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========================
START TIME: Wed Jul  3 22:55:47 UTC 2024
python3 version = Python 3.10.14
========================
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Already on 'bench_cluster'
M	examples/config_tiny_llama.py
M	examples/config_tiny_llama.yaml
M	examples/train_tiny_llama.sh
M	src/nanotron/models/llama.py
M	src/nanotron/trainer.py
Your branch is up to date with 'origin/bench_cluster'.
Job status: RUNNING
W0703 22:55:55.861000 140035408860992 torch/distributed/run.py:757] 
W0703 22:55:55.861000 140035408860992 torch/distributed/run.py:757] *****************************************
W0703 22:55:55.861000 140035408860992 torch/distributed/run.py:757] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0703 22:55:55.861000 140035408860992 torch/distributed/run.py:757] *****************************************
[default0]:07/03/2024 22:56:17 [WARNING|DP=0|PP=0|TP=0|ip-26-0-171-88]: [Vocab Size Padding] Padded vocab (size: 50257) with 7 dummy tokens (new size: 50264)
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: Config:
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: Config(general=GeneralArgs(project='bench_cluster',
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                            run='%date_%jobid',
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                            seed=42,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                            step=None,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                            consumed_train_samples=None,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                            benchmark_csv_path=None,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                            ignore_sanity_checks=True),
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:        parallelism=ParallelismArgs(dp=1,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                    pp=1,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                    tp=8,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                    pp_engine=<nanotron.parallel.pipeline_parallel.engine.OneForwardOneBackwardPipelineEngine object at 0x7fd61b0c4730>,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                    tp_mode=<TensorParallelLinearMode.REDUCE_SCATTER: 2>,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                    tp_linear_async_communication=False,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                    expert_parallel_size=1),
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:        model=ModelArgs(model_config=LlamaConfig(bos_token_id=1,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                 eos_token_id=2,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                 hidden_act='silu',
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                 hidden_size=2048,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                 initializer_range=0.02,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                 intermediate_size=4096,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                 is_llama_config=True,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                 max_position_embeddings=4096,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                 num_attention_heads=32,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                 num_hidden_layers=24,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                 num_key_value_heads=32,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                 pad_token_id=None,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                 pretraining_tp=1,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                 rms_norm_eps=1e-05,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                 rope_scaling=None,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                 rope_theta=10000.0,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                 tie_word_embeddings=True,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                 use_cache=True,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                 vocab_size=50264),
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                        init_method=RandomInit(std=0.025),
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                        dtype=torch.bfloat16,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                        make_vocab_size_divisible_by=1,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                        ddp_bucket_cap_mb=25),
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:        tokenizer=TokenizerArgs(tokenizer_name_or_path='openai-community/gpt2',
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                tokenizer_revision=None,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                tokenizer_max_length=None),
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:        checkpoints=CheckpointsArgs(checkpoints_path=Path('/dev/null'),
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                    checkpoint_interval=100000,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                    save_initial_state=False,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                    resume_checkpoint_path=None,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                    checkpoints_path_is_shared_file_system=False),
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:        logging=LoggingArgs(log_level='info',
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                            log_level_replica='info',
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                            iteration_step_info_interval=1),
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:        tokens=TokensArgs(sequence_length=4096,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                          train_steps=20,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                          micro_batch_size=32,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                          batch_accumulation_per_replica=32,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                          val_check_interval=-1,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                          limit_val_batches=0,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                          limit_test_batches=0),
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:        optimizer=OptimizerArgs(optimizer_factory=AdamWOptimizerArgs(adam_eps=1e-08,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                                     adam_beta1=0.9,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                                     adam_beta2=0.95,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                                     torch_adam_is_fused=True,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                                     name='adamW'),
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                zero_stage=1,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                weight_decay=0.01,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                clip_grad=1.0,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                accumulate_grad_in_fp32=True,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                learning_rate_scheduler=LRSchedulerArgs(learning_rate=0.0001,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                                        lr_warmup_steps=1,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                                        lr_warmup_style='linear',
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                                        lr_decay_style='linear',
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                                        lr_decay_steps=19,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                                        lr_decay_starting_step=None,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                                        min_decay_lr=1e-05)),
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:        data_stages=[DatasetStageArgs(name='Training Stage',
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                      start_training_step=1,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                      data=DataArgs(dataset=PretrainDatasetsArgs(hf_dataset_or_datasets='roneneldan/TinyStories',
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                                                 hf_dataset_splits='train',
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                                                 hf_dataset_config_name=None,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                                                 dataset_processing_num_proc_per_process=64,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                                                 dataset_overwrite_cache=False,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                                                 text_column_name='text'),
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                    seed=42,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:                                                    num_loading_workers=0))],
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:        profiler=ProfilerArgs(profiler_export_path=Path('/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-32')),
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:        lighteval=None)
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: Model Config:
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: LlamaConfig(bos_token_id=1,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:             eos_token_id=2,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:             hidden_act='silu',
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:             hidden_size=2048,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:             initializer_range=0.02,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:             intermediate_size=4096,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:             is_llama_config=True,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:             max_position_embeddings=4096,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:             num_attention_heads=32,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:             num_hidden_layers=24,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:             num_key_value_heads=32,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:             pad_token_id=None,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:             pretraining_tp=1,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:             rms_norm_eps=1e-05,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:             rope_scaling=None,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:             rope_theta=10000.0,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:             tie_word_embeddings=True,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:             use_cache=True,
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:             vocab_size=50264)
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: Building model..
