File size: 5,678 Bytes
a20151e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 | # WANDB_MODE=online CUDA_VISIBLE_DEVICES=6 python src/lgmodeling/train_model.py \
# --seed 0 --tgt_len 512 --mem_len 512 --eval_tgt_len 128 --position-embeddings "learnable" \
# --num-shared-experts 1 --num-routed-experts 0 --topk 0 --rotary-dim 64 \
# --n_layer 12 --n_embd 512 --n_head 8 --n_inner 2048 --attention-bias \
# --learning-rate 0.00025 --batch-size 24 --max_step 60000 --warmup_step 0 --dataset enwik8 \
# --wandb-project LMC-Attention --wandb-group "GPT2-Enwik8-FFN" --wandb-entity "vinh-bui0512-hcmut"\
# --model-save-dir /mnt/data/vinhbk/weights/enwik8 --data-path /mnt/data/vinhbk/datasets/enwik8
# WANDB_MODE=online CUDA_VISIBLE_DEVICES=6 python src/lgmodeling/train_model.py \
# --seed 0 --tgt_len 512 --mem_len 512 --eval_tgt_len 128 --position-embeddings "rope" \
# --num-shared-experts 1 --num-routed-experts 0 --topk 0 --rotary-dim 64 \
# --n_layer 12 --n_embd 512 --n_head 8 --n_inner 2048 --attention-bias \
# --learning-rate 0.00025 --batch-size 24 --max_step 60000 --warmup_step 0 --dataset enwik8 \
# --wandb-project LMC-Attention --wandb-group "GPT2-Enwik8-FFN" --wandb-entity "vinh-bui0512-hcmut"\
# --model-save-dir /mnt/data/vinhbk/weights/enwik8 --data-path /mnt/data/vinhbk/datasets/enwik8
# WANDB_MODE=online CUDA_VISIBLE_DEVICES=6 python src/lgmodeling/train_model.py \
# --seed 0 --tgt_len 512 --mem_len 512 --eval_tgt_len 128 --position-embeddings "sinusoidal" \
# --num-shared-experts 1 --num-routed-experts 0 --topk 0 --rotary-dim 64 \
# --n_layer 12 --n_embd 512 --n_head 8 --n_inner 2048 --attention-bias \
# --learning-rate 0.00025 --batch-size 24 --max_step 60000 --warmup_step 0 --dataset enwik8 \
# --wandb-project LMC-Attention --wandb-group "GPT2-Enwik8-FFN" --wandb-entity "vinh-bui0512-hcmut"\
# --model-save-dir /mnt/data/vinhbk/weights/enwik8 --data-path /mnt/data/vinhbk/datasets/enwik8
WANDB_MODE=online CUDA_VISIBLE_DEVICES=6 python src/lgmodeling/train_model.py \
--seed 0 --tgt_len 512 --mem_len 512 --eval_tgt_len 128 --position-embeddings "learnable" \
--num-shared-experts 0 --num-routed-experts 4 --topk 4 --rotary-dim 64 \
--n_layer 12 --n_embd 512 --n_head 8 --n_inner 2048 --attention-bias \
--learning-rate 0.00025 --batch-size 24 --max_step 60000 --warmup_step 0 --dataset enwik8 \
--wandb-project LMC-Attention --wandb-group "GPT2-Enwik8-MoE" --wandb-entity "vinh-bui0512-hcmut"\
--model-save-dir /mnt/data/vinhbk/weights/enwik8 --data-path /mnt/data/vinhbk/datasets/enwik8
WANDB_MODE=online CUDA_VISIBLE_DEVICES=6 python src/lgmodeling/train_model.py \
--seed 0 --tgt_len 512 --mem_len 512 --eval_tgt_len 128 --position-embeddings "rope" \
--num-shared-experts 0 --num-routed-experts 4 --topk 4 --rotary-dim 64 \
