finetune-gpt2xl
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Xirider
TypeError: __init__() got an unexpected keyword argument 'no_args_is_help'
(gh_finetune-gpt2xl) r730ub20@r730ub20-M0:~/llm_dev/finetune-gpt2xl$ deepspeed --num_gpus=1 run_clm.py --deepspeed ds_config.json --model_name_or_path gpt2-xl --train_file train.csv --validation_file validation.csv --do_train --do_eval --fp16 --overwrite_cache --evaluation_strategy="steps" --output_dir finetuned --eval_steps 200 --num_train_epochs 1 --gradient_accumulation_steps 2 --per_device_train_batch_size 1 [2023-05-22 22:00:31,576] [WARNING] [runner.py:191:fetch_hostfile] Unable to find hostfile, will proceed with training with local resources only. [2023-05-22 22:00:31,600] [INFO] [runner.py:541:main] cmd = /usr/bin/python3 -u -m deepspeed.launcher.launch --world_info=eyJsb2NhbGhvc3QiOiBbMF19 --master_addr=127.0.0.1 --master_port=29500 --enable_each_rank_log=None run_clm.py --deepspeed ds_config.json --model_name_or_path gpt2-xl --train_file train.csv --validation_file validation.csv --do_train --do_eval --fp16 --overwrite_cache --evaluation_strategy=steps --output_dir finetuned --eval_steps 200 --num_train_epochs 1 --gradient_accumulation_steps 2 --per_device_train_batch_size 1 [2023-05-22 22:00:33,028] [INFO] [launch.py:229:main] WORLD INFO DICT: {'localhost': [0]} [2023-05-22 22:00:33,028] [INFO] [launch.py:235:main] nnodes=1, num_local_procs=1, node_rank=0 [2023-05-22 22:00:33,028] [INFO] [launch.py:246:main] global_rank_mapping=defaultdict(<class 'list'>, {'localhost': [0]}) [2023-05-22 22:00:33,028] [INFO] [launch.py:247:main] dist_world_size=1 [2023-05-22 22:00:33,028] [INFO] [launch.py:249:main] Setting CUDA_VISIBLE_DEVICES=0 [2023-05-22 22:00:34,832] [INFO] [comm.py:622:init_distributed] Initializing TorchBackend in DeepSpeed with backend nccl 05/22/2023 22:00:34 - WARNING - main - Process rank: 0, device: cuda:0, n_gpu: 1distributed training: True, 16-bits training: True 05/22/2023 22:00:34 - INFO - main - Training/evaluation parameters TrainingArguments( _n_gpu=1, adafactor=False, adam_beta1=0.9, adam_beta2=0.999, adam_epsilon=1e-08, dataloader_drop_last=False, dataloader_num_workers=0, dataloader_pin_memory=True, ddp_find_unused_parameters=None, debug=[], deepspeed=ds_config.json, disable_tqdm=False, do_eval=True, do_predict=False, do_train=True, eval_accumulation_steps=None, eval_steps=200, evaluation_strategy=IntervalStrategy.STEPS, fp16=True, fp16_backend=auto, fp16_full_eval=False, fp16_opt_level=O1, gradient_accumulation_steps=2, greater_is_better=None, group_by_length=False, ignore_data_skip=False, label_names=None, label_smoothing_factor=0.0, learning_rate=5e-05, length_column_name=length, load_best_model_at_end=False, local_rank=0, log_on_each_node=True, logging_dir=runs/May22_22-00-34_r730ub20-M0, logging_first_step=False, logging_steps=500, logging_strategy=IntervalStrategy.STEPS, lr_scheduler_type=SchedulerType.LINEAR, max_grad_norm=1.0, max_steps=-1, metric_for_best_model=None, mp_parameters=, no_cuda=False, num_train_epochs=1.0, output_dir=finetuned, overwrite_output_dir=False, past_index=-1, per_device_eval_batch_size=8, per_device_train_batch_size=1, prediction_loss_only=False, push_to_hub=False, remove_unused_columns=True, report_to=['wandb'], resume_from_checkpoint=None, run_name=finetuned, save_steps=500, save_strategy=IntervalStrategy.STEPS, save_total_limit=None, seed=42, sharded_ddp=[], skip_memory_metrics=True, tpu_metrics_debug=False, tpu_num_cores=None, use_legacy_prediction_loop=False, warmup_ratio=0.0, warmup_steps=0, weight_decay=0.0, ) 05/22/2023 22:00:36 - WARNING - datasets.builder - Using custom data configuration default-3bfffae691dad1b0 05/22/2023 22:00:36 - WARNING - datasets.builder - Reusing dataset csv (/home/r730ub20/.cache/huggingface/datasets/csv/default-3bfffae691dad1b0/0.0.0/2dc6629a9ff6b5697d82c25b73731dd440507a69cbce8b425db50b751e8fcfd0) [INFO|configuration_utils.py:517] 2023-05-22 22:00:36,541 >> loading configuration file https://huggingface.co/gpt2-xl/resolve/main/config.json from cache at /home/r730ub20/.cache/huggingface/transformers/d2de8fec009fa9b9196047559bcac6c1f02a9c500718b4346bc516354965b1ca.d684cb2afa3f8c44c73bd67537d9aa5ff6044658793e077d7306ef2e37dd79bd [INFO|configuration_utils.py:553] 2023-05-22 22:00:36,543 >> Model config GPT2Config { "activation_function": "gelu_new", "architectures": [ "GPT2LMHeadModel" ], "attn_pdrop": 0.1, "bos_token_id": 50256, "embd_pdrop": 0.1, "eos_token_id": 50256, "gradient_checkpointing": false, "initializer_range": 0.02, "layer_norm_epsilon": 1e-05, "model_type": "gpt2", "n_ctx": 1024, "n_embd": 1600, "n_head": 25, "n_inner": null, "n_layer": 48, "n_positions": 1024, "output_past": true, "resid_pdrop": 0.1, "scale_attn_weights": true, "summary_activation": null, "summary_first_dropout": 0.1, "summary_proj_to_labels": true, "summary_type": "cls_index", "summary_use_proj": true, "task_specific_params": { "text-generation": { "do_sample": true, "max_length": 50 } }, "transformers_version": "4.7.0", "use_cache": true, "vocab_size": 50257 }
[INFO|configuration_utils.py:517] 2023-05-22 22:00:36,953 >> loading configuration file https://huggingface.co/gpt2-xl/resolve/main/config.json from cache at /home/r730ub20/.cache/huggingface/transformers/d2de8fec009fa9b9196047559bcac6c1f02a9c500718b4346bc516354965b1ca.d684cb2afa3f8c44c73bd67537d9aa5ff6044658793e077d7306ef2e37dd79bd [INFO|configuration_utils.py:553] 2023-05-22 22:00:36,954 >> Model config GPT2Config { "activation_function": "gelu_new", "architectures": [ "GPT2LMHeadModel" ], "attn_pdrop": 0.1, "bos_token_id": 50256, "embd_pdrop": 0.1, "eos_token_id": 50256, "gradient_checkpointing": false, "initializer_range": 0.02, "layer_norm_epsilon": 1e-05, "model_type": "gpt2", "n_ctx": 1024, "n_embd": 1600, "n_head": 25, "n_inner": null, "n_layer": 48, "n_positions": 1024, "output_past": true, "resid_pdrop": 0.1, "scale_attn_weights": true, "summary_activation": null, "summary_first_dropout": 0.1, "summary_proj_to_labels": true, "summary_type": "cls_index", "summary_use_proj": true, "task_specific_params": { "text-generation": { "do_sample": true, "max_length": 50 } }, "transformers_version": "4.7.0", "use_cache": true, "vocab_size": 50257 }
[INFO|tokenization_utils_base.py:1717] 2023-05-22 22:00:39,950 >> loading file https://huggingface.co/gpt2-xl/resolve/main/vocab.json from cache at /home/r730ub20/.cache/huggingface/transformers/8560a2df03f812b276794ae6935255d0590522553a4c8103155472b07591a21b.c7ed1f96aac49e745788faa77ba0a26a392643a50bb388b9c04ff469e555241f [INFO|tokenization_utils_base.py:1717] 2023-05-22 22:00:39,950 >> loading file https://huggingface.co/gpt2-xl/resolve/main/merges.txt from cache at /home/r730ub20/.cache/huggingface/transformers/18fe27e0b70062b3e45fc4e827d5449d9fe85875937594da927e48cb657366d1.5d12962c5ee615a4c803841266e9c3be9a691a924f72d395d3a6c6c81157788b [INFO|tokenization_utils_base.py:1717] 2023-05-22 22:00:39,950 >> loading file https://huggingface.co/gpt2-xl/resolve/main/tokenizer.json from cache at /home/r730ub20/.cache/huggingface/transformers/aabb8839163cd911f810ab23f5ae8c966b9b9ea60622c429020611caa389b04b.cf2d0ecb83b6df91b3dbb53f1d1e4c311578bfd3aa0e04934215a49bf9898df0 [INFO|tokenization_utils_base.py:1717] 2023-05-22 22:00:39,950 >> loading file https://huggingface.co/gpt2-xl/resolve/main/added_tokens.json from cache at None [INFO|tokenization_utils_base.py:1717] 2023-05-22 22:00:39,950 >> loading file https://huggingface.co/gpt2-xl/resolve/main/special_tokens_map.json from cache at None [INFO|tokenization_utils_base.py:1717] 2023-05-22 22:00:39,950 >> loading file https://huggingface.co/gpt2-xl/resolve/main/tokenizer_config.json from cache at None [INFO|modeling_utils.py:1152] 2023-05-22 22:00:40,482 >> loading weights file https://huggingface.co/gpt2-xl/resolve/main/pytorch_model.bin from cache at /home/r730ub20/.cache/huggingface/transformers/96569b907e56747ce3e593c6a13d8475b8c733a64aab8af8f602b90d94c4af71.8fbbcdf404c82c5967934d411f1462fa0574d639f2aa398aa3754fced1bb26c0 [INFO|modeling_utils.py:1336] 2023-05-22 22:00:58,095 >> All model checkpoint weights were used when initializing GPT2LMHeadModel.
[INFO|modeling_utils.py:1344] 2023-05-22 22:00:58,095 >> All the weights of GPT2LMHeadModel were initialized from the model checkpoint at gpt2-xl.
If your task is similar to the task the model of the checkpoint was trained on, you can already use GPT2LMHeadModel for predictions without further training.
05/22/2023 22:00:58 - WARNING - datasets.fingerprint - Parameter 'function'=<function main.tokenizers before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using tokenizers before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using tokenizers before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
[INFO|trainer.py:414] 2023-05-22 22:01:05,456 >> Using amp fp16 backend
[2023-05-22 22:01:05,461] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed info: version=0.9.2, git-hash=unknown, git-branch=unknown
[2023-05-22 22:01:05,462] [WARNING] [config_utils.py:69:_process_deprecated_field] Config parameter cpu_offload is deprecated use offload_optimizer instead
[2023-05-22 22:01:10,928] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed Flops Profiler Enabled: False
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using tokenizers before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using tokenizers before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using tokenizers before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using tokenizers before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
Installed CUDA version 11.7 does not match the version torch was compiled with 11.3 but since the APIs are compatible, accepting this combination
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using tokenizers before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using tokenizers before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using tokenizers before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
Installed CUDA version 11.7 does not match the version torch was compiled with 11.3 but since the APIs are compatible, accepting this combination
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using tokenizers before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
Using /home/r730ub20/.cache/torch_extensions/py38_cu113 as PyTorch extensions root...
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using tokenizers before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using tokenizers before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using tokenizers before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
Detected CUDA files, patching ldflags
Emitting ninja build file /home/r730ub20/.cache/torch_extensions/py38_cu113/cpu_adam/build.ninja...
