Create README.md

README.md

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+---
+license: llama2
+datasets:
+- huangyt/FINETUNE2_TEST
+---
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+在llama-2-13b上使用huangyt/FINETUNE2_TEST資料集進行訓練，總資料筆數約17w
+
+# Fine-Tuning Information
+- **GPU:** RTX4090 (single core / 24564MiB)
+- **model:** meta-llama/Llama-2-13b-hf
+- **dataset:** huangyt/FINETUNE2_TEST (共約2.2w筆訓練集)
+- **peft_type:** LoRA
+- **lora_target:** q_proj, v_proj
+- **per_device_train_batch_size:** 8
+- **gradient_accumulation_steps:** 8
+- **learning_rate :** 5e-5
+- **epoch:** 1
+- **precision:** bf16
+- **quantization:** load_in_4bit
+
+# Fine-Tuning Detail
+- **train_loss:** 0.567
+- **train_runtime:** 2:47:57 (use deepspeed)
+
+# Evaluation
+- 評估結果來自**HuggingFaceH4/open_llm_leaderboard**
+- 與Llama-2-13b比較4種Benchmark，包含**ARC**、**HellaSwag**、**MMLU**、**TruthfulQA**
+
+| Model                                                  |Average|  ARC  |HellaSwag| MMLU  |TruthfulQA|
+|--------------------------------------------------------|-------|-------|---------|-------|----------|
+|meta-llama/Llama-2-13b-hf                               | 56.9  | 58.11 |  80.97  | 54.34 |  34.17   |
+|meta-llama/Llama-2-13b-chat-hf                          | 59.93 | 59.04 |  81.94  | 54.64 |  44.12   |
+|CHIH-HUNG/llama-2-13b-Fintune_1_17w                     | 58.24 | 59.47 |   81    | 54.31 |  38.17   |
+|CHIH-HUNG/llama-2-13b-huangyt_Fintune_1_17w-q_k_v_o_proj| 58.49 | 59.73 |  81.06  | 54.53 |  38.64   |
+|CHIH-HUNG/llama-2-13b-Fintune_1_17w-gate_up_down_proj   | 58.81 | 57.17 |  82.26  | 55.89 |  39.93   |
+
+# How to convert dataset to json
+
+- 在**load_dataset**中輸入資料集名稱，並且在**take**中輸入要取前幾筆資料
+- 觀察該資料集的欄位名稱，填入**example**欄位中(例如system_prompt、question、response)
+- 最後指定json檔儲存位置 (**json_filename**)
+
+```py
+import json
+from datasets import load_dataset
+
+# 讀取數據集，take可以取得該數據集前n筆資料
+dataset = load_dataset("huangyt/FINETUNE2_TEST", split="train", streaming=True)
+
+# 提取所需欄位並建立新的字典列表
+extracted_data = []
+for example in dataset:
+    extracted_example = {
+        "instruction": example["instruction"],
+        "input": example["input"],
+        "output": example["output"]
+    }
+    extracted_data.append(extracted_example)
+
+# 指定 JSON 文件名稱
+json_filename = "FINETUNE2_TEST.json"
+
+# 寫入 JSON 文件
+with open(json_filename, "w") as json_file:
+    json.dump(extracted_data, json_file, indent=4)
+
+print(f"數據已提取並保存為 {json_filename}")
+```