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README.md

@@ -1,7 +1,7 @@
 ---
 base_model: Qwen/Qwen3-4B-Instruct-2507
 datasets:
-- u-10bei/structured_data_with_cot_dataset_512_v5
+- u-10bei/structured_data_with_cot_dataset_512_v2
 language:
 - en
 license: apache-2.0
@@ -13,7 +13,7 @@ tags:
 - structured-output
 ---
 
-＜【課題】ここは自分で記入して下さい＞
+qwen3-4b-lora-for-LLM2025A
 
 This repository provides a **LoRA adapter** fine-tuned from
 **Qwen/Qwen3-4B-Instruct-2507** using **QLoRA (4-bit, Unsloth)**.
@@ -33,9 +33,9 @@ while intermediate reasoning (Chain-of-Thought) is masked.
 
 - Base model: Qwen/Qwen3-4B-Instruct-2507
 - Method: QLoRA (4-bit)
-- Max sequence length: 512
+- Max sequence length: 1024
 - Epochs: 1
-- Learning rate: 1e-06
+- Learning rate: 2e-05
 - LoRA: r=64, alpha=128
 
 ## Usage
@@ -59,7 +59,7 @@ model = PeftModel.from_pretrained(model, adapter)
 
 ## Sources & Terms (IMPORTANT)
 
-Training data: u-10bei/structured_data_with_cot_dataset_512_v5
+Training data: u-10bei/structured_data_with_cot_dataset_512_v2
 
 Dataset License: MIT License. This dataset is used and distributed under the terms of the MIT License.
 Compliance: Users must comply with the MIT license (including copyright notice) and the base model's original terms of use.

adapter_config.json

@@ -33,12 +33,12 @@
   "rank_pattern": {},
   "revision": null,
   "target_modules": [
-    "v_proj",
     "down_proj",
-    "up_proj",
-    "gate_proj",
     "k_proj",
+    "gate_proj",
     "o_proj",
+    "v_proj",
+    "up_proj",
     "q_proj"
   ],
   "target_parameters": null,

adapter_model.safetensors

@@ -1,3 +1,3 @@
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+oid sha256:9b75d61e23d84f4fb3b7c2c6d23545f8454f2a79836d514687a8de806cc458b6
 size 528550256