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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: 0.2990 |
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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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 0.1884 | 2.23 | 10000 | 0.2693 | |
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| 0.192 | 2.24 | 10050 | 0.2685 | |
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| 0.1956 | 2.26 | 10100 | 0.2687 | |
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| 0.1865 | 2.27 | 10150 | 0.2707 | |
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| 0.1896 | 2.28 | 10200 | 0.2684 | |
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| 0.1965 | 2.29 | 10250 | 0.2665 | |
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| 0.1805 | 2.3 | 10300 | 0.2676 | |
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| 0.2016 | 2.31 | 10350 | 0.2679 | |
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| 0.1755 | 2.32 | 10400 | 0.2695 | |
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| 0.1832 | 2.33 | 10450 | 0.2694 | |
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| 0.1789 | 2.35 | 10500 | 0.2696 | |
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| 0.1866 | 2.36 | 10550 | 0.2683 | |
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| 0.1816 | 2.37 | 10600 | 0.2665 | |
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| 0.1848 | 2.38 | 10650 | 0.2677 | |
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| 0.1629 | 2.39 | 10700 | 0.2684 | |
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| 0.1735 | 2.4 | 10750 | 0.2663 | |
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| 0.1687 | 2.41 | 10800 | 0.2674 | |
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| 0.1895 | 2.42 | 10850 | 0.2658 | |
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| 0.1964 | 2.43 | 10900 | 0.2676 | |
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| 0.1962 | 2.45 | 10950 | 0.2659 | |
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| 0.2073 | 2.46 | 11000 | 0.2645 | |
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| 0.223 | 2.47 | 11050 | 0.2648 | |
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| 0.1857 | 2.48 | 11100 | 0.2644 | |
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| 0.1867 | 2.49 | 11150 | 0.2643 | |
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| 0.1907 | 2.5 | 11200 | 0.2646 | |
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| 0.2093 | 2.51 | 11250 | 0.2626 | |
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| 0.1783 | 2.52 | 11300 | 0.2660 | |
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| 0.1985 | 2.54 | 11350 | 0.2644 | |
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| 0.206 | 2.55 | 11400 | 0.2621 | |
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| 0.1849 | 2.56 | 11450 | 0.2634 | |
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| 0.1838 | 2.57 | 11500 | 0.2638 | |
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| 0.1897 | 2.58 | 11550 | 0.2625 | |
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| 0.1953 | 2.59 | 11600 | 0.2623 | |
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| 0.1972 | 2.6 | 11650 | 0.2617 | |
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| 0.1953 | 2.61 | 11700 | 0.2615 | |
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| 0.1699 | 2.62 | 11750 | 0.2637 | |
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| 0.1748 | 2.64 | 11800 | 0.2651 | |
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| 0.191 | 2.65 | 11850 | 0.2610 | |
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| 0.1924 | 2.66 | 11900 | 0.2618 | |
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| 0.1813 | 2.67 | 11950 | 0.2622 | |
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| 0.1859 | 2.68 | 12000 | 0.2619 | |
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| 0.2019 | 2.69 | 12050 | 0.2610 | |
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| 0.2125 | 2.7 | 12100 | 0.2631 | |
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| 0.167 | 2.71 | 12150 | 0.2640 | |
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| 0.1794 | 2.73 | 12200 | 0.2617 | |
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| 0.1767 | 2.74 | 12250 | 0.2616 | |
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| 0.1976 | 2.75 | 12300 | 0.2600 | |
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| 0.1932 | 2.76 | 12350 | 0.2595 | |
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| 0.1949 | 2.77 | 12400 | 0.2580 | |
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| 0.1813 | 2.78 | 12450 | 0.2596 | |
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| 0.1843 | 2.79 | 12500 | 0.2598 | |
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| 0.1739 | 2.8 | 12550 | 0.2604 | |
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| 0.1925 | 2.81 | 12600 | 0.2587 | |
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| 0.1798 | 2.83 | 12650 | 0.2589 | |
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| 0.1734 | 2.84 | 12700 | 0.2600 | |
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| 0.1962 | 2.85 | 12750 | 0.2580 | |
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| 0.1684 | 2.86 | 12800 | 0.2612 | |
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| 0.1951 | 2.87 | 12850 | 0.2592 | |
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| 0.1765 | 2.88 | 12900 | 0.2590 | |
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| 0.1871 | 2.89 | 12950 | 0.2579 | |
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| 0.1875 | 2.9 | 13000 | 0.2594 | |
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| 0.1792 | 2.91 | 13050 | 0.2570 | |
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| 0.1797 | 2.93 | 13100 | 0.2594 | |
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| 0.1638 | 2.94 | 13150 | 0.2584 | |
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| 0.1846 | 2.95 | 13200 | 0.2575 | |
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| 0.1722 | 2.96 | 13250 | 0.2570 | |