Building extension module cpu_adam...
Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using tokenizers before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
ninja: no work to do.
Loading extension module cpu_adam...
Time to load cpu_adam op: 3.7361702919006348 seconds
Adam Optimizer #0 is created with AVX2 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
[2023-05-22 22:01:17,581] [INFO] [logging.py:96:log_dist] [Rank 0] Using DeepSpeed Optimizer param name adamw as basic optimizer
[2023-05-22 22:01:17,630] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed Basic Optimizer = DeepSpeedCPUAdam
[2023-05-22 22:01:17,630] [INFO] [utils.py:54:is_zero_supported_optimizer] Checking ZeRO support for optimizer=DeepSpeedCPUAdam type=<class 'deepspeed.ops.adam.cpu_adam.DeepSpeedCPUAdam'>
[2023-05-22 22:01:17,630] [INFO] [logging.py:96:log_dist] [Rank 0] Creating torch.float16 ZeRO stage 2 optimizer
[2023-05-22 22:01:17,630] [INFO] [stage_1_and_2.py:133:init] Reduce bucket size 200000000
[2023-05-22 22:01:17,630] [INFO] [stage_1_and_2.py:134:init] Allgather bucket size 200000000
[2023-05-22 22:01:17,630] [INFO] [stage_1_and_2.py:135:init] CPU Offload: True
[2023-05-22 22:01:17,630] [INFO] [stage_1_and_2.py:136:init] Round robin gradient partitioning: False
Using /home/r730ub20/.cache/torch_extensions/py38_cu113 as PyTorch extensions root...
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using tokenizers before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using tokenizers before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using tokenizers before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
Emitting ninja build file /home/r730ub20/.cache/torch_extensions/py38_cu113/utils/build.ninja...
Building extension module utils...
Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using tokenizers before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
ninja: no work to do.
Loading extension module utils...
Time to load utils op: 0.6310455799102783 seconds
Rank: 0 partition count [1] and sizes[(1557611200, False)]
[2023-05-22 22:01:24,621] [INFO] [utils.py:785:see_memory_usage] Before initializing optimizer states
[2023-05-22 22:01:24,622] [INFO] [utils.py:786:see_memory_usage] MA 3.1 GB Max_MA 3.1 GB CA 3.1 GB Max_CA 3 GB
[2023-05-22 22:01:24,623] [INFO] [utils.py:793:see_memory_usage] CPU Virtual Memory: used = 18.32 GB, percent = 7.3%
[2023-05-22 22:01:31,310] [INFO] [utils.py:785:see_memory_usage] After initializing optimizer states
[2023-05-22 22:01:31,311] [INFO] [utils.py:786:see_memory_usage] MA 3.1 GB Max_MA 3.1 GB CA 3.1 GB Max_CA 3 GB
[2023-05-22 22:01:31,311] [INFO] [utils.py:793:see_memory_usage] CPU Virtual Memory: used = 35.84 GB, percent = 14.2%
[2023-05-22 22:01:31,311] [INFO] [stage_1_and_2.py:489:init] optimizer state initialized
[2023-05-22 22:01:31,369] [INFO] [utils.py:785:see_memory_usage] After initializing ZeRO optimizer
[2023-05-22 22:01:31,370] [INFO] [utils.py:786:see_memory_usage] MA 3.1 GB Max_MA 3.1 GB CA 3.1 GB Max_CA 3 GB
[2023-05-22 22:01:31,370] [INFO] [utils.py:793:see_memory_usage] CPU Virtual Memory: used = 35.84 GB, percent = 14.2%
[2023-05-22 22:01:31,386] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed Final Optimizer = adamw
[2023-05-22 22:01:31,386] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed using configured LR scheduler = WarmupLR
