{ "run_info": { "created_at": "2026-08-06T12:43:21+00:00", "total_time": 1532.9845309570082, "experiment_name": "lokr/llama-3.2-3B-rank32-factor8-lr0.003", "peft_branch": "auto-research", "train_config": { "model_id": "meta-llama/Llama-3.2-3B", "dtype": "bfloat16", "max_seq_length": 768, "batch_size": 4, "batch_size_eval": 50, "max_steps": 5000, "eval_steps": 250, "compile": false, "use_gc": false, "query_template": "Question: {query} Think step by step.\nAnswer:", "seed": 0, "grad_norm_clip": 1.0, "optimizer_type": "AdamW", "optimizer_kwargs": { "lr": 0.003, "weight_decay": 0.1 }, "lr_scheduler": "cosine", "use_amp": false, "autocast_adapter_dtype": true, "generation_kwargs": { "max_length": 800, "max_new_tokens": 300 }, "attn_implementation": null, "init_kv_cache_prefix": null }, "peft_config": { "task_type": null, "peft_type": "LOKR", "auto_mapping": null, "peft_version": "0.20.1.dev0@UNKNOWN", "base_model_name_or_path": "meta-llama/Llama-3.2-3B", "revision": null, "inference_mode": false, "rank_pattern": {}, "alpha_pattern": {}, "r": 32, "alpha": 64, "rank_dropout": 0.0, "module_dropout": 0.0, "use_effective_conv2d": false, "decompose_both": false, "decompose_factor": 8, "rank_dropout_scale": false, "target_modules": [ "q_proj", "v_proj" ], "exclude_modules": null, "init_weights": true, "layers_to_transform": null, "layers_pattern": null, "modules_to_save": null }, "error_msg": "" }, "train_info": { "accelerator_memory_reserved_avg": 15824497462, "accelerator_memory_max": 23595057152, "accelerator_memory_reserved_99th": 21386756096, "train_time": 1307.3613977189816, "file_size": 4622968, "num_trainable_params": 1150464, "num_total_params": 3213900288, "status": "success", "metrics": [ { "step": 250, "valid accuracy": 0.32, "train loss": 0.9270877740383148, "train samples": 1000, "train time": 43.66479822300607, "eval time": 13.922552911011735, "tokens / sec": 4848.73418900742, "mem allocated avg": 6799740565.504, "mem reserved avg": 15942247514.112, "elapsed time": 85.75519717100542 }, { "step": 500, "valid accuracy": 0.34, "train loss": 0.7118661236763001, "train samples": 2000, "train time": 43.944341480208095, "eval time": 13.804070371988928, "tokens / sec": 4733.146361828587, "mem allocated avg": 6792644532.224, "mem reserved avg": 15596393594.88, "elapsed time": 147.75061033500242 }, { "step": 750, "valid accuracy": 0.28, "train loss": 0.693268860578537, "train samples": 3000, "train time": 45.00842113170074, "eval time": 13.829937142989365, "tokens / sec": 4763.575229014002, "mem allocated avg": 6802870536.192, "mem reserved avg": 15802895958.016, "elapsed time": 210.7075444869988 }, { "step": 1000, "valid accuracy": 0.32, "train loss": 0.6756969265937806, "train samples": 4000, "train time": 43.577776318008546, "eval time": 10.035979694977868, "tokens / sec": 4780.785473762346, "mem allocated avg": 6793522110.464, "mem reserved avg": 15816049295.36, "elapsed time": 268.5969132730097 }, { "step": 1250, "valid accuracy": 0.32, "train loss": 0.6747316555976868, "train samples": 5000, "train time": 43.6757008919958, "eval time": 10.33713387500029, "tokens / sec": 4774.691550244076, "mem allocated avg": 6794507005.952, "mem reserved avg": 15854636892.16, "elapsed time": 326.7247922690003 }, { "step": 1500, "valid accuracy": 0.42, "train loss": 0.6669513373374939, "train samples": 6000, "train time": 44.722955610981444, "eval time": 8.636160207999637, "tokens / sec": 4680.616411420718, "mem allocated avg": 6795964114.944, "mem reserved avg": 15784088698.88, "elapsed time": 384.3359192000062 }, { "step": 