24650 | 0.3058 | |
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| 0.1298 | 3.8295 | 24700 | 0.3055 | |
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| 0.1231 | 3.8372 | 24750 | 0.3057 | |
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| 0.1289 | 3.8450 | 24800 | 0.3059 | |
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| 0.1184 | 3.8527 | 24850 | 0.3056 | |
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| 0.1226 | 3.8605 | 24900 | 0.3055 | |
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| 0.1593 | 3.8682 | 24950 | 0.3057 | |
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| 0.128 | 3.8760 | 25000 | 0.3064 | |
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| 0.1332 | 3.8837 | 25050 | 0.3058 | |
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| 0.1397 | 3.8915 | 25100 | 0.3055 | |
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| 0.1059 | 3.8992 | 25150 | 0.3058 | |
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| 0.1281 | 3.9070 | 25200 | 0.3054 | |
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| 0.1277 | 3.9147 | 25250 | 0.3056 | |
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| 0.1119 | 3.9225 | 25300 | 0.3059 | |
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| 0.1212 | 3.9302 | 25350 | 0.3059 | |
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| 0.1131 | 3.9380 | 25400 | 0.3059 | |
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| 0.1407 | 3.9457 | 25450 | 0.3059 | |
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| 0.1286 | 3.9535 | 25500 | 0.3056 | |
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| 0.1252 | 3.9612 | 25550 | 0.3056 | |
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| 0.138 | 3.9690 | 25600 | 0.3056 | |
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| 0.1245 | 3.9767 | 25650 | 0.3056 | |
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| 0.1213 | 3.9845 | 25700 | 0.3056 | |
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| 0.1276 | 3.9922 | 25750 | 0.3056 | |
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| 0.1328 | 4.0 | 25800 | 0.3056 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
