eleutherai-oslo

Eleutherai-oslo's group workspace

Group: j6eW99b7adtz2siaCUHGKE_1pxd2l2g

1-2

of 2

Tags

Notes

Author

eleutherai-oslo

State

Crashed

Start time

April 20th, 2023 1:54:32 AM

Runtime

1m 5s

Tracked hours

Run path

eleutherai-oslo/polyglot-ko-12_8b/9hrgnv4k

Linux-5.15.0-1019-aws-x86_64-with-glibc2.31

Python version

3.9.16

Git repository

git clone https://github.com/EleutherAI/gpt-neox.git

Git state

git checkout -b "ip-26-0-129-82-0" bf9b3012943259407c4274604504193228b3c3f0

Command

/fsx/polyglot.train/gpt-neox/train.py --deepspeed_config "{\"train_batch_size\": 64, \"train_micro_batch_size_per_gpu\": 8, \"gradient_accumulation_steps\": 2, \"optimizer\": {\"type\": \"Adam\", \"params\": {\"lr\": 0.0001, \"betas\": [0.9, 0.95], \"eps\": 1e-08}}, \"fp16\": {\"fp16\": true, \"enabled\": true, \"initial_scale_power\": 32, \"loss_scale_window\": 1000, \"hysteresis\": 2, \"min_loss_scale\": 1}, \"gradient_clipping\": 1.0, \"zero_optimization\": {\"stage\": 1, \"allgather_partitions\": true, \"allgather_bucket_size\": 500000000, \"overlap_comm\": true, \"reduce_scatter\": true, \"reduce_bucket_size\": 500000000, \"contiguous_gradients\": true, \"cpu_offload\": false}, \"wall_clock_breakdown\": true}" --megatron_config "{\"hostfile\": \"/fsx/polyglot.train/hostfiles/hosts_163635\", \"launcher\": \"openmpi\", \"train_batch_size\": 64, \"train_micro_batch_size_per_gpu\": 8, \"gradient_accumulation_steps\": 2, \"optimizer\": {\"type\": \"Adam\", \"params\": {\"lr\": 0.0001, \"betas\": [0.9, 0.95], \"eps\": 1e-08}}, \"fp16\": {\"fp16\": true, \"enabled\": true, \"initial_scale_power\": 32, \"loss_scale_window\": 1000, \"hysteresis\": 2, \"min_loss_scale\": 1}, \"gradient_clipping\": 1.0, \"zero_optimization\": {\"stage\": 1, \"allgather_partitions\": true, \"allgather_bucket_size\": 500000000, \"overlap_comm\": true, \"reduce_scatter\": true, \"reduce_bucket_size\": 500000000, \"contiguous_gradients\": true, \"cpu_offload\": false}, \"wall_clock_breakdown\": true, \"precision\": \"fp16\", \"num_layers\": 36, \"hidden_size\": 5120, \"num_attention_heads\": 40, \"seq_length\": 2048, \"max_position_embeddings\": 2048, \"pos_emb\": \"rotary\", \"no_weight_tying\": true, \"attention_config\": [\"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\", \"global\"], \"sparsity_config\": {}, \"scaled_upper_triang_masked_softmax_fusion\": true, \"bias_gelu_fusion\": true, \"rotary_ndims\": 