1750, "valid accuracy": 0.46, "train loss": 0.6600646764039994, "train samples": 7000, "train time": 44.147544838750036, "eval time": 7.810703630006174, "tokens / sec": 4742.166314450195, "mem allocated avg": 6797846458.368, "mem reserved avg": 16197387026.432, "elapsed time": 440.50814956301474 }, { "step": 2000, "valid accuracy": 0.46, "train loss": 0.6624095524549485, "train samples": 8000, "train time": 43.98306571893045, "eval time": 7.598463203001302, "tokens / sec": 4722.181062303872, "mem allocated avg": 6793247461.376, "mem reserved avg": 15799850893.312, "elapsed time": 496.3889749700029 }, { "step": 2250, "valid accuracy": 0.36, "train loss": 0.6519601926803589, "train samples": 9000, "train time": 45.462686326907715, "eval time": 13.740995499014389, "tokens / sec": 4728.009217369544, "mem allocated avg": 6804674760.704, "mem reserved avg": 16098552446.976, "elapsed time": 559.7353278819937 }, { "step": 2500, "valid accuracy": 0.38, "train loss": 0.6490274410247803, "train samples": 10000, "train time": 42.95588268118445, "eval time": 13.741985282016685, "tokens / sec": 4794.84967236438, "mem allocated avg": 6790849527.808, "mem reserved avg": 15565380911.104, "elapsed time": 620.6423299649905 }, { "step": 2750, "valid accuracy": 0.38, "train loss": 0.638805770277977, "train samples": 11000, "train time": 44.075625506957294, "eval time": 9.21670454001287, "tokens / sec": 4807.214816873213, "mem allocated avg": 6800556472.32, "mem reserved avg": 15965735616.512, "elapsed time": 678.0697450590087 }, { "step": 3000, "valid accuracy": 0.44, "train loss": 0.6281948779821396, "train samples": 12000, "train time": 43.90088801126694, "eval time": 10.656771742011188, "tokens / sec": 4754.5963067177645, "mem allocated avg": 6795873429.504, "mem reserved avg": 15874777939.968, "elapsed time": 736.8918209109979 }, { "step": 3250, "valid accuracy": 0.5, "train loss": 0.6351900390386581, "train samples": 13000, "train time": 44.91159329522634, "eval time": 13.774559659010265, "tokens / sec": 4695.91445161258, "mem allocated avg": 6798974142.464, "mem reserved avg": 15770885029.888, "elapsed time": 799.6646873739955 }, { "step": 3500, "valid accuracy": 0.52, "train loss": 0.6157620249986648, "train samples": 14000, "train time": 43.8277162159211, "eval time": 10.279233909997856, "tokens / sec": 4785.784387364565, "mem allocated avg": 6796146567.168, "mem reserved avg": 15755340939.264, "elapsed time": 858.011582512001 }, { "step": 3750, "valid accuracy": 0.54, "train loss": 0.6115566066503525, "train samples": 15000, "train time": 44.967253953713225, "eval time": 13.822728877014015, "tokens / sec": 4819.12905384576, "mem allocated avg": 6807568994.304, "mem reserved avg": 16073713778.688, "elapsed time": 921.0013866620138 }, { "step": 4000, "valid accuracy": 0.38, "train loss": 0.6212958168983459, "train samples": 16000, "train time": 43.98874276672723, "eval time": 13.764712378993863, "tokens / sec": 4646.029578153488, "mem allocated avg": 6788096286.72, "mem reserved avg": 15774408245.248, "elapsed time": 983.0344113839965 }, { "step": 4250, "valid accuracy": 0.44, "train loss": 0.6039810788631439, "train samples": 17000, "train time": 43.837045381893404, "eval time": 10.33728496299591, "tokens / sec": 4822.154370999484, "mem allocated avg": 6799123298.304, "mem reserved avg": 15757891076.096, "elapsed time": 1041.2764754859963 }, { "step": 4500, "valid accuracy": 0.52, "train loss": 0.6095903199911118, "train samples": 18000, "train time": 43.668030562083004, "eval time": 7.992580848978832, "tokens / sec": 