Upload models/scripts/finetune_qwen2_5.sh with huggingface_hub

models/scripts/finetune_qwen2_5.sh

@@ -0,0 +1,49 @@
+#!/bin/bash
+
+# You can use 2B instead of 7B
+# MODEL_NAME="Qwen/Qwen2-VL-7B-Instruct"
+# MODEL_NAME="Qwen/Qwen2-VL-2B-Instruct"
+MODEL_NAME="Qwen/Qwen2.5-VL-7B-Instruct"
+# MODEL_NAME="Qwen/Qwen2.5-VL-7B-Instruct"
+
+GLOBAL_BATCH_SIZE=128
+BATCH_PER_DEVICE=4
+NUM_DEVICES=8
+GRAD_ACCUM_STEPS=$((GLOBAL_BATCH_SIZE / (BATCH_PER_DEVICE * NUM_DEVICES)))
+
+export PYTHONPATH=src:$PYTHONPATH
+
+deepspeed src/training/train.py \
+    --use_liger True \
+    --deepspeed scripts/zero2_offload.json \
+    --model_id $MODEL_NAME \
+    --data_path /home/world_model/EVA/train_data_v4/dataset_stage0_600k.json \
+    --image_folder /home/world_model/ \
+    --remove_unused_columns False \
+    --freeze_vision_tower False \
+    --freeze_llm False \
+    --tune_merger True \
+    --bf16 True \
+    --fp16 False \
+    --disable_flash_attn2 False \
+    --output_dir output/fft_qwen2_5vl \
+    --num_train_epochs 1 \
+    --per_device_train_batch_size $BATCH_PER_DEVICE \
+    --gradient_accumulation_steps $GRAD_ACCUM_STEPS \
+    --image_min_pixels $((512 * 28 * 28)) \
+    --image_max_pixels $((1280 * 28 * 28)) \
+    --learning_rate 1e-5 \
+    --merger_lr 1e-5 \
+    --vision_lr 2e-6 \
+    --weight_decay 0.1 \
+    --warmup_ratio 0.03 \
+    --lr_scheduler_type "cosine" \
+    --logging_steps 1 \
+    --tf32 True \
+    --gradient_checkpointing True \
+    --report_to tensorboard \
+    --lazy_preprocess True \
+    --save_strategy "steps" \
+    --save_steps 200 \
+    --save_total_limit 10 \
+    --dataloader_num_workers 4