Update run_train_test.sh

run_train_test.sh

@@ -5,7 +5,10 @@ TRAIN_ARGS="--train_iters 50000 --lr_decay_style cosine
 --lr_warmup_iters 50 --lr 1e-5 --min_lr 1e-6  --use_flash_attn 
 --attention_dropout 0.0 --adam_beta1 0.9 --adam_beta2 0.95 --adam_eps 1e-5"
 
+### for one node, 8GPUs
 DISTRIBUTED_ARGS="--nproc_per_node 8 --nnodes 1 --node_rank 0 --master_addr localhost --master_port 8000"
+
+# ### for multi nodes, 8GPUs
 # DISTRIBUTED_ARGS="--nproc_per_node 8 --nnodes 2 --node_rank $RANK --master_addr $MASTER_ADDR --master_port $MASTER_PORT"
 
 LLAMA2_ARGS=" --no_bias_gelu_fusion --no_bias_dropout_fusion 
@@ -25,9 +28,11 @@ torchrun $DISTRIBUTED_ARGS finetune.py \
 	--vocab_file megatron_test/llama2_tokenizer.model \
 	--bf16 \
 	--micro_batch_size 4 \
-	--global_batch_size 16 \
+	--global_batch_size 128 \
 	--sequence_parallel \
     --recompute_granularity selective \
 	--use_checkpoint_args \
     $COMMON_ARGS $LOG_ARGS $TRAIN_ARGS $LLAMA2_ARGS
 
+### Increase the micro_batch_size, if you have 80G GPU
+### Decrease the micro_batch_size, if you need to train larger model