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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: 0.2772 |
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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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| 0.248 | 1.61 | 8000 | 0.2689 | |
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| 0.2504 | 1.62 | 8050 | 0.2705 | |
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| 0.2309 | 1.63 | 8100 | 0.2696 | |
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| 0.2499 | 1.64 | 8150 | 0.2682 | |
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| 0.2602 | 1.65 | 8200 | 0.2700 | |
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| 0.2437 | 1.66 | 8250 | 0.2695 | |
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| 0.2156 | 1.67 | 8300 | 0.2700 | |
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| 0.2584 | 1.68 | 8350 | 0.2669 | |
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| 0.2476 | 1.69 | 8400 | 0.2667 | |
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| 0.2915 | 1.7 | 8450 | 0.2677 | |
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| 0.239 | 1.71 | 8500 | 0.2680 | |
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| 0.2473 | 1.72 | 8550 | 0.2662 | |
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| 0.2408 | 1.73 | 8600 | 0.2662 | |
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| 0.256 | 1.74 | 8650 | 0.2668 | |
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| 0.2457 | 1.75 | 8700 | 0.2667 | |
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| 0.2562 | 1.76 | 8750 | 0.2653 | |
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| 0.2434 | 1.77 | 8800 | 0.2653 | |
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| 0.2687 | 1.78 | 8850 | 0.2640 | |
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| 0.2679 | 1.79 | 8900 | 0.2637 | |
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| 0.2444 | 1.8 | 8950 | 0.2659 | |
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| 0.2719 | 1.81 | 9000 | 0.2645 | |
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| 0.2236 | 1.82 | 9050 | 0.2648 | |
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| 0.2385 | 1.83 | 9100 | 0.2648 | |
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| 0.2592 | 1.84 | 9150 | 0.2638 | |
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| 0.2652 | 1.85 | 9200 | 0.2645 | |
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| 0.2418 | 1.86 | 9250 | 0.2637 | |
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| 0.2393 | 1.87 | 9300 | 0.2630 | |
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| 0.237 | 1.88 | 9350 | 0.2643 | |
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| 0.2365 | 1.89 | 9400 | 0.2642 | |
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| 0.2402 | 1.9 | 9450 | 0.2629 | |
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| 0.2395 | 1.91 | 9500 | 0.2624 | |
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| 0.2351 | 1.92 | 9550 | 0.2626 | |
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| 0.2507 | 1.93 | 9600 | 0.2620 | |
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| 0.2343 | 1.94 | 9650 | 0.2619 | |
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| 0.2202 | 1.95 | 9700 | 0.2621 | |
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| 0.2429 | 1.96 | 9750 | 0.2616 | |
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| 0.2747 | 1.97 | 9800 | 0.2601 | |
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| 0.2192 | 1.98 | 9850 | 0.2612 | |
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| 0.2421 | 1.99 | 9900 | 0.2597 | |
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| 0.2349 | 2.0 | 9950 | 0.2597 | |
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| 0.1913 | 2.01 | 10000 | 0.2672 | |
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| 0.1903 | 2.02 | 10050 | 0.2710 | |
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| 0.1823 | 2.03 | 10100 | 0.2695 | |
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| 0.1738 | 2.04 | 10150 | 0.2682 | |
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| 0.1984 | 2.05 | 10200 | 0.2691 | |
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| 0.1769 | 2.06 | 10250 | 0.2703 | |
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| 0.1934 | 2.07 | 10300 | 0.2709 | |
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| 0.1715 | 2.08 | 10350 | 0.2705 | |
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| 0.1896 | 2.09 | 10400 | 0.2700 | |
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| 0.1887 | 2.1 | 10450 | 0.2693 | |
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| 0.1683 | 2.11 | 10500 | 0.2722 | |
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| 0.1919 | 2.12 | 10550 | 0.2727 | |
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| 0.1901 | 2.13 | 10600 | 0.2729 | |
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| 0.1628 | 2.14 | 10650 | 0.2711 | |
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| 0.172 | 2.15 | 10700 | 0.2692 | |
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| 0.1807 | 2.16 | 10750 | 0.2690 | |
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| 0.1778 | 2.17 | 10800 | 0.2693 | |
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| 0.1773 | 2.18 | 10850 | 0.2704 | |