[default0]:07/03/2024 22:56:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: Setting PP block ranks...
[default7]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=7|ip-26-0-171-88]: Local number of parameters: 139M (264.73MiB)
[default7]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=7|ip-26-0-171-88]: [After model building] Memory usage: 290.76MiB. Peak allocated: 317.33MiB Peak reserved: 324.00MiB
[default7]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=7|ip-26-0-171-88]: No checkpoint path provided.
[default4]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=4|ip-26-0-171-88]: Local number of parameters: 139M (264.73MiB)
[default4]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=4|ip-26-0-171-88]: [After model building] Memory usage: 290.76MiB. Peak allocated: 317.33MiB Peak reserved: 324.00MiB
[default4]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=4|ip-26-0-171-88]: No checkpoint path provided.
[default1]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=1|ip-26-0-171-88]: Local number of parameters: 139M (264.73MiB)
[default1]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=1|ip-26-0-171-88]: [After model building] Memory usage: 290.76MiB. Peak allocated: 317.33MiB Peak reserved: 324.00MiB
[default1]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=1|ip-26-0-171-88]: No checkpoint path provided.
[default6]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=6|ip-26-0-171-88]: Local number of parameters: 139M (264.73MiB)
[default6]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=6|ip-26-0-171-88]: [After model building] Memory usage: 290.76MiB. Peak allocated: 317.33MiB Peak reserved: 324.00MiB
[default2]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=2|ip-26-0-171-88]: Local number of parameters: 139M (264.73MiB)
[default2]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=2|ip-26-0-171-88]: [After model building] Memory usage: 290.76MiB. Peak allocated: 317.33MiB Peak reserved: 324.00MiB
[default6]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=6|ip-26-0-171-88]: No checkpoint path provided.
[default5]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=5|ip-26-0-171-88]: Local number of parameters: 139M (264.73MiB)
[default2]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=2|ip-26-0-171-88]: No checkpoint path provided.
[default5]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=5|ip-26-0-171-88]: [After model building] Memory usage: 290.76MiB. Peak allocated: 317.33MiB Peak reserved: 324.00MiB
[default5]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=5|ip-26-0-171-88]: No checkpoint path provided.
[default3]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=3|ip-26-0-171-88]: Local number of parameters: 139M (264.73MiB)
[default3]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=3|ip-26-0-171-88]: [After model building] Memory usage: 290.76MiB. Peak allocated: 317.33MiB Peak reserved: 324.00MiB
[default3]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=3|ip-26-0-171-88]: No checkpoint path provided.
[default0]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: Total number of parameters: 1.11G (2117.88MiB)
[default0]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: Local number of parameters: 139M (264.73MiB)
[default0]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: [After model building] Memory usage: 290.76MiB. Peak allocated: 317.33MiB Peak reserved: 324.00MiB
[default0]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: No checkpoint path provided.
