p71924506
/
CPM-9G-8B
forked from p83651209/CPM-9G-8B
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Delete sft_code.sh

This commit is contained in:
p83651209 2024-11-02 16:30:05 +08:00
parent 2f35baea6c
commit 7519028f67
1 changed files with 0 additions and 154 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

154
sft_code.sh
View File

@ -1,154 +0,0 @@
#!/bin/bash
deepspeed --include localhost:0,1,2,3,4,5,6,7 --master_port 21666 src/train.py \
--stage sft \
--model_name_or_path /mnt/diskhd/Backup/DownloadModel/2b_sft_model/ \
--do_train \
--dataset TACO \
--template jiuge \
--finetuning_type full \
--output_dir TACO \
--per_device_train_batch_size 14 \
--gradient_accumulation_steps 6 \
--lr_scheduler_type cosine \
--logging_step 1 \
--save_steps 300 \
--lr_scheduler_type cosine_with_restarts \
--warmup_ratio 0.001 \
--optim adamw_torch \
--learning_rate 2e-5 \
--num_train_epochs 2.0 \
--plot_loss \
--bf16 \
--gradient_checkpointing \
--report_to tensorboard \
--deepspeed deepspeed_configs/zero2.json \
--cutoff_len 2048
deepspeed --include localhost:0,1,2,3,4,5,6,7 --master_port 21666 src/train.py \
--stage sft \
--model_name_or_path /mnt/diskhd/Backup/DownloadModel/2b_sft_model/ \
--do_train \
--dataset Tested-143k-Python-Alpaca \
--template jiuge \
--finetuning_type full \
--output_dir Tested-143k-Python-Alpaca \
--per_device_train_batch_size 14 \
--gradient_accumulation_steps 6 \
--lr_scheduler_type cosine \
--logging_step 1 \
--save_steps 300 \
--lr_scheduler_type cosine_with_restarts \
--warmup_ratio 0.001 \
--optim adamw_torch \
--learning_rate 2e-5 \
--num_train_epochs 2.0 \
--plot_loss \
--bf16 \
--gradient_checkpointing \
--report_to tensorboard \
--deepspeed deepspeed_configs/zero2.json \
--cutoff_len 2048
deepspeed --include localhost:0,1,2,3,4,5,6,7 --master_port 21666 src/train.py \
--stage sft \
--model_name_or_path /mnt/diskhd/Backup/DownloadModel/2b_sft_model/ \
--do_train \
--dataset UltraInteract_sft \
--template jiuge \
--finetuning_type full \
--output_dir UltraInteract_sft \
--per_device_train_batch_size 14 \
--gradient_accumulation_steps 6 \
--lr_scheduler_type cosine \
--logging_step 1 \
--save_steps 300 \
--lr_scheduler_type cosine_with_restarts \
--warmup_ratio 0.001 \
--optim adamw_torch \
--learning_rate 2e-5 \
--num_train_epochs 2.0 \
--plot_loss \
--bf16 \
--gradient_checkpointing \
--report_to tensorboard \
--deepspeed deepspeed_configs/zero2.json \
--cutoff_len 2048
deepspeed --include localhost:0,1,2,3,4,5,6,7 --master_port 21666 src/train.py \
--stage sft \
--model_name_or_path /mnt/diskhd/Backup/DownloadModel/2b_sft_model/ \
--do_train \
--dataset code_instructions_120k_alpaca \
--template jiuge \
--finetuning_type full \
--output_dir code_instructions_120k_alpaca \
--per_device_train_batch_size 14 \
--gradient_accumulation_steps 6 \
--lr_scheduler_type cosine \
--logging_step 1 \
--save_steps 300 \
--lr_scheduler_type cosine_with_restarts \
--warmup_ratio 0.001 \
--optim adamw_torch \
--learning_rate 2e-5 \
--num_train_epochs 2.0 \
--plot_loss \
--bf16 \
--gradient_checkpointing \
--report_to tensorboard \
--deepspeed deepspeed_configs/zero2.json \
--cutoff_len 2048
deepspeed --include localhost:0,1,2,3,4,5,6,7 --master_port 21666 src/train.py \
--stage sft \
--model_name_or_path /mnt/diskhd/Backup/DownloadModel/2b_sft_model/ \
--do_train \
--dataset CodeExercise-Python-27k \
--template jiuge \
--finetuning_type full \
--output_dir CodeExercise-Python-27k \
--per_device_train_batch_size 14 \
--gradient_accumulation_steps 6 \
--lr_scheduler_type cosine \
--logging_step 1 \
--save_steps 300 \
--lr_scheduler_type cosine_with_restarts \
--warmup_ratio 0.001 \
--optim adamw_torch \
--learning_rate 2e-5 \
--num_train_epochs 2.0 \
--plot_loss \
--bf16 \
--gradient_checkpointing \
--report_to tensorboard \
--deepspeed deepspeed_configs/zero2.json \
--cutoff_len 2048
deepspeed --include localhost:0,1,2,3,4,5,6,7 --master_port 21666 src/train.py \
--stage sft \
--model_name_or_path /mnt/diskhd/Backup/DownloadModel/2b_sft_model/ \
--do_train \
--dataset CodeNet4Repair \
--template jiuge \
--finetuning_type full \
--output_dir CodeNet4Repair \
--per_device_train_batch_size 14 \
--gradient_accumulation_steps 6 \
--lr_scheduler_type cosine \
--logging_step 1 \
--save_steps 300 \
--lr_scheduler_type cosine_with_restarts \
--warmup_ratio 0.001 \
--optim adamw_torch \
--learning_rate 2e-5 \
--num_train_epochs 2.0 \
--plot_loss \
--bf16 \
--gradient_checkpointing \
--report_to tensorboard \
--deepspeed deepspeed_configs/zero2.json \
--cutoff_len 2048