[2023-05-22 22:01:31,386] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed LR Scheduler = <deepspeed.runtime.lr_schedules.WarmupLR object at 0x7f22265c1040>
[2023-05-22 22:01:31,386] [INFO] [logging.py:96:log_dist] [Rank 0] step=0, skipped=0, lr=[5e-05], mom=[[0.9, 0.999]]
[2023-05-22 22:01:31,387] [INFO] [config.py:955:print] DeepSpeedEngine configuration:
[2023-05-22 22:01:31,387] [INFO] [config.py:959:print] activation_checkpointing_config {
"partition_activations": false,
"contiguous_memory_optimization": false,
"cpu_checkpointing": false,
"number_checkpoints": null,
"synchronize_checkpoint_boundary": false,
"profile": false
}
[2023-05-22 22:01:31,387] [INFO] [config.py:959:print] aio_config ................... {'block_size': 1048576, 'queue_depth': 8, 'thread_count': 1, 'single_submit': False, 'overlap_events': True}
[2023-05-22 22:01:31,387] [INFO] [config.py:959:print] amp_enabled .................. False
[2023-05-22 22:01:31,387] [INFO] [config.py:959:print] amp_params ................... False
[2023-05-22 22:01:31,388] [INFO] [config.py:959:print] autotuning_config ............ {
"enabled": false,
"start_step": null,
"end_step": null,
"metric_path": null,
"arg_mappings": null,
"metric": "throughput",
"model_info": null,
"results_dir": "autotuning_results",
"exps_dir": "autotuning_exps",
"overwrite": true,
"fast": true,
"start_profile_step": 3,
"end_profile_step": 5,
"tuner_type": "gridsearch",
"tuner_early_stopping": 5,
"tuner_num_trials": 50,
"model_info_path": null,
"mp_size": 1,
"max_train_batch_size": null,
"min_train_batch_size": 1,
"max_train_micro_batch_size_per_gpu": 1.024000e+03,
"min_train_micro_batch_size_per_gpu": 1,
"num_tuning_micro_batch_sizes": 3
}
[2023-05-22 22:01:31,388] [INFO] [config.py:959:print] bfloat16_enabled ............. False
[2023-05-22 22:01:31,388] [INFO] [config.py:959:print] checkpoint_parallel_write_pipeline False
[2023-05-22 22:01:31,388] [INFO] [config.py:959:print] checkpoint_tag_validation_enabled True
[2023-05-22 22:01:31,388] [INFO] [config.py:959:print] checkpoint_tag_validation_fail False
[2023-05-22 22:01:31,388] [INFO] [config.py:959:print] comms_config ................. <deepspeed.comm.config.DeepSpeedCommsConfig object at 0x7f2032c4a580>
[2023-05-22 22:01:31,388] [INFO] [config.py:959:print] communication_data_type ...... None
[2023-05-22 22:01:31,388] [INFO] [config.py:959:print] compression_config ........... {'weight_quantization': {'shared_parameters': {'enabled': False, 'quantizer_kernel': False, 'schedule_offset': 0, 'quantize_groups': 1, 'quantize_verbose': False, 'quantization_type': 'symmetric', 'quantize_weight_in_forward': False, 'rounding': 'nearest', 'fp16_mixed_quantize': False, 'quantize_change_ratio': 0.001}, 'different_groups': {}}, 'activation_quantization': {'shared_parameters': {'enabled': False, 'quantization_type': 'symmetric', 'range_calibration': 'dynamic', 'schedule_offset': 1000}, 'different_groups': {}}, 'sparse_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'row_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'head_pruning': {'shared_parameters': {'enabled': False, 'method': 'topk', 'schedule_offset': 1000}, 'different_groups': {}}, 'channel_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'layer_reduction': {'enabled': False}}
[2023-05-22 22:01:31,388] [INFO] [config.py:959:print] curriculum_enabled_legacy .... False
[2023-05-22 22:01:31,388] [INFO] [config.py:959:print] curriculum_params_legacy ..... False
