PEFT-method-comparison / MetaMathQA /results /fourierft--llama-3.2-3B-default.json
github-actions[bot]
🚀 Deploy method comparison app from GH action
904a7bc
{
"run_info": {
"created_at": "2025-06-20T10:18:57+00:00",
"total_time": 2823.832106703994,
"experiment_name": "fourierft/llama-3.2-3B-default",
"peft_branch": "main",
"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,
"query_template": "Question: {query} Think step by step.\nAnswer:",
"seed": 0,
"grad_norm_clip": 1.0,
"optimizer_type": "AdamW",
"optimizer_kwargs": {
"lr": 0.0001,
"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
},
"peft_config": {
"task_type": null,
"peft_type": "FOURIERFT",
"auto_mapping": null,
"base_model_name_or_path": "meta-llama/Llama-3.2-3B",
"revision": null,
"inference_mode": false,
"n_frequency": 1000,
"scaling": 300,
"random_loc_seed": 777,
"fan_in_fan_out": false,
"target_modules": [
"q_proj",
"v_proj"
],
"exclude_modules": null,
"bias": "none",
"modules_to_save": null,
"layers_to_transform": null,
"layers_pattern": null,
"n_frequency_pattern": {},
"init_weights": false
},
"error_msg": ""
},
"train_info": {
"accelerator_memory_reserved_avg": 13104129350,
"accelerator_memory_max": 23653777408,
"accelerator_memory_reserved_99th": 19017267937,
"train_time": 2424.3862988609762,
"file_size": 231416,
"num_trainable_params": 56000,
"num_total_params": 3212805824,
"status": "success",
"metrics": [
{
"step": 250,
"valid accuracy": 0.0,
"train loss": 1.3263031902313231,
"train samples": 1000,
"train time": 53.55340486107161,
"eval time": 19.578013352002017,
"tokens / sec": 3953.4180982374883,
"mem allocated avg": 6781303625.728,
"mem reserved avg": 13152850804.736,
"elapsed time": 119.84825310099404
},
{
"step": 500,
"valid accuracy": 0.0,
"train loss": 1.3399862418174744,
"train samples": 2000,
"train time": 52.85717789203045,
"eval time": 19.544192551999004,
"tokens / sec": 3935.03793231005,
"mem allocated avg": 6774035257.344,
"mem reserved avg": 13043463356.416,
"elapsed time": 233.5829256769939
},
{
"step": 750,
"valid accuracy": 0.0,
"train loss": 1.3045952091217041,
"train samples": 3000,
"train time": 53.35706212905643,
"eval time": 19.607110917990212,
"tokens / sec": 4018.2309790861696,
"mem allocated avg": 6783920330.752,
"mem reserved avg": 13205673869.312,
"elapsed time": 348.1469791559939
},
{
"step": 1000,
"valid accuracy": 0.0,
"train loss": 1.3111453976631164,
"train samples": 4000,
"train time": 52.95546973698947,
"eval time": 19.472347582006478,
"tokens / sec": 3934.1733919976355,
"mem allocated avg": 6776025266.176,
"mem reserved avg": 13077269446.656,
"elapsed time": 461.81266678999236
},
{
"step": 1250,
"valid accuracy": 0.0,
"train loss": 1.299716483592987,
"train samples": 5000,
"train time": 52.12036712520057,
"eval time": 19.626158429004136,
"tokens / sec": 4001.0846335572023,
"mem allocated avg": 6775331573.76,
"mem reserved avg": 13063344357.376,
"elapsed time": 574.6407375999988
},
{
"step": 1500,
"valid accuracy": 0.0,
"train loss": 1.2867344057559966,
"train samples": 6000,
"train time": 52.594848359090975,
"eval time": 19.54386943600548,
"tokens / sec": 3980.0666135738998,
"mem allocated avg": 6776458844.16,
"mem reserved avg": 13093568512.0,
"elapsed time": 688.0431025519938
},
{
"step": 1750,
"valid accuracy": 0.0,
"train loss": 1.2803141210079194,
"train samples": 7000,
"train time": 52.98738884186605,
"eval time": 19.568909612993593,
"tokens / sec": 3951.0344739725274,
"mem allocated avg": 6778496358.4,
"mem reserved avg": 13108768669.696,
"elapsed time": 801.9154772249894
},
{
"step": 2000,
"valid accuracy": 0.0,
"train loss": 1.2766506419181824,
"train samples": 8000,
"train time": 52.03297274692159,
"eval time": 19.525613270001486,
"tokens / sec": 3991.62279292005,
"mem allocated avg": 6774647097.344,
"mem reserved avg": 13051189264.384,
"elapsed time": 914.5343848449993
},
{
"step": 2250,
"valid accuracy": 0.0,
"train loss": 1.2596003375053406,
"train samples": 9000,
"train time": 53.934016149127274,
"eval time": 19.535415460006334,
"tokens / sec": 3985.388356870549,
"mem allocated avg": 6785830477.824,
"mem reserved avg": 13237223424.0,
"elapsed time": 1029.9007452719961
},
{
"step": 2500,
"valid accuracy": 0.0,
"train loss": 1.2684449093341827,
"train samples": 10000,
"train time": 52.006629903029534,
"eval time": 19.470633051998448,
"tokens / sec": 3960.3989026791724,
"mem allocated avg": 6771212331.008,
"mem reserved avg": 12996118052.864,
"elapsed time": 1142.5889472209965
},
{
"step": 2750,
"valid accuracy": 0.0,
"train loss": 1.2548872971534728,
"train samples": 11000,
"train time": 53.403087337108445,
"eval time": 19.463876378998975,
"tokens / sec": 3967.579601952513,
"mem allocated avg": 6781916252.16,
"mem reserved avg": 13168084516.864,
