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6-7B.yml
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6-7B.yml
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# GPT-2 pretraining setup
{
# 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": 1,
# model settings
"num-layers": 32,
"hidden-size": 4096,
"num-attention-heads": 32,
"seq-length": 2048,
"max-position-embeddings": 2048,
"norm": "layernorm",
"pos-emb": "rotary",
"no-weight-tying": true,
"gpt_j_residual": false,
"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": false,
"bias-gelu-fusion": false,
# init methods
"init_method": "small_init",
"output_layer_init_method": "wang_init",
# optimizer settings
"optimizer": {
"type": "Adam",
"params": {
"lr": 0.00012,
"betas": [0.9, 0.95],
"eps": 1.0e-8,
}
},
# for all zero_optimization options, see https://www.deepspeed.ai/docs/config-json/#zero-optimizations-for-fp16-training
"zero_optimization": {
"stage": 1,
"allgather_partitions": True,
"allgather_bucket_size": 500000000,
"overlap_comm": True,
"reduce_scatter": True,
"reduce_bucket_size": 500000000,
"contiguous_gradients": True,
},
"min_lr": 0.000012,
# batch / data settings
"train_micro_batch_size_per_gpu": 4,
"data-impl": "mmap",
# 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
"fp16": {
"fp16": true,
"enabled": true,
"loss_scale": 0,
"loss_scale_window": 1000,
"hysteresis": 2,
"min_loss_scale": 1
},
# misc. training settings
"train-iters": 320000,
"lr-decay-iters": 320000,
"distributed-backend": "nccl",
"lr-decay-style": "cosine",
"warmup": 0.01,
"checkpoint-factor": 10000,
"eval-interval": 1000,
"eval-iters": 10,
# logging
"log-interval": 100,
"steps_per_print": 10,
"keep-last-n-checkpoints": 4,
"wall_clock_breakdown": true,
}