[2023-05-22 22:01:31,388] [INFO] [config.py:959:print] data_efficiency_config ....... {'enabled': False, 'seed': 1234, 'data_sampling': {'enabled': False, 'num_epochs': 1000, 'num_workers': 0, 'curriculum_learning': {'enabled': False}}, 'data_routing': {'enabled': False, 'random_ltd': {'enabled': False, 'layer_token_lr_schedule': {'enabled': False}}}}
[2023-05-22 22:01:31,388] [INFO] [config.py:959:print] data_efficiency_enabled ...... False
[2023-05-22 22:01:31,388] [INFO] [config.py:959:print] dataloader_drop_last ......... False
[2023-05-22 22:01:31,388] [INFO] [config.py:959:print] disable_allgather ............ False
[2023-05-22 22:01:31,388] [INFO] [config.py:959:print] dump_state ................... False
[2023-05-22 22:01:31,388] [INFO] [config.py:959:print] dynamic_loss_scale_args ...... {'init_scale': 65536, 'scale_window': 1000, 'delayed_shift': 2, 'min_scale': 1}
[2023-05-22 22:01:31,388] [INFO] [config.py:959:print] eigenvalue_enabled ........... False
[2023-05-22 22:01:31,388] [INFO] [config.py:959:print] eigenvalue_gas_boundary_resolution 1
[2023-05-22 22:01:31,388] [INFO] [config.py:959:print] eigenvalue_layer_name ........ bert.encoder.layer
[2023-05-22 22:01:31,388] [INFO] [config.py:959:print] eigenvalue_layer_num ......... 0
[2023-05-22 22:01:31,388] [INFO] [config.py:959:print] eigenvalue_max_iter .......... 100
[2023-05-22 22:01:31,388] [INFO] [config.py:959:print] eigenvalue_stability ......... 1e-06
[2023-05-22 22:01:31,388] [INFO] [config.py:959:print] eigenvalue_tol ............... 0.01
[2023-05-22 22:01:31,388] [INFO] [config.py:959:print] eigenvalue_verbose ........... False
[2023-05-22 22:01:31,388] [INFO] [config.py:959:print] elasticity_enabled ........... False
[2023-05-22 22:01:31,389] [INFO] [config.py:959:print] flops_profiler_config ........ {
"enabled": false,
"profile_step": 1,
"module_depth": -1,
"top_modules": 1,
"detailed": true,
"output_file": null
}
[2023-05-22 22:01:31,389] [INFO] [config.py:959:print] fp16_auto_cast ............... False
[2023-05-22 22:01:31,389] [INFO] [config.py:959:print] fp16_enabled ................. True
[2023-05-22 22:01:31,389] [INFO] [config.py:959:print] fp16_master_weights_and_gradients False
[2023-05-22 22:01:31,389] [INFO] [config.py:959:print] global_rank .................. 0
[2023-05-22 22:01:31,389] [INFO] [config.py:959:print] grad_accum_dtype ............. None
[2023-05-22 22:01:31,389] [INFO] [config.py:959:print] gradient_accumulation_steps .. 2
[2023-05-22 22:01:31,389] [INFO] [config.py:959:print] gradient_clipping ............ 1.0
[2023-05-22 22:01:31,389] [INFO] [config.py:959:print] gradient_predivide_factor .... 1.0
[2023-05-22 22:01:31,389] [INFO] [config.py:959:print] hybrid_engine ................ enabled=False max_out_tokens=512 inference_tp_size=1 release_inference_cache=False pin_parameters=True tp_gather_partition_size=8
[2023-05-22 22:01:31,389] [INFO] [config.py:959:print] initial_dynamic_scale ........ 65536
[2023-05-22 22:01:31,389] [INFO] [config.py:959:print] load_universal_checkpoint .... False
[2023-05-22 22:01:31,389] [INFO] [config.py:959:print] loss_scale ................... 0
[2023-05-22 22:01:31,389] [INFO] [config.py:959:print] memory_breakdown ............. False
[2023-05-22 22:01:31,389] [INFO] [config.py:959:print] mics_hierarchial_params_gather False
[2023-05-22 22:01:31,389] [INFO] [config.py:959:print] mics_shard_size .............. -1
