75 lines
2.8 KiB
Markdown
75 lines
2.8 KiB
Markdown
---
|
||
license: llama2
|
||
datasets:
|
||
- huangyt/FINETUNE1
|
||
---
|
||
# Model Card for Model ID
|
||
|
||
<!-- Provide a quick summary of what the model is/does. -->
|
||
|
||
在llama-2-13b上使用huangyt/FINETUNE1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/FINETUNE1 (共約17w筆訓練集)
|
||
- **peft_type:** LoRA
|
||
- **lora_rank:** 8
|
||
- **lora_target:** q_proj, k_proj, v_proj, o_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:** 0.688
|
||
- **train_runtime:** 15:44:38 (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 |
|
||
|CHIH-HUNG/llama-2-13b-FINETUNE1_17w-r16 | 58.86 | 57.25 | 82.27 | 56.16 | 39.75 |
|
||
|CHIH-HUNG/llama-2-13b-FINETUNE1_17w-r4 | 58.71 | 56.74 | 82.27 | 56.18 | 39.65 |
|
||
|
||
# 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/FINETUNE1", 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 = "huangyt_FINETUNE_1.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}")
|
||
``` |