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| 0.1811 | 2.97 | 13300 | 0.2581 | |
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| 0.173 | 2.98 | 13350 | 0.2578 | |
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| 0.2 | 2.99 | 13400 | 0.2575 | |
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| 0.1744 | 3.0 | 13450 | 0.2653 | |
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| 0.1266 | 3.02 | 13500 | 0.2777 | |
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| 0.1407 | 3.03 | 13550 | 0.2771 | |
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| 0.1258 | 3.04 | 13600 | 0.2740 | |
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| 0.1296 | 3.05 | 13650 | 0.2770 | |
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| 0.1325 | 3.06 | 13700 | 0.2741 | |
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| 0.1332 | 3.07 | 13750 | 0.2789 | |
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| 0.1314 | 3.08 | 13800 | 0.2751 | |
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| 0.1261 | 3.09 | 13850 | 0.2764 | |
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| 0.131 | 3.1 | 13900 | 0.2771 | |
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| 0.1222 | 3.12 | 13950 | 0.2795 | |
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| 0.1269 | 3.13 | 14000 | 0.2766 | |
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| 0.1352 | 3.14 | 14050 | 0.2780 | |
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| 0.1355 | 3.15 | 14100 | 0.2791 | |
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| 0.1362 | 3.16 | 14150 | 0.2794 | |
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| 0.1319 | 3.17 | 14200 | 0.2772 | |
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| 0.1177 | 3.18 | 14250 | 0.2765 | |
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| 0.1339 | 3.19 | 14300 | 0.2800 | |
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| 0.1422 | 3.21 | 14350 | 0.2773 | |
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| 0.1295 | 3.22 | 14400 | 0.2770 | |
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| 0.1413 | 3.23 | 14450 | 0.2751 | |
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| 0.1296 | 3.24 | 14500 | 0.2777 | |
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| 0.1318 | 3.25 | 14550 | 0.2743 | |
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| 0.1341 | 3.26 | 14600 | 0.2760 | |
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| 0.1455 | 3.27 | 14650 | 0.2751 | |
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| 0.1349 | 3.28 | 14700 | 0.2764 | |
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| 0.1356 | 3.29 | 14750 | 0.2793 | |
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| 0.1337 | 3.31 | 14800 | 0.2746 | |
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| 0.1338 | 3.32 | 14850 | 0.2777 | |
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| 0.1392 | 3.33 | 14900 | 0.2773 | |
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| 0.1294 | 3.34 | 14950 | 0.2789 | |
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| 0.1313 | 3.35 | 15000 | 0.2799 | |
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| 0.128 | 3.36 | 15050 | 0.2819 | |
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| 0.1351 | 3.37 | 15100 | 0.2771 | |
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| 0.1298 | 3.38 | 15150 | 0.2785 | |
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| 0.13 | 3.4 | 15200 | 0.2779 | |
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| 0.1413 | 3.41 | 15250 | 0.2761 | |
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| 0.1324 | 3.42 | 15300 | 0.2770 | |
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| 0.1517 | 3.43 | 15350 | 0.2758 | |
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| 0.1323 | 3.44 | 15400 | 0.2764 | |
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| 0.1289 | 3.45 | 15450 | 0.2783 | |
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| 0.1281 | 3.46 | 15500 | 0.2784 | |
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| 0.1268 | 3.47 | 15550 | 0.2767 | |
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| 0.1349 | 3.48 | 15600 | 0.2770 | |
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| 0.1277 | 3.5 | 15650 | 0.2772 | |
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| 0.1271 | 3.51 | 15700 | 0.2766 | |
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| 0.1333 | 3.52 | 15750 | 0.2769 | |
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| 0.1262 | 3.53 | 15800 | 0.2759 | |
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| 0.1596 | 3.54 | 15850 | 0.2739 | |
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| 0.1246 | 3.55 | 15900 | 0.2744 | |
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| 0.1387 | 3.56 | 15950 | 0.2780 | |
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| 0.1366 | 3.57 | 16000 | 0.2759 | |
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| 0.1302 | 3.58 | 16050 | 0.2763 | |
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| 0.1309 | 3.6 | 16100 | 0.2761 | |
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| 0.13 | 3.61 | 16150 | 0.2763 | |
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| 0.1289 | 3.62 | 16200 | 0.2753 | |
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| 0.1271 | 3.63 | 16250 | 0.2755 | |
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| 0.1255 | 3.64 | 16300 | 0.2730 | |
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| 0.1275 | 3.65 | 16350 | 0.2725 | |
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| 0.1323 | 3.66 | 16400 | 0.2730 | |
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| 0.1233 | 3.67 | 16450 | 0.2753 | |
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| 0.1256 | 3.69 | 16500 | 0.2733 | |
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| 0.1487 | 3.7 | 16550 | 0.2741 | |
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| 0.1366 | 3.71 | 16600 | 0.2741 | |
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| 0.1495 | 3.72 | 16650 | 0.2743 | |
