{ "run_info": { "created_at": "2026-08-06T10:13:59+00:00", "total_time": 4814.026151216996, "experiment_name": "lokr/llama-3.2-3B-rank32-factor8-all-linear-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": [ "down_proj", "k_proj", "up_proj", "o_proj", "v_proj", "q_proj", "gate_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": 28733233902, "accelerator_memory_max": 40372273152, "accelerator_memory_reserved_99th": 36979081216, "train_time": 4292.985215063964, "file_size": 24437952, "num_trainable_params": 6091008, "num_total_params": 3218840832, "status": "success", "metrics": [ { "step": 250, "valid accuracy": 0.38, "train loss": 0.8615508460998536, "train samples": 1000, "train time": 171.43761316602468, "eval time": 30.569398073013872, "tokens / sec": 1234.9623638014941, "mem allocated avg": 6873432496.128, "mem reserved avg": 28930102788.096, "elapsed time": 233.96793232500204 }, { "step": 500, "valid accuracy": 0.36, "train loss": 0.7002903352975846, "train samples": 2000, "train time": 171.33122572375578, "eval time": 30.383617023995612, "tokens / sec": 1213.993532827219, "mem allocated avg": 6865498011.648, "mem reserved avg": 28395521966.08, "elapsed time": 442.96696859801887 }, { "step": 750, "valid accuracy": 0.26, "train loss": 0.7056614835262298, "train samples": 3000, "train time": 172.8551740029361, "eval time": 30.535659058979945, "tokens / sec": 1240.3504913098996, "mem allocated avg": 6876121849.856, "mem reserved avg": 28633364168.704, "elapsed time": 653.4886630160036 }, { "step": 1000, "valid accuracy": 0.32, "train loss": 0.6885825423002243, "train samples": 4000, "train time": 169.4359879681724, "eval time": 30.406957479019184, "tokens / sec": 1229.5852994296272, "mem allocated avg": 6867443728.384, "mem reserved avg": 28759604330.496, "elapsed time": 860.6749559840246 }, { "step": 1250, "valid accuracy": 0.34, "train loss": 0.6797382447719574, "train samples": 5000, "train time": 168.55452173313824, "eval time": 30.731183161988156, "tokens / sec": 1237.2139166350285, "mem allocated avg": 6867681554.432, "mem reserved avg": 28730613301.248, "elapsed time": 1067.156196824013 }, { "step": 1500, "valid accuracy": 0.42, "train loss": 0.6683728358745575, "train samples": 6000, "train time": 174.49907591292867, "eval time": 30.453326868999284, "tokens / sec": 1199.610937220388, "mem allocated avg": 6869211674.624, "mem reserved avg": 28693585985.536, "elapsed time": 1279.4822671050206 }, { "step": 1750, "valid accuracy": 0.44, "train loss": 0.6583834865093231, "train samples": 7000, "train time": 170.7857195379038, "eval time": 25.239067126007285, "tokens / sec": 1225.834341222752, "mem allocated avg": 6870617331.712, "mem reserved avg": 29237360721.92, "elapsed time": 1482.7154341220157 }, { "step": 2000, "valid accuracy": 0.4, "train loss": 0.6530058711767197, "train samples": 8000, "train time": 170.49540531635284, "eval time": 20.073756367026363, "tokens / sec": 1218.1911859420595, "mem allocated avg": 6866557816.832, "mem reserved avg": 28706730934.272, "elapsed time": 1680.7453745120147 }, { "step": 2250, "valid accuracy": 0.38, "train loss": 0.6375795097351075, "train samples": 9000, "train time": 172.48475469491677, "eval time": 30.480793218011968, "tokens / sec": 1246.185498423848, "mem allocated avg": 6878300321.792, "mem reserved avg": 29174731374.592, "elapsed time": 1890.9911642649968 }, { "step": 2500, "valid accuracy": 0.44, "train loss": 0.6300644111633301, "train samples": 10000, "train time": 170.72695773094893, "eval