[default0]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: Parametrizing model parameters using StandardParametrizator
[default0]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: [Optimizer Building] Using LearningRateForSP as learning rate
[default0]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: [ZeRO sharding] Size of optimizer params per rank:
[default0]:07/03/2024 22:56:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: [ZeRO sharding] DP Rank 0 has 139M out of 139M (100.00%) params' optimizer states
[default0]:07/03/2024 22:56:35 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: [Training Plan] Stage Training Stage has 19 remaining training steps and has consumed 0 samples
[default0]:07/03/2024 22:56:35 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: Using `datasets` library
[default0]:07/03/2024 22:56:35 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: Loading tokenizer from openai-community/gpt2 and transformers/hf_hub versions ('4.41.2', '0.23.4')
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/03/2024 22:56:35 [WARNING|DP=0|PP=0|TP=0|ip-26-0-171-88]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/03/2024 22:56:37 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: [Training Plan] There are 1 training stages 
[default0]:07/03/2024 22:56:37 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: [Stage Training Stage] start from step 1 
[default0]:07/03/2024 22:56:37 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: 
[default0]:07/03/2024 22:56:37 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: [Start training] datetime: 2024-07-03 22:56:37.645485 | mbs: 32 | grad_accum: 32 | global_batch_size: 1024 | sequence_length: 4096 | train_steps: 20 | start_iteration_step: 0 | consumed_train_samples: 0
[default0]:07/03/2024 22:56:37 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: Resuming training from stage Training Stage, it has trained for 0 samples and has 19 remaining train steps
[default0]:07/03/2024 22:56:37 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:  Memory usage: 1350.75MiB. Peak allocated 1350.76MiB. Peak reserved: 1384.00MiB
[default7]:07/03/2024 22:56:37 [WARNING|DP=0|PP=0|TP=7|ip-26-0-171-88]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/03/2024 22:56:37 [WARNING|DP=0|PP=0|TP=1|ip-26-0-171-88]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/03/2024 22:56:37 [WARNING|DP=0|PP=0|TP=2|ip-26-0-171-88]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/03/2024 22:56:37 [WARNING|DP=0|PP=0|TP=5|ip-26-0-171-88]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/03/2024 22:56:37 [WARNING|DP=0|PP=0|TP=6|ip-26-0-171-88]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/03/2024 22:56:37 [WARNING|DP=0|PP=0|TP=3|ip-26-0-171-88]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/03/2024 22:56:38 [WARNING|DP=0|PP=0|TP=4|ip-26-0-171-88]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default7]:  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
[default0]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default0]:  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
[default4]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default4]:  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
[default1]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default1]:  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
[default5]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default5]:  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
[default2]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default2]:  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
[default6]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default6]:  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
[default3]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default3]:  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
[default3]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
[default3]:  warnings.warn(
[default6]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
[default6]:  warnings.warn(
[default0]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
[default0]:  warnings.warn(
[default4]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
[default4]:  warnings.warn(