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| 0.1372 | 3.73 | 16700 | 0.2737 | |
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| 0.142 | 3.74 | 16750 | 0.2715 | |
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| 0.1403 | 3.75 | 16800 | 0.2724 | |
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| 0.1321 | 3.76 | 16850 | 0.2714 | |
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| 0.1313 | 3.77 | 16900 | 0.2733 | |
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| 0.1326 | 3.79 | 16950 | 0.2756 | |
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| 0.1263 | 3.8 | 17000 | 0.2746 | |
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| 0.1193 | 3.81 | 17050 | 0.2726 | |
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| 0.1347 | 3.82 | 17100 | 0.2713 | |
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| 0.13 | 3.83 | 17150 | 0.2733 | |
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| 0.1431 | 3.84 | 17200 | 0.2725 | |
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| 0.1277 | 3.85 | 17250 | 0.2730 | |
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| 0.131 | 3.86 | 17300 | 0.2720 | |
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| 0.1382 | 3.88 | 17350 | 0.2715 | |
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| 0.1322 | 3.89 | 17400 | 0.2710 | |
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| 0.1232 | 3.9 | 17450 | 0.2726 | |
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| 0.1308 | 3.91 | 17500 | 0.2716 | |
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| 0.1285 | 3.92 | 17550 | 0.2709 | |
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| 0.1342 | 3.93 | 17600 | 0.2719 | |
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| 0.1279 | 3.94 | 17650 | 0.2731 | |
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| 0.1294 | 3.95 | 17700 | 0.2740 | |
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| 0.1244 | 3.96 | 17750 | 0.2729 | |
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| 0.1307 | 3.98 | 17800 | 0.2704 | |
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| 0.1291 | 3.99 | 17850 | 0.2707 | |
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| 0.1231 | 4.0 | 17900 | 0.2711 | |
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| 0.105 | 4.01 | 17950 | 0.2896 | |
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| 0.099 | 4.02 | 18000 | 0.2944 | |
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| 0.0914 | 4.03 | 18050 | 0.2960 | |
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| 0.0903 | 4.04 | 18100 | 0.2945 | |
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| 0.1024 | 4.05 | 18150 | 0.2947 | |
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| 0.0937 | 4.07 | 18200 | 0.2993 | |
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| 0.0908 | 4.08 | 18250 | 0.2991 | |
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| 0.1044 | 4.09 | 18300 | 0.2966 | |
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| 0.1023 | 4.1 | 18350 | 0.2945 | |
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| 0.0961 | 4.11 | 18400 | 0.2979 | |
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| 0.0955 | 4.12 | 18450 | 0.2977 | |
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| 0.098 | 4.13 | 18500 | 0.2962 | |
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| 0.091 | 4.14 | 18550 | 0.2959 | |
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| 0.0855 | 4.15 | 18600 | 0.2998 | |
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| 0.0882 | 4.17 | 18650 | 0.2971 | |
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| 0.1019 | 4.18 | 18700 | 0.2987 | |
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| 0.0969 | 4.19 | 18750 | 0.2985 | |
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| 0.0875 | 4.2 | 18800 | 0.2994 | |
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| 0.0892 | 4.21 | 18850 | 0.2992 | |
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| 0.0849 | 4.22 | 18900 | 0.3009 | |
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| 0.0886 | 4.23 | 18950 | 0.2979 | |
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| 0.092 | 4.24 | 19000 | 0.2960 | |
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| 0.0959 | 4.26 | 19050 | 0.2969 | |
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| 0.0957 | 4.27 | 19100 | 0.2965 | |
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| 0.0953 | 4.28 | 19150 | 0.2989 | |
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| 0.0977 | 4.29 | 19200 | 0.2963 | |
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| 0.0917 | 4.3 | 19250 | 0.2989 | |
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| 0.0992 | 4.31 | 19300 | 0.3003 | |
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| 0.0912 | 4.32 | 19350 | 0.2972 | |
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| 0.0889 | 4.33 | 19400 | 0.2973 | |
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| 0.0901 | 4.34 | 19450 | 0.2966 | |
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| 0.0913 | 4.36 | 19500 | 0.2991 | |
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| 0.0886 | 4.37 | 19550 | 0.2974 | |
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| 0.0858 | 4.38 | 19600 | 0.2968 | |
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| 0.0905 | 4.39 | 19650 | 0.2959 | |
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| 0.0916 | 4.4 | 19700 | 0.2986 | |
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| 0.0885 | 4.41 | 19750 | 0.2984 | |
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| 0.0933 | 4.42 | 19800 | 0.2981 | |
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| 0.086 | 4.43 | 19850 | 0.2957 | |
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| 0.0975 | 4.44 | 19900 | 0.2986 | |
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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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- PEFT 0.10.0 |
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- Transformers 4.39.3 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
