I need some help with my segmentation model

username: lightersss
cooked: <p><div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/8/d/8d47fcf442a8cf80cb401b0c278f573e4f6f6d2b.jpeg" data-download-href="https://discuss.pytorch.org/uploads/default/8d47fcf442a8cf80cb401b0c278f573e4f6f6d2b" title="1"><img src="https://discuss.pytorch.org/uploads/default/optimized/3X/8/d/8d47fcf442a8cf80cb401b0c278f573e4f6f6d2b_2_520x500.jpeg" alt="1" data-base62-sha1="k9PyxBRFVnQLpk2eriMMY7GUfAT" width="520" height="500" srcset="https://discuss.pytorch.org/uploads/default/optimized/3X/8/d/8d47fcf442a8cf80cb401b0c278f573e4f6f6d2b_2_520x500.jpeg, https://discuss.pytorch.org/uploads/default/optimized/3X/8/d/8d47fcf442a8cf80cb401b0c278f573e4f6f6d2b_2_780x750.jpeg 1.5x, https://discuss.pytorch.org/uploads/default/original/3X/8/d/8d47fcf442a8cf80cb401b0c278f573e4f6f6d2b.jpeg 2x" data-dominant-color="141414"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">1</span><span class="informations">999×960 93.3 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div> <div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/1/c/1c411f2e6859c5bc3d3374fcc231ec5e592e3fb7.jpeg" data-download-href="https://discuss.pytorch.org/uploads/default/1c411f2e6859c5bc3d3374fcc231ec5e592e3fb7" title="Image_01L"><img src="https://discuss.pytorch.org/uploads/default/optimized/3X/1/c/1c411f2e6859c5bc3d3374fcc231ec5e592e3fb7_2_520x500.jpeg" alt="Image_01L" data-base62-sha1="41WTiO6hmuQUGx8beBmxEIpeXrx" width="520" height="500" srcset="https://discuss.pytorch.org/uploads/default/optimized/3X/1/c/1c411f2e6859c5bc3d3374fcc231ec5e592e3fb7_2_520x500.jpeg, https://discuss.pytorch.org/uploads/default/optimized/3X/1/c/1c411f2e6859c5bc3d3374fcc231ec5e592e3fb7_2_780x750.jpeg 1.5x, https://discuss.pytorch.org/uploads/default/original/3X/1/c/1c411f2e6859c5bc3d3374fcc231ec5e592e3fb7.jpeg 2x" data-dominant-color="742F0A"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">Image_01L</span><span class="informations">999×960 64.2 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div> <div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/a/5/a5ea743554c9a29518b972a8d053599f6a51d3e0.png" data-download-href="https://discuss.pytorch.org/uploads/default/a5ea743554c9a29518b972a8d053599f6a51d3e0" title="Image_01L_2ndHO"><img src="https://discuss.pytorch.org/uploads/default/original/3X/a/5/a5ea743554c9a29518b972a8d053599f6a51d3e0.png" alt="Image_01L_2ndHO" data-base62-sha1="nFL64dsxv6WedcQ6QXlL2s101yg" width="520" height="500" data-dominant-color="141414"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">Image_01L_2ndHO</span><span class="informations">999×960 11.9 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div><br>
this is the mask, segmentation result and the input image<br>
Is that overfitting or something else?my dice coefficient  was stable at 0.9685 for about 7 epoches.</p>
<p>my model is consists of two Unet which I think is not complicated.The conv block looks just like this</p>
<pre><code class="lang-auto">class BasicResBlock(nn.Module):
    def __init__(self, in_channels, out_channels):
        super(BasicResBlock, self).__init__()
        self.double_conv = nn.Sequential(
            nn.Conv2d(in_channels, out_channels, kernel_size=3, padding=1),
            nn.BatchNorm2d(out_channels),
            nn.ReLU(),
            nn.Conv2d(out_channels, out_channels, kernel_size=3, padding=1),
            nn.BatchNorm2d(out_channels)
        )
        self.cov1x1 = nn.Sequential(  # 调节通道数
            nn.Conv2d(in_channels, out_channels, kernel_size=1, padding=0),
            nn.BatchNorm2d(out_channels),
            nn.ReLU())

    def forward(self, x):
        res = self.cov1x1(x)
        x = self.double_conv(x)
        return F.relu(res + x)
</code></pre>
<p>My model output 2 results,coarse and refine, and I set the loss like this</p>
<pre><code class="lang-auto">coarse_mask, refine= net(imgs)
                loss1 = criterion1(coarse_mask, true_masks)
                loss2 = criterion1(refine, true_masks)
                loss =0.8*loss1 +loss2
</code></pre>
<p>I really need some advice!!!Thank you!!!</p>