[default7]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
[default7]:  warnings.warn(
[default0]:07/03/2024 22:58:18 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:  Memory usage: 1429.02MiB. Peak allocated 59034.87MiB. Peak reserved: 60780.00MiB
[default2]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
[default2]:  warnings.warn(
[default1]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
[default1]:  warnings.warn(
[default5]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
[default5]:  warnings.warn(
[default0]:07/03/2024 22:58:20 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: iteration: 1 / 20 | consumed_tokens: 4.19M | elapsed_time_per_iteration_ms: 103K | tokens_per_sec: 40.9K | tokens_per_sec_per_gpu: 5.11K | global_batch_size: 1.02K | lm_loss: 11.5 | lr: 0.0001 | model_tflops_per_gpu: 46.4 | hardware_tflops_per_gpu: 46.4 | grad_norm: 15.7 | cuda_memory_allocated: 2.61G | cuda_max_memory_reserved: 63.7G | hd_total_memory_tb: 312G | hd_used_memory_tb: 67.8G | hd_free_memory_tb: 244G
[default0]:07/03/2024 22:58:20 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:  Memory usage: 2489.86MiB. Peak allocated 2489.86MiB. Peak reserved: 60780.00MiB
[default0]:07/03/2024 22:59:51 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:  Memory usage: 2489.87MiB. Peak allocated 60095.72MiB. Peak reserved: 60780.00MiB
[default0]:07/03/2024 22:59:52 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: iteration: 2 / 20 | consumed_tokens: 8.39M | elapsed_time_per_iteration_ms: 92.3K | tokens_per_sec: 45.5K | tokens_per_sec_per_gpu: 5.68K | global_batch_size: 1.02K | lm_loss: 11.5 | lr: 9.53e-05 | model_tflops_per_gpu: 51.6 | hardware_tflops_per_gpu: 51.6 | grad_norm: 16 | cuda_memory_allocated: 2.61G | cuda_max_memory_reserved: 63.7G | hd_total_memory_tb: 312G | hd_used_memory_tb: 67.8G | hd_free_memory_tb: 244G
[default0]:07/03/2024 22:59:52 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:  Memory usage: 2489.86MiB. Peak allocated 2489.95MiB. Peak reserved: 60780.00MiB
[default0]:07/03/2024 23:01:23 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:  Memory usage: 2489.87MiB. Peak allocated 60095.72MiB. Peak reserved: 60780.00MiB
[default0]:STAGE:2024-07-03 23:01:24 1097996:1097996 ActivityProfilerController.cpp:314] Completed Stage: Warm Up
[default0]:07/03/2024 23:01:24 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: iteration: 3 / 20 | consumed_tokens: 12.6M | elapsed_time_per_iteration_ms: 92.1K | tokens_per_sec: 45.6K | tokens_per_sec_per_gpu: 5.69K | global_batch_size: 1.02K | lm_loss: 12.8 | lr: 9.05e-05 | model_tflops_per_gpu: 51.7 | hardware_tflops_per_gpu: 51.7 | grad_norm: 137 | cuda_memory_allocated: 2.61G | cuda_max_memory_reserved: 63.7G | hd_total_memory_tb: 312G | hd_used_memory_tb: 67.8G | hd_free_memory_tb: 244G
[default0]:07/03/2024 23:01:24 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:  Memory usage: 2489.86MiB. Peak allocated 2489.95MiB. Peak reserved: 60780.00MiB
[default0]:07/03/2024 23:02:55 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:  Memory usage: 2489.87MiB. Peak allocated 60095.72MiB. Peak reserved: 60780.00MiB
[default0]:07/03/2024 23:02:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: iteration: 4 / 20 | consumed_tokens: 16.8M | elapsed_time_per_iteration_ms: 92.1K | tokens_per_sec: 45.5K | tokens_per_sec_per_gpu: 5.69K | global_batch_size: 1.02K | lm_loss: 12.2 | lr: 8.58e-05 | model_tflops_per_gpu: 51.6 | hardware_tflops_per_gpu: 51.6 | grad_norm: 22.4 | cuda_memory_allocated: 2.61G | cuda_max_memory_reserved: 63.7G | hd_total_memory_tb: 312G | hd_used_memory_tb: 67.8G | hd_free_memory_tb: 244G
[default0]:07/03/2024 23:02:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:  Memory usage: 2489.86MiB. Peak allocated 2489.95MiB. Peak reserved: 60780.00MiB
[default0]:07/03/2024 23:04:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: iteration: 5 / 20 | consumed_tokens: 21M | elapsed_time_per_iteration_ms: 92.3K | tokens_per_sec: 45.4K | tokens_per_sec_per_gpu: 5.68K | global_batch_size: 1.02K | lm_loss: 12.4 | lr: 8.11e-05 | model_tflops_per_gpu: 51.5 | hardware_tflops_per_gpu: 51.5 | grad_norm: 42.8