time": 30.564193555997917, "tokens / sec": 1206.4117040296962, "mem allocated avg": 6863159779.328, "mem reserved avg": 28354786885.632, "elapsed time": 2099.5891719350184 }, { "step": 2750, "valid accuracy": 0.46, "train loss": 0.6156140941381455, "train samples": 11000, "train time": 175.56682728099986, "eval time": 30.624924142000964, "tokens / sec": 1206.839602226668, "mem allocated avg": 6873532012.544, "mem reserved avg": 29056410058.752, "elapsed time": 2313.028025173 }, { "step": 3000, "valid accuracy": 0.4, "train loss": 0.6006648186445236, "train samples": 12000, "train time": 168.66434494018904, "eval time": 18.980127498012735, "tokens / sec": 1237.5526082529132, "mem allocated avg": 6868978239.488, "mem reserved avg": 28823433248.768, "elapsed time": 2508.053776479006 }, { "step": 3250, "valid accuracy": 0.56, "train loss": 0.6037812237739563, "train samples": 13000, "train time": 171.0474435731303, "eval time": 24.763687291997485, "tokens / sec": 1232.9970889616397, "mem allocated avg": 6870784204.8, "mem reserved avg": 28628398112.768, "elapsed time": 2710.9462912730232 }, { "step": 3500, "valid accuracy": 0.46, "train loss": 0.5813168592453003, "train samples": 14000, "train time": 171.50457438497688, "eval time": 22.86701555599575, "tokens / sec": 1222.9994491527293, "mem allocated avg": 6869285494.784, "mem reserved avg": 28652557303.808, "elapsed time": 2912.6192737650126 }, { "step": 3750, "valid accuracy": 0.62, "train loss": 0.5727146596908569, "train samples": 15000, "train time": 174.36638085806044, "eval time": 24.90966416199808, "tokens / sec": 1242.8026488454955, "mem allocated avg": 6880991285.248, "mem reserved avg": 29152602226.688, "elapsed time": 3119.1520819069992 }, { "step": 4000, "valid accuracy": 0.48, "train loss": 0.5771222689151764, "train samples": 16000, "train time": 166.84103391700773, "eval time": 21.578396992990747, "tokens / sec": 1224.9564462760516, "mem allocated avg": 6861483413.504, "mem reserved avg": 28693292384.256, "elapsed time": 3314.887631963007 }, { "step": 4250, "valid accuracy": 0.48, "train loss": 0.5596228052377701, "train samples": 17000, "train time": 168.76604135675007, "eval time": 26.615190682001412, "tokens / sec": 1252.5564876712988, "mem allocated avg": 6871832551.424, "mem reserved avg": 28660518092.8, "elapsed time": 3517.33625098801 }, { "step": 4500, "valid accuracy": 0.56, "train loss": 0.5638360705375671, "train samples": 18000, "train time": 170.94274596704054, "eval time": 19.347630154981744, "tokens / sec": 1215.7169865521487, "mem allocated avg": 6867000530.944, "mem reserved avg": 28579878404.096, "elapsed time": 3714.970551975013 }, { "step": 4750, "valid accuracy": 0.54, "train loss": 0.5517311846017837, "train samples": 19000, "train time": 172.1988175440929, "eval time": 17.573275297996588, "tokens / sec": 1219.1663275866772, "mem allocated avg": 6869788155.904, "mem reserved avg": 28620730925.056, "elapsed time": 3911.9516312760243 }, { "step": 5000, "valid accuracy": 0.52, "train loss": 0.5587065149545669, "train samples": 20000, "train time": 168.7623130355787, "eval time": 20.3918305770203, "tokens / sec": 1234.161799833178, "mem allocated avg": 6866212829.184, "mem reserved avg": 28180454834.176, "elapsed time": 4108.278737300017 }, { "step": 5000, "test accuracy": 0.5079605761940864, "train loss": 0.5587065149545669, "train samples": 20000, "train total tokens": 4198051, "forgetting": 0.18798315525054932 } ] }, "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" } }