4759.04219459919, "mem allocated avg": 6794387621.888, "mem reserved avg": 15730720374.784, "elapsed time": 1097.2214920280094 }, { "step": 4750, "valid accuracy": 0.44, "train loss": 0.6002804050445557, "train samples": 19000, "train time": 44.70480700198095, "eval time": 8.954350112006068, "tokens / sec": 4696.116907309257, "mem allocated avg": 6796872839.168, "mem reserved avg": 15848370601.984, "elapsed time": 1155.0104628030094 }, { "step": 5000, "valid accuracy": 0.44, "train loss": 0.6074805817604065, "train samples": 20000, "train time": 43.53095386302448, "eval time": 9.616009549994487, "tokens / sec": 4784.641307318437, "mem allocated avg": 6793322434.56, "mem reserved avg": 15480622415.872, "elapsed time": 1212.3254529940023 }, { "step": 5000, "test accuracy": 0.4533737680060652, "train loss": 0.6074805817604065, "train samples": 20000, "train total tokens": 4198051, "forgetting": 0.12120223045349121 } ] }, "meta_info": { "model_info": { "sha": "13afe5124825b4f3751f836b40dafda64c1ed062", "created_at": "2024-09-18T15:23:48+00:00" }, "dataset_info": { "metamath": { "sha": "aa4f34d3d2d3231299b5b03d9b3e5a20da45aa18", "created_at": "2023-09-21T17:22:46+00:00" }, "gsm8k": { "sha": "740312add88f781978c0658806c59bc2815b9866", "created_at": "2022-04-12T10:22:10+00:00" } }, "package_info": { "transformers-version": "5.12.1", "transformers-commit-hash": null, "peft-version": "0.20.1.dev0", "peft-commit-hash": "c702de402330f48c0d8b1f260d59413aa3110b65", "datasets-version": "4.8.4", "datasets-commit-hash": null, "bitsandbytes-version": "0.49.2", "bitsandbytes-commit-hash": null, "torch-version": "2.11.0+cu130", "torch-commit-hash": null }, "system_info": { "system": "Linux", "release": "7.0.0-1009-aws", "version": "#9~24.04.1-Ubuntu SMP PREEMPT Mon Jul 13 22:43:41 UTC 2026", "machine": "x86_64", "processor": "x86_64", "accelerator": "NVIDIA L40S" }, "pytorch_info": "PyTorch built with:\n - GCC 13.3\n - C++ Version: 201703\n - Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications\n - Intel(R) MKL-DNN v3.10.2 (Git Hash f1d471933dc852f956fd05389f9313c7148783d5)\n - OpenMP 201511 (a.k.a. OpenMP 4.5)\n - LAPACK is enabled (usually provided by MKL)\n - NNPACK is enabled\n - CPU capability usage: AVX2\n - CUDA Runtime 13.0\n - NVCC architecture flags: -gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_90,code=sm_90;-gencode;arch=compute_100,code=sm_100;-gencode;arch=compute_120,code=sm_120\n - CuDNN 90.7.1 (built against CUDA 12.8)\n - Built with CuDNN 91.9\n - Magma 2.6.1\n - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, COMMIT_SHA=70d99e998b4955e0049d13a98d77ae1b14db1f45, CUDA_VERSION=13.0, CUDNN_VERSION=9.19.0, CXX_COMPILER=/opt/rh/gcc-toolset-13/root/usr/bin/c++, CXX_FLAGS= -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DLIBKINETO_NOXPUPTI=ON -DUSE_FBGEMM -DUSE_MSLK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -DC10_NODEPRECATED -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=range-loop-construct -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-unknown-pragmas -Wno-unused-parameter -Wno-strict-overflow -Wno-strict-aliasing -Wno-stringop-overflow -Wsuggest-override -Wno-psabi -Wno-error=old-style-cast -faligned-new -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-dangling-reference -Wno-error=dangling-reference -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, TORCH_VERSION=2.11.0, USE_CUDA=ON, USE_CUDNN=ON, USE_CUSPARSELT=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=1, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF, USE_XCCL=OFF, USE_XPU=OFF, \n" } }