[default0]:07/03/2024 23:04:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:  Memory usage: 2489.86MiB. Peak allocated 60095.72MiB. Peak reserved: 60780.00MiB
[default0]:07/03/2024 23:06:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: iteration: 6 / 20 | consumed_tokens: 25.2M | elapsed_time_per_iteration_ms: 92.3K | tokens_per_sec: 45.5K | tokens_per_sec_per_gpu: 5.68K | global_batch_size: 1.02K | lm_loss: 11.1 | lr: 7.63e-05 | model_tflops_per_gpu: 51.6 | hardware_tflops_per_gpu: 51.6 | grad_norm: 24.8
[default0]:STAGE:2024-07-03 23:06:19 1097996:1097996 ActivityProfilerController.cpp:320] Completed Stage: Collection
[default0]:STAGE:2024-07-03 23:06:21 1097996:1097996 ActivityProfilerController.cpp:324] Completed Stage: Post Processing
[default0]:07/03/2024 23:08:43 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:  Memory usage: 2489.86MiB. Peak allocated 60095.72MiB. Peak reserved: 60780.00MiB
[default0]:07/03/2024 23:10:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: iteration: 7 / 20 | consumed_tokens: 29.4M | elapsed_time_per_iteration_ms: 92.2K | tokens_per_sec: 45.5K | tokens_per_sec_per_gpu: 5.69K | global_batch_size: 1.02K | lm_loss: 10.2 | lr: 7.16e-05 | model_tflops_per_gpu: 51.6 | hardware_tflops_per_gpu: 51.6 | grad_norm: 12.1
[default0]:07/03/2024 23:10:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:  Memory usage: 2489.86MiB. Peak allocated 60095.72MiB. Peak reserved: 60780.00MiB
[default0]:07/03/2024 23:11:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: iteration: 8 / 20 | consumed_tokens: 33.6M | elapsed_time_per_iteration_ms: 92.2K | tokens_per_sec: 45.5K | tokens_per_sec_per_gpu: 5.69K | global_batch_size: 1.02K | lm_loss: 9.8 | lr: 6.68e-05 | model_tflops_per_gpu: 51.6 | hardware_tflops_per_gpu: 51.6 | grad_norm: 7.31
[default0]:07/03/2024 23:11:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:  Memory usage: 2489.86MiB. Peak allocated 60095.72MiB. Peak reserved: 60780.00MiB
[default0]:07/03/2024 23:13:19 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: iteration: 9 / 20 | consumed_tokens: 37.7M | elapsed_time_per_iteration_ms: 92.3K | tokens_per_sec: 45.4K | tokens_per_sec_per_gpu: 5.68K | global_batch_size: 1.02K | lm_loss: 9.32 | lr: 6.21e-05 | model_tflops_per_gpu: 51.5 | hardware_tflops_per_gpu: 51.5 | grad_norm: 6.66
[default0]:07/03/2024 23:13:19 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:  Memory usage: 2489.86MiB. Peak allocated 60095.72MiB. Peak reserved: 60780.00MiB
[default0]:07/03/2024 23:14:51 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: iteration: 10 / 20 | consumed_tokens: 41.9M | elapsed_time_per_iteration_ms: 92.1K | tokens_per_sec: 45.5K | tokens_per_sec_per_gpu: 5.69K | global_batch_size: 1.02K | lm_loss: 9.22 | lr: 5.74e-05 | model_tflops_per_gpu: 51.6 | hardware_tflops_per_gpu: 51.6 | grad_norm: 16.3
[default0]:07/03/2024 23:14:51 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:  Memory usage: 2489.86MiB. Peak allocated 60095.72MiB. Peak reserved: 60780.00MiB
[default0]:07/03/2024 23:16:23 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: iteration: 11 / 20 | consumed_tokens: 46.1M | elapsed_time_per_iteration_ms: 92K | tokens_per_sec: 45.6K | tokens_per_sec_per_gpu: 5.7K | global_batch_size: 1.02K | lm_loss: 8.63 | lr: 5.26e-05 | model_tflops_per_gpu: 51.7 | hardware_tflops_per_gpu: 51.7 | grad_norm: 7.95
[default0]:07/03/2024 23:16:23 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:  Memory usage: 2489.86MiB. Peak allocated 60095.72MiB. Peak reserved: 60780.00MiB
[default0]:07/03/2024 23:17:55 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: iteration: 12 / 20 | consumed_tokens: 50.3M | elapsed_time_per_iteration_ms: 92K | tokens_per_sec: 45.6K | tokens_per_sec_per_gpu: 5.7K | global_batch_size: 1.02K | lm_loss: 8.27 | lr: 4.79e-05 | model_tflops_per_gpu: 51.7 | hardware_tflops_per_gpu: 51.7 | grad_norm: 5.43
[default0]:07/03/2024 23:17:55 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:  Memory usage: 2489.86MiB. Peak allocated 60095.72MiB. Peak reserved: 60780.00MiB
[default0]:07/03/2024 23:19:28 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: iteration: 13 / 20 | consumed_tokens: 54.5M | elapsed_time_per_iteration_ms: 92.3K | tokens_per_sec: 45.5K | tokens_per_sec_per_gpu: 5.68K | global_batch_size: 1.02K | lm_loss: 8.1 | lr: 4.32e-05 | model_tflops_per_gpu: 51.6 | hardware_tflops_per_gpu: 51.6 | grad_norm: 5.53