"elapsed time": 1257.0122518049902
},
{
"step": 3000,
"valid accuracy": 0.0,
"train loss": 1.253697858095169,
"train samples": 12000,
"train time": 53.20096563108382,
"eval time": 19.472515105997445,
"tokens / sec": 3923.443823321214,
"mem allocated avg": 6777045135.36,
"mem reserved avg": 13084844359.68,
"elapsed time": 1370.94780872899
},
{
"step": 3250,
"valid accuracy": 0.0,
"train loss": 1.248513156414032,
"train samples": 13000,
"train time": 52.962746563891415,
"eval time": 19.54665829600708,
"tokens / sec": 3982.06312328573,
"mem allocated avg": 6779038627.84,
"mem reserved avg": 13110345728.0,
"elapsed time": 1484.7621198889974
},
{
"step": 3500,
"valid accuracy": 0.0,
"train loss": 1.2477959940433503,
"train samples": 14000,
"train time": 52.93443578510778,
"eval time": 19.444701158994576,
"tokens / sec": 3962.4489595298505,
"mem allocated avg": 6776803573.76,
"mem reserved avg": 13097142059.008,
"elapsed time": 1598.8772237269877
},
{
"step": 3750,
"valid accuracy": 0.0,
"train loss": 1.228544222354889,
"train samples": 15000,
"train time": 53.31031796212483,
"eval time": 19.472959079008433,
"tokens / sec": 4064.9354249577,
"mem allocated avg": 6788200585.216,
"mem reserved avg": 13268999471.104,
"elapsed time": 1713.6814467679942
},
{
"step": 4000,
"valid accuracy": 0.0,
"train loss": 1.2609001460075377,
"train samples": 16000,
"train time": 51.9827769130934,
"eval time": 19.473652824002784,
"tokens / sec": 3931.552182017475,
"mem allocated avg": 6770180233.216,
"mem reserved avg": 12983610638.336,
"elapsed time": 1826.5604049959948
},
{
"step": 4250,
"valid accuracy": 0.0,
"train loss": 1.227214762210846,
"train samples": 17000,
"train time": 53.09942602888623,
"eval time": 19.547112297004787,
"tokens / sec": 3981.0034836347163,
"mem allocated avg": 6779591426.048,
"mem reserved avg": 13132760088.576,
"elapsed time": 1940.5098487799987
},
{
"step": 4500,
"valid accuracy": 0.0,
"train loss": 1.2504195840358734,
"train samples": 18000,
"train time": 52.23909889203787,
"eval time": 19.522137050997117,
"tokens / sec": 3978.207978462565,
"mem allocated avg": 6775933241.344,
"mem reserved avg": 13056079822.848,
"elapsed time": 2053.2267840139975
},
{
"step": 4750,
"valid accuracy": 0.0,
"train loss": 1.2349513354301453,
"train samples": 19000,
"train time": 53.36620609794045,
"eval time": 19.541859832999762,
"tokens / sec": 3933.931514912433,
"mem allocated avg": 6777532579.84,
"mem reserved avg": 13101604798.464,
"elapsed time": 2167.8329333979927
},
{
"step": 5000,
"valid accuracy": 0.0,
"train loss": 1.2480293517112733,
"train samples": 20000,
"train time": 52.46977503092785,
"eval time": 19.44991449599911,
"tokens / sec": 3969.5234042309344,
"mem allocated avg": 6773533165.568,
"mem reserved avg": 13049645760.512,
"elapsed time": 2281.220151823989
},
{
"step": 5000,
"test accuracy": 0.000758150113722517,
"train loss": 1.2480293517112733,
"train samples": 20000,
"train total tokens": 4198051
}
]
},
"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": "e53f048856ff4f594e959d75785d2c2d37b678ee",
"created_at": "2022-04-12T10:22:10+00:00"
}
},
"package_info": {
"transformers-version": "4.52.4",
"transformers-commit-hash": null,
"peft-version": "0.15.2.dev0",
"peft-commit-hash": "5fe7f8f8abe914d313fc3751f2ea92de7718fbaf",
"datasets-version": "3.6.0",
"datasets-commit-hash": null,
"bitsandbytes-version": "0.46.0",
"bitsandbytes-commit-hash": null,
"torch-version": "2.7.1+cu126",
"torch-commit-hash": null
},
"system_info": {
"system": "Linux",
"release": "6.8.0-1029-aws",
"version": "#31-Ubuntu SMP Wed Apr 23 18:42:41 UTC 2025",
"machine": "x86_64",
"processor": "x86_64",
"accelerator": "NVIDIA L40S"
},
"pytorch_info": "PyTorch built with:\n - GCC 11.2\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 v3.7.1 (Git Hash 8d263e693366ef8db40acc569cc7d8edf644556d)\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 12.6\n - NVCC architecture flags: -gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-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\n - CuDNN 90.7.1 (built against CUDA 12.8)\n - Built with CuDNN 90.5.1\n - Magma 2.6.1\n - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, COMMIT_SHA=e2d141dbde55c2a4370fac5165b0561b6af4798b, CUDA_VERSION=12.6, CUDNN_VERSION=9.5.1, CXX_COMPILER=/opt/rh/gcc-toolset-11/root/usr/bin/c++, CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=1 -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DLIBKINETO_NOXPUPTI=ON -DUSE_FBGEMM -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -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 -fdiagnostics-color=always -faligned-new -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, TORCH_VERSION=2.7.1, 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, \n"
}
}