[2023-05-22 22:01:31,389] [INFO] [config.py:959:print] monitor_config ............... tensorboard=TensorBoardConfig(enabled=False, output_path='', job_name='DeepSpeedJobName') wandb=WandbConfig(enabled=False, group=None, team=None, project='deepspeed') csv_monitor=CSVConfig(enabled=False, output_path='', job_name='DeepSpeedJobName') enabled=False
[2023-05-22 22:01:31,389] [INFO] [config.py:959:print] nebula_config ................ {
"enabled": false,
"persistent_storage_path": null,
"persistent_time_interval": 100,
"num_of_version_in_retention": 2,
"enable_nebula_load": true,
"load_path": null
}
[2023-05-22 22:01:31,389] [INFO] [config.py:959:print] optimizer_legacy_fusion ...... False
[2023-05-22 22:01:31,389] [INFO] [config.py:959:print] optimizer_name ............... adamw
[2023-05-22 22:01:31,389] [INFO] [config.py:959:print] optimizer_params ............. {'lr': 5e-05, 'betas': [0.9, 0.999], 'eps': 1e-08, 'weight_decay': 0.0}
[2023-05-22 22:01:31,389] [INFO] [config.py:959:print] pipeline ..................... {'stages': 'auto', 'partition': 'best', 'seed_layers': False, 'activation_checkpoint_interval': 0}
[2023-05-22 22:01:31,389] [INFO] [config.py:959:print] pld_enabled .................. False
[2023-05-22 22:01:31,390] [INFO] [config.py:959:print] pld_params ................... False
[2023-05-22 22:01:31,390] [INFO] [config.py:959:print] prescale_gradients ........... False
[2023-05-22 22:01:31,390] [INFO] [config.py:959:print] scheduler_name ............... WarmupLR
[2023-05-22 22:01:31,390] [INFO] [config.py:959:print] scheduler_params ............. {'warmup_min_lr': 0, 'warmup_max_lr': 5e-05, 'warmup_num_steps': 0}
[2023-05-22 22:01:31,390] [INFO] [config.py:959:print] sparse_attention ............. None
[2023-05-22 22:01:31,390] [INFO] [config.py:959:print] sparse_gradients_enabled ..... False
[2023-05-22 22:01:31,390] [INFO] [config.py:959:print] steps_per_print .............. 2000
[2023-05-22 22:01:31,390] [INFO] [config.py:959:print] train_batch_size ............. 2
[2023-05-22 22:01:31,390] [INFO] [config.py:959:print] train_micro_batch_size_per_gpu 1
[2023-05-22 22:01:31,390] [INFO] [config.py:959:print] use_node_local_storage ....... False
[2023-05-22 22:01:31,390] [INFO] [config.py:959:print] wall_clock_breakdown ......... False
[2023-05-22 22:01:31,390] [INFO] [config.py:959:print] world_size ................... 1
[2023-05-22 22:01:31,390] [INFO] [config.py:959:print] zero_allow_untested_optimizer False
[2023-05-22 22:01:31,390] [INFO] [config.py:959:print] zero_config .................. stage=2 contiguous_gradients=True reduce_scatter=True reduce_bucket_size=200000000 allgather_partitions=True allgather_bucket_size=200000000 overlap_comm=True load_from_fp32_weights=True elastic_checkpoint=False offload_param=None offload_optimizer=DeepSpeedZeroOffloadOptimizerConfig(device='cpu', nvme_path=None, buffer_count=4, pin_memory=False, pipeline=False, pipeline_read=False, pipeline_write=False, fast_init=False) sub_group_size=1,000,000,000 cpu_offload_param=None cpu_offload_use_pin_memory=None prefetch_bucket_size=50,000,000 param_persistence_threshold=100,000 model_persistence_threshold=sys.maxsize max_live_parameters=1,000,000,000 max_reuse_distance=1,000,000,000 gather_16bit_weights_on_model_save=False stage3_gather_fp16_weights_on_model_save=False ignore_unused_parameters=True legacy_stage1=False round_robin_gradients=False mics_shard_size=-1 mics_hierarchical_params_gather=False memory_efficient_linear=True
[2023-05-22 22:01:31,390] [INFO] [config.py:959:print] zero_enabled ................. True