[default0]:07/03/2024 23:19:28 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:  Memory usage: 2489.86MiB. Peak allocated 60095.72MiB. Peak reserved: 60780.00MiB
[default0]:07/03/2024 23:21:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: iteration: 14 / 20 | consumed_tokens: 58.7M | elapsed_time_per_iteration_ms: 92.1K | tokens_per_sec: 45.6K | tokens_per_sec_per_gpu: 5.69K | global_batch_size: 1.02K | lm_loss: 7.93 | lr: 3.84e-05 | model_tflops_per_gpu: 51.7 | hardware_tflops_per_gpu: 51.7 | grad_norm: 5.77
[default0]:07/03/2024 23:21:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:  Memory usage: 2489.86MiB. Peak allocated 60095.72MiB. Peak reserved: 60780.00MiB
[default0]:07/03/2024 23:22:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: iteration: 15 / 20 | consumed_tokens: 62.9M | elapsed_time_per_iteration_ms: 92.1K | tokens_per_sec: 45.5K | tokens_per_sec_per_gpu: 5.69K | global_batch_size: 1.02K | lm_loss: 7.72 | lr: 3.37e-05 | model_tflops_per_gpu: 51.6 | hardware_tflops_per_gpu: 51.6 | grad_norm: 5.17
[default0]:07/03/2024 23:22:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:  Memory usage: 2489.86MiB. Peak allocated 60095.72MiB. Peak reserved: 60780.00MiB
[default0]:07/03/2024 23:24:04 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: iteration: 16 / 20 | consumed_tokens: 67.1M | elapsed_time_per_iteration_ms: 92.2K | tokens_per_sec: 45.5K | tokens_per_sec_per_gpu: 5.69K | global_batch_size: 1.02K | lm_loss: 7.56 | lr: 2.89e-05 | model_tflops_per_gpu: 51.6 | hardware_tflops_per_gpu: 51.6 | grad_norm: 4.93
[default0]:07/03/2024 23:24:04 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:  Memory usage: 2489.86MiB. Peak allocated 60095.72MiB. Peak reserved: 60780.00MiB
[default0]:07/03/2024 23:25:36 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: iteration: 17 / 20 | consumed_tokens: 71.3M | elapsed_time_per_iteration_ms: 92K | tokens_per_sec: 45.6K | tokens_per_sec_per_gpu: 5.7K | global_batch_size: 1.02K | lm_loss: 7.45 | lr: 2.42e-05 | model_tflops_per_gpu: 51.7 | hardware_tflops_per_gpu: 51.7 | grad_norm: 4.93
[default0]:07/03/2024 23:25:36 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:  Memory usage: 2489.86MiB. Peak allocated 60095.72MiB. Peak reserved: 60780.00MiB
[default0]:07/03/2024 23:27:08 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: iteration: 18 / 20 | consumed_tokens: 75.5M | elapsed_time_per_iteration_ms: 92K | tokens_per_sec: 45.6K | tokens_per_sec_per_gpu: 5.7K | global_batch_size: 1.02K | lm_loss: 7.35 | lr: 1.95e-05 | model_tflops_per_gpu: 51.7 | hardware_tflops_per_gpu: 51.7 | grad_norm: 4.03
[default0]:07/03/2024 23:27:08 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:  Memory usage: 2489.86MiB. Peak allocated 60095.72MiB. Peak reserved: 60780.00MiB
[default0]:07/03/2024 23:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: iteration: 19 / 20 | consumed_tokens: 79.7M | elapsed_time_per_iteration_ms: 92.3K | tokens_per_sec: 45.5K | tokens_per_sec_per_gpu: 5.68K | global_batch_size: 1.02K | lm_loss: 7.29 | lr: 1.47e-05 | model_tflops_per_gpu: 51.6 | hardware_tflops_per_gpu: 51.6 | grad_norm: 4.11
[default0]:07/03/2024 23:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]:  Memory usage: 2489.86MiB. Peak allocated 60095.72MiB. Peak reserved: 60780.00MiB
[default0]:07/03/2024 23:30:13 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-88]: iteration: 20 / 20 | consumed_tokens: 83.9M | elapsed_time_per_iteration_ms: 92.2K | tokens_per_sec: 45.5K | tokens_per_sec_per_gpu: 5.69K | global_batch_size: 1.02K | lm_loss: 7.23 | lr: 1e-05 | model_tflops_per_gpu: 51.6 | hardware_tflops_per_gpu: 51.6 | grad_norm: 3.96
Saved 1 csv files over 1 completed logs
Processing file: /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-32/profiler/ip-26-0-171-88_1097996.1720048094691939359.pt.trace.json
Results written to /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-32/profiler.csv
Consider using `hf_transfer` for faster uploads. This solution comes with some limitations. See https://huggingface.co/docs/huggingface_hub/hf_transfer for more details.

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