summary / fengshen /examples /classification /demo_classification_afqmc_roberta_deepspeed.sh
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MODEL_NAME="IDEA-CCNL/Erlangshen-Roberta-110M-NLI"
TEXTA_NAME=sentence1
TEXTB_NAME=sentence2
LABEL_NAME=label
ID_NAME=id
BATCH_SIZE=32
VAL_BATCH_SIZE=32
ZERO_STAGE=1
config_json="./ds_config.json"
cat <<EOT > $config_json
{
"train_micro_batch_size_per_gpu": $BATCH_SIZE,
"steps_per_print": 1000,
"gradient_clipping": 0.1,
"zero_optimization": {
"stage": ${ZERO_STAGE}
},
"zero_allow_untested_optimizer": false,
"fp16": {
"enabled": true,
"loss_scale": 0,
"loss_scale_window": 1000,
"hysteresis": 2,
"min_loss_scale": 1
},
"activation_checkpointing": {
"partition_activations": false,
"contiguous_memory_optimization": false
},
"wall_clock_breakdown": false
}
EOT
export PL_DEEPSPEED_CONFIG_PATH=$config_json
DATA_ARGS="\
--dataset_name IDEA-CCNL/AFQMC \
--train_batchsize $BATCH_SIZE \
--valid_batchsize $VAL_BATCH_SIZE \
--max_length 128 \
--texta_name $TEXTA_NAME \
--textb_name $TEXTB_NAME \
--label_name $LABEL_NAME \
--id_name $ID_NAME \
"
MODEL_ARGS="\
--learning_rate 1e-5 \
--weight_decay 1e-2 \
--warmup_ratio 0.01 \
--num_labels 2 \
--model_type huggingface-auto \
"
MODEL_CHECKPOINT_ARGS="\
--monitor val_acc \
--save_top_k 3 \
--mode max \
--every_n_train_steps 0 \
--save_weights_only True \
--dirpath . \
--filename model-{epoch:02d}-{val_acc:.4f} \
"
TRAINER_ARGS="\
--max_epochs 67 \
--gpus 1 \
--num_nodes 1 \
--strategy deepspeed_stage_${ZERO_STAGE} \
--gradient_clip_val 1.0 \
--check_val_every_n_epoch 1 \
--val_check_interval 1.0 \
--precision 16 \
--default_root_dir . \
"
options=" \
--pretrained_model_path $MODEL_NAME \
$DATA_ARGS \
$MODEL_ARGS \
$MODEL_CHECKPOINT_ARGS \
$TRAINER_ARGS \
"
python3 finetune_classification.py $options