64, \"init_method\": \"small_init\", \"output_layer_init_method\": \"wang_init\", \"gpt_j_residual\": true, \"output_layer_parallelism\": \"column\", \"lr_decay_style\": \"cosine\", \"lr_decay_iters\": 500000, \"min_lr\": 1e-05, \"optimizer_type\": \"Adam\", \"zero_stage\": 1, \"zero_reduce_scatter\": true, \"zero_contiguous_gradients\": true, \"zero_reduce_bucket_size\": 500000000, \"zero_allgather_bucket_size\": 500000000, \"lr\": 0.0001, \"tokenizer_type\": \"HFTokenizer\", \"data_path\": \"/fsx/polyglot.train/gpt-neox/processed/multi_ko_13b_text_document\", \"data_impl\": \"mmap\", \"save\": \"/fsx/polyglot.train/gpt-neox/checkpoints/13B_scratch\", \"config_files\": {\"13B_ko.yml\": \"# GPT-2 pretraining setup\n{\n # Tokenizer / checkpoint settings - you will need to change these to the location you have them saved in\n \\"tokenizer-type\\": \\"HFTokenizer\\",\n \\"vocab-file\\": \\"./tokenizer/MBBPE/tokenizer.json\\",\n \\"save\\": \\"/fsx/polyglot.train/gpt-neox/checkpoints/13B_scratch\\",\n # \\"load\\": \\"/fsx/polyglot.train/gpt-neox/checkpoints/6B_scratch\\",\n\n # wandb config\n \\"wandb_team\\": \\"eleutherai-oslo\\",\n\n # If finetuning, edit the following to the location of your finetuning dataset:\n \\"data-path\\": \\"/fsx/polyglot.train/gpt-neox/processed/multi_ko_13b_text_document\\",\n # parallelism settings ( you will want to change these based on your cluster setup, ideally scheduling pipeline stages\n # across the node boundaries )\n \\"pipe-parallel-size\\": 1,\n \\"model-parallel-size\\": 4,\n\n # model settings\n \\"num-layers\\": 36,\n \\"hidden-size\\": 5120,\n \\"num-attention-heads\\": 40,\n \\"seq-length\\": 2048,\n \\"max-position-embeddings\\": 2048,\n \\"norm\\": \\"layernorm\\",\n \\"pos-emb\\": \\"rotary\\",\n \\"no-weight-tying\\": true,\n \\"rotary_ndims\\": 64,\n \\"gpt_j_residual\\": true,\n \\"output_layer_parallelism\\": \\"column\\",\n\n # these should provide some speedup but takes a while to build, set to true if desired\n \\"scaled-upper-triang-masked-softmax-fusion\\": true,\n \\"bias-gelu-fusion\\": true,\n\n # init methods\n \\"init_method\\": \\"small_init\\",\n \\"output_layer_init_method\\": \\"wang_init\\",\n\n # optimizer settings\n \\"optimizer\\": {\n \\"type\\": \\"Adam\\",\n \\"params\\": {\n \\"lr\\": 0.0001,\n \\"betas\\": [0.9, 0.95],\n \\"eps\\": 1.0e-8,\n }\n },\n \\"min_lr\\": 0.00001,\n \\"zero_optimization\\": {\n \\"stage\\": 1,\n \\"allgather_partitions\\": True,\n \\"allgather_bucket_size\\": 500000000,\n \\"overlap_comm\\": True,\n \\"reduce_scatter\\": True,\n \\"reduce_bucket_size\\": 500000000,\n \\"contiguous_gradients\\": True,\n \\"cpu_offload\\": False\n },\n\n # batch / data settings\n \\"train_micro_batch_size_per_gpu\\": 8,\n \\"gradient_accumulation_steps\\": 2,\n \\"data-impl\\": \\"mmap\\",\n # \\"split\\": \\"949,50,1\\",\n\n # activation checkpointing\n \\"checkpoint-activations\\": true,\n \\"checkpoint-num-layers\\": 1,\n \\"partition-activations\\": true,\n \\"synchronize-each-layer\\": true,\n\n # regularization\n \\"gradient_clipping\\": 1.0,\n \\"weight-decay\\": 0.1,\n \\"hidden-dropout\\": 0,\n \\"attention-dropout\\": 0,\n\n # precision settings\n # \\"attention_softmax_in_fp32\\": true,\n \\"fp16\\": {\n \\"fp16\\": true,\n \\"enabled\\": true,\n \\"initial_scale_power\\": 32,\n \\"loss_scale_window\\": 1000,\n \\"hysteresis\\": 2,\n \\"min_loss_scale\\": 1\n },\n\n # misc. training settings\n \\"train-iters\\": 500000,\n \\"lr-decay-iters\\": 500000,\n \\"distributed-backend\\": \\"nccl\\",\n \\"lr-decay-style\\": \\"cosine\\",\n \\"warmup\\": 0.01,\n \\"save-interval\\": 1000,\n \\"eval-interval\\": 1000,\n \\"eval-tasks-interval\\": 50000000000,\n \\"eval-iters\\": 10,\n\n # logging\n \\"log-interval\\": 100,\n \\"steps_per_print\\": 10,\n \\"keep-last-n-checkpoints\\": 5,\n \\"wall_clock_breakdown\\": true,\n\n # wandb\n \\"use_wandb\\": true,\n # \\"wandb_init_all_ranks\\": true,\n \\"wandb_project\\": \\"polyglot-ko-12_8b\\",\n \\"eval_tasks\\": [\\"nsmc\\"],\n\n # deepspeed launcher\n \\"launcher\\": \\"openmpi\\",\n \\"deepspeed_mpi\\": true\n}\n\"}, \"save_interval\": 1000, \"batch_size\": 8, \"train_iters\": 500000, \"eval_iters\": 10, \"keep_last_n_checkpoints\": 5, \"eval_tasks_interval\": 50000000000, \"vocab_file\": \"./tokenizer/MBBPE/tokenizer.json\", \"attention_dropout\": 0, \"hidden_dropout\": 0, \"weight_decay\": 0.1, \"checkpoint_activations\": true, \"synchronize_each_layer\": true, \"partition_activations\": true, \"gas\": 2, \"clip_grad\": 1.0, \"dynamic_loss_scale\": true, \"pipe_parallel_size\": 1, \"model_parallel_size\": 4, \"is_pipe_parallel\": true, \"use_wandb\": true, \"wandb_group\": \"j6eW99b7adtz2siaCUHGKE_1pxd2l2g\", \"wandb_team\": \"eleutherai-oslo\", \"wandb_project\": \"polyglot-ko-12_8b\", \"log_interval\": 100, \"text_gen_type\": \"unconditional\", \"eval_tasks\": [\"nsmc\"], \"deepspeed_mpi\": true, \"user_script\": \"/fsx/polyglot.train/gpt-neox/train.py\", \"global_num_gpus\": 16}"