--n_layer 12 --n_embd 512 --n_head 8 --n_inner 2048 --attention-bias \
--learning-rate 0.00025 --batch-size 24 --max_step 60000 --warmup_step 0 --dataset enwik8 \
--wandb-project LMC-Attention --wandb-group "GPT2-Enwik8-MoE" --wandb-entity "vinh-bui0512-hcmut"\
--model-save-dir /mnt/data/vinhbk/weights/enwik8 --data-path /mnt/data/vinhbk/datasets/enwik8
WANDB_MODE=online CUDA_VISIBLE_DEVICES=6 python src/lgmodeling/train_model.py \
--seed 0 --tgt_len 512 --mem_len 512 --eval_tgt_len 128 --position-embeddings "sinusoidal" \
--num-shared-experts 0 --num-routed-experts 4 --topk 4 --rotary-dim 64 \
--n_layer 12 --n_embd 512 --n_head 8 --n_inner 2048 --attention-bias \
--learning-rate 0.00025 --batch-size 24 --max_step 60000 --warmup_step 0 --dataset enwik8 \
--wandb-project LMC-Attention --wandb-group "GPT2-Enwik8-MoE" --wandb-entity "vinh-bui0512-hcmut"\
--model-save-dir /mnt/data/vinhbk/weights/enwik8 --data-path /mnt/data/vinhbk/datasets/enwik8
WANDB_MODE=online CUDA_VISIBLE_DEVICES=6 python src/lgmodeling/train_model.py \
--seed 0 --tgt_len 512 --mem_len 512 --eval_tgt_len 128 --position-embeddings "learnable" \
--num-shared-experts 0 --num-routed-experts 4 --topk 2 --rotary-dim 64 \
--n_layer 12 --n_embd 512 --n_head 8 --n_inner 2048 --attention-bias \
--learning-rate 0.00025 --batch-size 24 --max_step 60000 --warmup_step 0 --dataset enwik8 \
--wandb-project LMC-Attention --wandb-group "GPT2-Enwik8-SMoE" --wandb-entity "vinh-bui0512-hcmut"\
--model-save-dir /mnt/data/vinhbk/weights/enwik8 --data-path /mnt/data/vinhbk/datasets/enwik8
WANDB_MODE=online CUDA_VISIBLE_DEVICES=6 python src/lgmodeling/train_model.py \
--seed 0 --tgt_len 512 --mem_len 512 --eval_tgt_len 128 --position-embeddings "rope" \
--num-shared-experts 0 --num-routed-experts 4 --topk 2 --rotary-dim 64 \
--n_layer 12 --n_embd 512 --n_head 8 --n_inner 2048 --attention-bias \
--learning-rate 0.00025 --batch-size 24 --max_step 60000 --warmup_step 0 --dataset enwik8 \
--wandb-project LMC-Attention --wandb-group "GPT2-Enwik8-SMoE" --wandb-entity "vinh-bui0512-hcmut"\
--model-save-dir /mnt/data/vinhbk/weights/enwik8 --data-path /mnt/data/vinhbk/datasets/enwik8
WANDB_MODE=online CUDA_VISIBLE_DEVICES=6 python src/lgmodeling/train_model.py \
--seed 0 --tgt_len 512 --mem_len 512 --eval_tgt_len 128 --position-embeddings "sinusoidal" \
--num-shared-experts 0 --num-routed-experts 4 --topk 2 --rotary-dim 64 \
--n_layer 12 --n_embd 512 --n_head 8 --n_inner 2048 --attention-bias \
--learning-rate 0.00025 --batch-size 24 --max_step 60000 --warmup_step 0 --dataset enwik8 \
--wandb-project LMC-Attention --wandb-group "GPT2-Enwik8-SMoE" --wandb-entity "vinh-bui0512-hcmut"\
--model-save-dir /mnt/data/vinhbk/weights/enwik8 --data-path /mnt/data/vinhbk/datasets/enwik8 |