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| 0.182 | 2.19 | 10900 | 0.2701 | |
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| 0.1843 | 2.2 | 10950 | 0.2710 | |
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| 0.1786 | 2.21 | 11000 | 0.2685 | |
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| 0.1924 | 2.22 | 11050 | 0.2690 | |
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| 0.1903 | 2.23 | 11100 | 0.2711 | |
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| 0.1907 | 2.24 | 11150 | 0.2675 | |
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| 0.1685 | 2.25 | 11200 | 0.2694 | |
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| 0.1789 | 2.26 | 11250 | 0.2675 | |
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| 0.1741 | 2.27 | 11300 | 0.2692 | |
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| 0.1743 | 2.28 | 11350 | 0.2702 | |
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| 0.1665 | 2.29 | 11400 | 0.2693 | |
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| 0.1643 | 2.3 | 11450 | 0.2713 | |
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| 0.1958 | 2.31 | 11500 | 0.2690 | |
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| 0.1837 | 2.32 | 11550 | 0.2701 | |
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| 0.1953 | 2.33 | 11600 | 0.2702 | |
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| 0.1804 | 2.34 | 11650 | 0.2694 | |
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| 0.1829 | 2.35 | 11700 | 0.2666 | |
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| 0.1851 | 2.36 | 11750 | 0.2673 | |
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| 0.1883 | 2.37 | 11800 | 0.2681 | |
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| 0.2057 | 2.38 | 11850 | 0.2664 | |
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| 0.1972 | 2.39 | 11900 | 0.2663 | |
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| 0.1803 | 2.4 | 11950 | 0.2653 | |
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| 0.1743 | 2.41 | 12000 | 0.2671 | |
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| 0.1771 | 2.42 | 12050 | 0.2679 | |
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| 0.1695 | 2.43 | 12100 | 0.2658 | |
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| 0.2055 | 2.44 | 12150 | 0.2652 | |
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| 0.2058 | 2.45 | 12200 | 0.2653 | |
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| 0.1944 | 2.46 | 12250 | 0.2640 | |
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| 0.1901 | 2.47 | 12300 | 0.2656 | |
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| 0.1669 | 2.48 | 12350 | 0.2650 | |
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| 0.1843 | 2.49 | 12400 | 0.2681 | |
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| 0.173 | 2.5 | 12450 | 0.2664 | |
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| 0.195 | 2.51 | 12500 | 0.2633 | |
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| 0.1701 | 2.52 | 12550 | 0.2640 | |
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| 0.206 | 2.53 | 12600 | 0.2635 | |
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| 0.1826 | 2.54 | 12650 | 0.2659 | |
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| 0.1903 | 2.55 | 12700 | 0.2655 | |
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| 0.1761 | 2.56 | 12750 | 0.2651 | |
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| 0.2037 | 2.57 | 12800 | 0.2650 | |
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| 0.1924 | 2.58 | 12850 | 0.2644 | |
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| 0.192 | 2.59 | 12900 | 0.2653 | |
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| 0.1828 | 2.6 | 12950 | 0.2646 | |
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| 0.1831 | 2.61 | 13000 | 0.2662 | |
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| 0.1796 | 2.62 | 13050 | 0.2633 | |
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| 0.1905 | 2.63 | 13100 | 0.2632 | |
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| 0.1946 | 2.64 | 13150 | 0.2616 | |
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| 0.1722 | 2.65 | 13200 | 0.2642 | |
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| 0.1711 | 2.66 | 13250 | 0.2637 | |
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| 0.1939 | 2.67 | 13300 | 0.2633 | |
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| 0.194 | 2.68 | 13350 | 0.2632 | |
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| 0.1856 | 2.69 | 13400 | 0.2625 | |
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| 0.1949 | 2.7 | 13450 | 0.2612 | |
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| 0.1796 | 2.71 | 13500 | 0.2610 | |
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| 0.1805 | 2.72 | 13550 | 0.2618 | |
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| 0.1731 | 2.73 | 13600 | 0.2619 | |
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| 0.1961 | 2.74 | 13650 | 0.2612 | |
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| 0.1849 | 2.75 | 13700 | 0.2622 | |
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| 0.1715 | 2.76 | 13750 | 0.2615 | |
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| 0.1888 | 2.77 | 13800 | 0.2638 | |
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| 0.1766 | 2.78 | 13850 | 0.2625 | |
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| 0.166 | 2.79 | 13900 | 0.2631 | |