System Hardware

CPU count	96
GPU count	8
GPU type	NVIDIA A100-SXM4-40GB

W&B CLI Version

0.12.21

Group

j6eW99b7adtz2siaCUHGKE_1pxd2l2g

Config parameters are your model's inputs. Learn more

▶
Config parameters:{} 185 keys
- activation:
  "gelu"
- adlr_autoresume:
  false
- adlr_autoresume_interval:
  1,000
- amp:
  null
- apply_query_key_layer_scaling:
  false
- ▶
  attention_config:[] 36 items
- attention_dropout:
  0
- attention_softmax_in_fp32:
  false
- batch_size:
  8
- bias_dropout_fusion:
  false
- bias_gelu_fusion:
  true
- char_level_ppl:
  false
- checkpoint_activations:
  true
- checkpoint_in_cpu:
  false
- checkpoint_num_layers:
  1
- checkpoint_validation_with_forward_pass:
  false
- clip_grad:
  1
- ▶
  config_files:{} 1 key
  - 13B_ko.yml:
    "# GPT-2 pretraining setup { # Tokenizer / checkpoint settings - you will need to change these to the location you have them saved in "tokenizer-type": "HFTokenizer", "vocab-file": "./tokenizer/MBBPE/tokenizer.json", "save": "/fsx/polyglot.train/gpt-neox/checkpoints/13B_scratch", # "load": "/fsx/polyglot.train/gpt-neox/checkpoints/6B_scratch", # wandb config "wandb_team": "eleutherai-oslo", # If finetuning, edit the following to the location of your finetuning dataset: "data-path": "/fsx/polyglot.train/gpt-neox/processed/multi_ko_13b_text_document", # parallelism settings ( you will want to change these based on your cluster setup, ideally scheduling pipeline stages # across the node boundaries ) "pipe-parallel-size": 1, "model-parallel-size": 4, # model settings "num-layers": 36, "hidden-size": 5120, "num-attention-heads": 40, "seq-length": 2048, "max-position-embeddings": 2048, "norm": "layernorm", "pos-emb": "rotary", "no-weight-tying": true, "rotary_ndims": 64, "gpt_j_residual": true, "output_layer_parallelism": "column", # these should provide some speedup but takes a while to build, set to true if desired "scaled-upper-triang-masked-softmax-fusion": true, "bias-gelu-fusion": true, # init methods "init_method": "small_init", "output_layer_init_method": "wang_init", # optimizer settings "optimizer": { "type": "Adam", "params": { "lr": 0.0001, "betas": [0.9, 0.95], "eps": 1.0e-8, } }, "min_lr": 0.00001, "zero_optimization": { "stage": 1, "allgather_partitions": True, "allgather_bucket_size": 500000000, "overlap_comm": True, "reduce_scatter": True, "reduce_bucket_size": 500000000, "contiguous_gradients": True, "cpu_offload": False }, # batch / data settings "train_micro_batch_size_per_gpu": 8, "gradient_accumulation_steps": 2, "data-impl": "mmap", # "split": "949,50,1", # activation checkpointing "checkpoint-activations": true, "checkpoint-num-layers": 1, "partition-activations": true, "synchronize-each-layer": true, # regularization "gradient_clipping": 1.0, "weight-decay": 0.1, "hidden-dropout": 0, "attention-dropout": 0, # precision settings # "attention_softmax_in_fp32": true, "fp16": { "fp16": true, "enabled": true, "initial_scale_power": 32, "loss_scale_window": 1000, "hysteresis": 2, "min_loss_scale": 1 }, # misc. training settings "train-iters": 500000, "lr-decay-iters": 500000, "distributed-backend": "nccl", "lr-decay-style": "cosine", "warmup": 0.01, "save-interval": 1000, "eval-interval": 1000, "eval-tasks-interval": 50000000000, "eval-iters": 10, # logging "log-interval": 100, "steps_per_print": 10, "keep-last-n-checkpoints": 5, "wall_clock_breakdown": true, # wandb "use_wandb": true, # "wandb_init_all_ranks": true, "wandb_project": "polyglot-ko-12_8b", "eval_tasks": ["nsmc"], # deepspeed launcher "launcher": "openmpi", "deepspeed_mpi": true } "
- contiguous_checkpointing:
  false
- data_impl:
  "mmap"
- data_path:
  "/fsx/polyglot.train/gpt-neox/processed/multi_ko_13b_text_document"
- deepscale:
  false
- deepscale_config:
  null
- deepspeed:
  true
- deepspeed_activation_checkpointing:
  true
- deepspeed_mpi:
  true
- detect_nvlink_pairs:
  false
- distributed_backend:
  "nccl"
- do_test:
  null
- do_train:
  null
- do_valid:
  null
- dump_state:
  false
- dynamic_loss_scale:
  true
- eod_mask_loss:
  false
- eval_interval:
  1,000
- eval_iters:
  10
- eval_results_prefix:
  ""
- ▶
  eval_tasks:[] 1 item
  - 0:
    "nsmc"
- eval_tasks_interval:
  50,000,000,000
- exclude:
  null
- exit_interval:
  null
- finetune:
  false
- flops_profiler:
  null
- ▶
  fp16:{} 6 keys
- fp16_lm_cross_entropy:
  false
- fp32_allreduce:
  false
- ▶
  zero_optimization:{} 8 keys
- zero_reduce_bucket_size:
  500,000,000
- zero_reduce_scatter:
  true
- zero_stage:
  1

Summary metrics are your model's outputs. Learn more

No summary metrics saved for this run.

Check the summary metrics documentation for more information.

This run produced these artifacts as outputs. Total: 1. Learn more

wandb-events

run-9hrgnv4k-events:v0