docs(finetune): 模型微调实现

Author: zjZSTU

docs/微调模型.md

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+
+# 微调模型
+
+本工程通过`PyTorch`库进行卷积网络训练，其微调实现参考[迁移学习](https://blog.zhujian.life/posts/c7511b44.html)
+
+## 预训练模型
+
+`PyTorch`提供了`AlexNet`的预训练模型
+
+## python文件
+
+* 微调实现：`py/finetune.py`
+* 自定义微调数据集类：`py/utils/data/custom_finetune_dataset.py`
+* 自定义批量采样器类：`py/utils/data/custom_batch_sampler.py`
+* 辅助函数：`py/utils/util.py`
+
+## 训练参数
+
+* 批量处理：每次训练`128`个图像，其中`32`个正样本，`96`个负样本
+* 输入模型图像：缩放到`(227, 227)`，随机水平翻转，进行归一化操作
+* 优化器
+    * 使用`SGD`：学习率为`1e-3`，动量大小为`0.9`
+    * 随步长衰减：每隔`7`轮衰减一次，衰减因子为`0.1`
+* 迭代次数：`25`轮
+
+## 训练结果
+
+```
+$ python finetune.py 
+...
+...
+Epoch 0/24
+----------
+train Loss: 0.1906 Acc: 0.9163
+val Loss: 0.3662 Acc: 0.8692
+
+Epoch 1/24
+----------
+train Loss: 0.1204 Acc: 0.9499
+val Loss: 0.4081 Acc: 0.8701
+
+Epoch 2/24
+----------
+train Loss: 0.0958 Acc: 0.9608
+val Loss: 0.4002 Acc: 0.8719
+
+Epoch 3/24
+----------
+train Loss: 0.0825 Acc: 0.9663
+val Loss: 0.4505 Acc: 0.8725
+
+Epoch 4/24
+----------
+train Loss: 0.0726 Acc: 0.9707
+val Loss: 0.5031 Acc: 0.8697
+
+Epoch 5/24
+----------
+train Loss: 0.0662 Acc: 0.9733
+val Loss: 0.5340 Acc: 0.8681
+
+Epoch 6/24
+----------
+train Loss: 0.0611 Acc: 0.9754
+Qval Loss: 0.5102 Acc: 0.8714
+
+Epoch 7/24
+----------
+train Loss: 0.0505 Acc: 0.9799
+val Loss: 0.5529 Acc: 0.8725
+
+Epoch 8/24
+----------
+train Loss: 0.0489 Acc: 0.9806
+val Loss: 0.5540 Acc: 0.8728
+
+Epoch 9/24
+----------
+train Loss: 0.0479 Acc: 0.9810
+val Loss: 0.5818 Acc: 0.8717
+
+Epoch 10/24
+----------
+train Loss: 0.0465 Acc: 0.9815
+val Loss: 0.5819 Acc: 0.8727
+
+Epoch 11/24
+----------
+train Loss: 0.0452 Acc: 0.9821
+val Loss: 0.5765 Acc: 0.8732
+
+Epoch 12/24
+----------
+train Loss: 0.0456 Acc: 0.9819
+val Loss: 0.5957 Acc: 0.8725
+
+Epoch 13/24
+----------
+train Loss: 0.0449 Acc: 0.9823
+val Loss: 0.5857 Acc: 0.8724
+
+Epoch 14/24
+----------
+train Loss: 0.0438 Acc: 0.9827
+val Loss: 0.5943 Acc: 0.8723
+
+Epoch 15/24
+----------
+train Loss: 0.0442 Acc: 0.9823
+val Loss: 0.5874 Acc: 0.8730
+
+Epoch 16/24
+----------
+train Loss: 0.0443 Acc: 0.9824
+val Loss: 0.5950 Acc: 0.8720
+
+Epoch 17/24
+----------
+train Loss: 0.0437 Acc: 0.9828
+val Loss: 0.5945 Acc: 0.8729
+
+Epoch 18/24
+----------
+train Loss: 0.0434 Acc: 0.9828
+val Loss: 0.5975 Acc: 0.8725
+
+Epoch 19/24
+----------
+train Loss: 0.0435 Acc: 0.9827
+val Loss: 0.5900 Acc: 0.8730
+
+Epoch 20/24
+----------
+train Loss: 0.0432 Acc: 0.9828
+val Loss: 0.5922 Acc: 0.8730
+
+Epoch 21/24
+----------
+train Loss: 0.0426 Acc: 0.9832
+val Loss: 0.5977 Acc: 0.8720
+
+Epoch 22/24
+----------
+train Loss: 0.0426 Acc: 0.9832
+val Loss: 0.5974 Acc: 0.8726
+
+Epoch 23/24
+----------
+train Loss: 0.0435 Acc: 0.9828
+val Loss: 0.6019 Acc: 0.8718
+
+Epoch 24/24
+----------
+train Loss: 0.0432 Acc: 0.9828
+val Loss: 0.5996 Acc: 0.8718
+
+Training complete in 461m 14s
+Best val Acc: 0.873228
+```

mkdocs.yml

@@ -32,6 +32,7 @@ nav:
     - Home: index.md
     - 工程解析: './工程解析.md'
     - 数据集创建: './数据集创建.md'
+    - 微调模型: './微调模型.md'
     - '算法解析': './算法解析.md'
     - '数据集':
         - '创建': './create_data.md'