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| 0.1761 | 2.8 | 13950 | 0.2609 | |
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| 0.179 | 2.81 | 14000 | 0.2610 | |
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| 0.1653 | 2.82 | 14050 | 0.2621 | |
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| 0.1809 | 2.83 | 14100 | 0.2614 | |
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| 0.1747 | 2.84 | 14150 | 0.2608 | |
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| 0.1876 | 2.85 | 14200 | 0.2593 | |
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| 0.1709 | 2.86 | 14250 | 0.2611 | |
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| 0.1722 | 2.87 | 14300 | 0.2600 | |
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| 0.1779 | 2.88 | 14350 | 0.2592 | |
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| 0.1819 | 2.89 | 14400 | 0.2610 | |
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| 0.1805 | 2.9 | 14450 | 0.2596 | |
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| 0.1561 | 2.91 | 14500 | 0.2609 | |
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| 0.1891 | 2.92 | 14550 | 0.2605 | |
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| 0.1915 | 2.93 | 14600 | 0.2584 | |
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| 0.1752 | 2.94 | 14650 | 0.2589 | |
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| 0.1852 | 2.95 | 14700 | 0.2592 | |
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| 0.17 | 2.96 | 14750 | 0.2602 | |
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| 0.1745 | 2.97 | 14800 | 0.2592 | |
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| 0.195 | 2.98 | 14850 | 0.2582 | |
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| 0.1782 | 2.99 | 14900 | 0.2590 | |
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| 0.1656 | 3.0 | 14950 | 0.2651 | |
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| 0.1196 | 3.01 | 15000 | 0.2754 | |
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| 0.1178 | 3.02 | 15050 | 0.2792 | |
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| 0.1238 | 3.03 | 15100 | 0.2791 | |
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| 0.1254 | 3.04 | 15150 | 0.2777 | |
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| 0.1223 | 3.05 | 15200 | 0.2796 | |
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| 0.13 | 3.06 | 15250 | 0.2785 | |
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| 0.1215 | 3.07 | 15300 | 0.2784 | |
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| 0.1091 | 3.08 | 15350 | 0.2774 | |
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| 0.1207 | 3.09 | 15400 | 0.2796 | |
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| 0.1169 | 3.1 | 15450 | 0.2793 | |
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| 0.1228 | 3.11 | 15500 | 0.2810 | |
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| 0.1247 | 3.12 | 15550 | 0.2803 | |
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| 0.1321 | 3.13 | 15600 | 0.2779 | |
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| 0.132 | 3.14 | 15650 | 0.2790 | |
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| 0.144 | 3.15 | 15700 | 0.2793 | |
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| 0.1313 | 3.16 | 15750 | 0.2800 | |
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| 0.1216 | 3.17 | 15800 | 0.2829 | |
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| 0.1235 | 3.18 | 15850 | 0.2817 | |
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| 0.1254 | 3.19 | 15900 | 0.2801 | |
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| 0.1201 | 3.2 | 15950 | 0.2812 | |
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| 0.1202 | 3.21 | 16000 | 0.2790 | |
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| 0.1322 | 3.22 | 16050 | 0.2768 | |
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| 0.1241 | 3.23 | 16100 | 0.2786 | |
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| 0.1195 | 3.24 | 16150 | 0.2811 | |
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| 0.1122 | 3.25 | 16200 | 0.2794 | |
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| 0.1158 | 3.27 | 16250 | 0.2767 | |
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| 0.1178 | 3.28 | 16300 | 0.2787 | |
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| 0.129 | 3.29 | 16350 | 0.2778 | |
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| 0.1278 | 3.3 | 16400 | 0.2776 | |
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| 0.1199 | 3.31 | 16450 | 0.2770 | |
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| 0.1128 | 3.32 | 16500 | 0.2803 | |
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| 0.1292 | 3.33 | 16550 | 0.2794 | |
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| 0.1228 | 3.34 | 16600 | 0.2803 | |
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| 0.1263 | 3.35 | 16650 | 0.2795 | |
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| 0.1285 | 3.36 | 16700 | 0.2798 | |
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| 0.1342 | 3.37 | 16750 | 0.2815 | |
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| 0.1104 | 3.38 | 16800 | 0.2813 | |
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| 0.131 | 3.39 | 16850 | 0.2789 | |
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| 0.1248 | 3.4 | 16900 | 0.2794 | |
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| 0.1222 | 3.41 | 16950 | 0.2803 | |
