Upload ms-swift/examples/eval/train_eval/train.sh with huggingface_hub

ms-swift/examples/eval/train_eval/train.sh

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+CUDA_VISIBLE_DEVICES=0 \
+swift sft \
+  --model "Qwen/Qwen2.5-0.5B-Instruct" \
+  --train_type "lora" \
+  --dataset "AI-ModelScope/alpaca-gpt4-data-zh#100" \
+  --torch_dtype "bfloat16" \
+  --num_train_epochs "1" \
+  --per_device_train_batch_size "1" \
+  --learning_rate "1e-4" \
+  --lora_rank "8" \
+  --lora_alpha "32" \
+  --target_modules "all-linear" \
+  --gradient_accumulation_steps "16" \
+  --save_steps "50" \
+  --save_total_limit "5" \
+  --logging_steps "5" \
+  --max_length "2048" \
+  --eval_strategy "steps" \
+  --eval_steps "5" \
+  --per_device_eval_batch_size "5" \
+  --eval_use_evalscope \
+  --eval_datasets "gsm8k" \
+  --eval_datasets_args '{"gsm8k": {"few_shot_num": 0}}' \
+  --eval_limit "10"