[2023-05-22 22:01:31,390] [INFO] [config.py:959:print] zero_force_ds_cpu_optimizer .. True
[2023-05-22 22:01:31,390] [INFO] [config.py:959:print] zero_optimization_stage ...... 2
[2023-05-22 22:01:31,390] [INFO] [config.py:945:print_user_config] json = {
"fp16": {
"enabled": true,
"loss_scale": 0,
"loss_scale_window": 1000,
"initial_scale_power": 16,
"hysteresis": 2,
"min_loss_scale": 1
},
"optimizer": {
"type": "AdamW",
"params": {
"lr": 5e-05,
"betas": [0.9, 0.999],
"eps": 1e-08,
"weight_decay": 0.0
}
},
"scheduler": {
"type": "WarmupLR",
"params": {
"warmup_min_lr": 0,
"warmup_max_lr": 5e-05,
"warmup_num_steps": 0
}
},
"zero_optimization": {
"stage": 2,
"allgather_partitions": true,
"allgather_bucket_size": 2.000000e+08,
"overlap_comm": true,
"reduce_scatter": true,
"reduce_bucket_size": 2.000000e+08,
"contiguous_gradients": true,
"cpu_offload": true
},
"gradient_accumulation_steps": 2,
"gradient_clipping": 1.0,
"steps_per_print": 2.000000e+03,
"train_batch_size": 2,
"train_micro_batch_size_per_gpu": 1,
"wall_clock_breakdown": false
}
Using /home/r730ub20/.cache/torch_extensions/py38_cu113 as PyTorch extensions root...
No modifications detected for re-loaded extension module utils, skipping build step...
Loading extension module utils...
Time to load utils op: 0.0004444122314453125 seconds
[INFO|trainer.py:1147] 2023-05-22 22:01:31,391 >> ***** Running training *****
[INFO|trainer.py:1148] 2023-05-22 22:01:31,391 >> Num examples = 11428
[INFO|trainer.py:1149] 2023-05-22 22:01:31,391 >> Num Epochs = 1
[INFO|trainer.py:1150] 2023-05-22 22:01:31,391 >> Instantaneous batch size per device = 1
[INFO|trainer.py:1151] 2023-05-22 22:01:31,391 >> Total train batch size (w. parallel, distributed & accumulation) = 2
[INFO|trainer.py:1152] 2023-05-22 22:01:31,391 >> Gradient Accumulation steps = 2
[INFO|trainer.py:1153] 2023-05-22 22:01:31,391 >> Total optimization steps = 5714
[INFO|integrations.py:402] 2023-05-22 22:01:31,393 >> Automatic Weights & Biases logging enabled, to disable set os.environ["WANDB_DISABLED"] = "true"
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using tokenizers before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using tokenizers before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using tokenizers before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
Traceback (most recent call last):
File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/usr/lib/python3.8/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/home/r730ub20/.local/lib/python3.8/site-packages/wandb/main.py", line 1, in sys.executable is a valid python interpreter. You can override it with the _executable setting or with the WANDB__EXECUTABLE environment variable.
[2023-05-22 22:01:38,113] [INFO] [launch.py:428:sigkill_handler] Killing subprocess 10431
[2023-05-22 22:01:38,114] [ERROR] [launch.py:434:sigkill_handler] ['/usr/bin/python3', '-u', 'run_clm.py', '--local_rank=0', '--deepspeed', 'ds_config.json', '--model_name_or_path', 'gpt2-xl', '--train_file', 'train.csv', '--validation_file', 'validation.csv', '--do_train', '--do_eval', '--fp16', '--overwrite_cache', '--evaluation_strategy=steps', '--output_dir', 'finetuned', '--eval_steps', '200', '--num_train_epochs', '1', '--gradient_accumulation_steps', '2', '--per_device_train_batch_size', '1'] exits with return code = 1
(gh_finetune-gpt2xl) r730ub20@r730ub20-M0:~/llm_dev/finetune-gpt2xl$