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| 0.1256 | 3.42 | 17000 | 0.2784 | |
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| 0.1226 | 3.43 | 17050 | 0.2788 | |
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| 0.115 | 3.44 | 17100 | 0.2785 | |
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| 0.1338 | 3.45 | 17150 | 0.2787 | |
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| 0.1428 | 3.46 | 17200 | 0.2784 | |
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| 0.1192 | 3.47 | 17250 | 0.2788 | |
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| 0.1235 | 3.48 | 17300 | 0.2796 | |
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| 0.1297 | 3.49 | 17350 | 0.2795 | |
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| 0.1223 | 3.5 | 17400 | 0.2803 | |
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| 0.1248 | 3.51 | 17450 | 0.2788 | |
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| 0.1342 | 3.52 | 17500 | 0.2799 | |
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| 0.1224 | 3.53 | 17550 | 0.2774 | |
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| 0.1175 | 3.54 | 17600 | 0.2802 | |
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| 0.1278 | 3.55 | 17650 | 0.2802 | |
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| 0.1052 | 3.56 | 17700 | 0.2785 | |
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| 0.1141 | 3.57 | 17750 | 0.2772 | |
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| 0.1245 | 3.58 | 17800 | 0.2792 | |
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| 0.1246 | 3.59 | 17850 | 0.2780 | |
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| 0.1193 | 3.6 | 17900 | 0.2777 | |
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| 0.1159 | 3.61 | 17950 | 0.2791 | |
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| 0.1314 | 3.62 | 18000 | 0.2777 | |
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| 0.1214 | 3.63 | 18050 | 0.2784 | |
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| 0.1213 | 3.64 | 18100 | 0.2784 | |
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| 0.1237 | 3.65 | 18150 | 0.2789 | |
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| 0.1207 | 3.66 | 18200 | 0.2777 | |
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| 0.1158 | 3.67 | 18250 | 0.2782 | |
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| 0.1185 | 3.68 | 18300 | 0.2776 | |
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| 0.124 | 3.69 | 18350 | 0.2776 | |
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| 0.1186 | 3.7 | 18400 | 0.2777 | |
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| 0.1133 | 3.71 | 18450 | 0.2778 | |
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| 0.1203 | 3.72 | 18500 | 0.2772 | |
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| 0.1173 | 3.73 | 18550 | 0.2781 | |
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| 0.1211 | 3.74 | 18600 | 0.2774 | |
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| 0.1317 | 3.75 | 18650 | 0.2768 | |
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| 0.1147 | 3.76 | 18700 | 0.2769 | |
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| 0.1136 | 3.77 | 18750 | 0.2772 | |
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| 0.1169 | 3.78 | 18800 | 0.2774 | |
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| 0.1111 | 3.79 | 18850 | 0.2781 | |
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| 0.1183 | 3.8 | 18900 | 0.2767 | |
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| 0.116 | 3.81 | 18950 | 0.2768 | |
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| 0.1128 | 3.82 | 19000 | 0.2778 | |
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| 0.1048 | 3.83 | 19050 | 0.2780 | |
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| 0.125 | 3.84 | 19100 | 0.2781 | |
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| 0.1168 | 3.85 | 19150 | 0.2776 | |
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| 0.1205 | 3.86 | 19200 | 0.2773 | |
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| 0.1313 | 3.87 | 19250 | 0.2768 | |
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| 0.1136 | 3.88 | 19300 | 0.2766 | |
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| 0.122 | 3.89 | 19350 | 0.2766 | |
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| 0.117 | 3.9 | 19400 | 0.2765 | |
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| 0.1194 | 3.91 | 19450 | 0.2764 | |
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| 0.122 | 3.92 | 19500 | 0.2768 | |
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| 0.1277 | 3.93 | 19550 | 0.2766 | |
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| 0.1131 | 3.94 | 19600 | 0.2768 | |
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| 0.1242 | 3.95 | 19650 | 0.2770 | |
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| 0.128 | 3.96 | 19700 | 0.2769 | |
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| 0.1282 | 3.97 | 19750 | 0.2769 | |
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| 0.1187 | 3.98 | 19800 | 0.2771 | |
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| 0.1221 | 3.99 | 19850 | 0.2772 | |
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| 0.123 | 4.0 | 19900 | 0.2772 | |
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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 |
