diff --git a/training_interface.html b/training_interface.html
index 2d76e2c..e086d2f 100644
--- a/training_interface.html
+++ b/training_interface.html
@@ -520,15 +520,15 @@
                     <div class="form-row">
                         <div class="form-group" id="nEstimatorsGroup">
                             <label>N Estimators:</label>
-                            <input type="number" id="nEstimators" value="100" min="10" max="1000" required>
+                            <input type="number" id="nEstimators" value="400" min="10" max="1000" required>
                         </div>
                         <div class="form-group">
                             <label>Max Depth:</label>
-                            <input type="number" id="maxDepth" value="20" min="1" max="50" required>
+                            <input type="number" id="maxDepth" value="12" min="1" max="50" required>
                         </div>
                         <div class="form-group" id="learningRateGroup">
                             <label>Learning Rate:</label>
-                            <input type="number" step="0.0001" id="learningRate" value="0.1" min="0.0001" max="1" required>
+                            <input type="number" step="0.0001" id="learningRate" value="0.05" min="0.0001" max="1" required>
                         </div>
                         <div class="form-group" id="testSizeGroup">
                             <label>Tỷ lệ dữ liệu test (0-1):</label>
@@ -1411,42 +1411,52 @@
                 nEstimatorsGroup.style.display = '';
                 learningRateGroup.style.display = '';
                 useGpuGroup.style.display = '';
+                document.querySelector('#nEstimatorsGroup label').textContent = 'N Estimators:';
+                document.getElementById('nEstimators').value = 400;
+                document.getElementById('maxDepth').value = 12;
+                document.querySelector('#learningRateGroup label').textContent = 'Learning Rate:';
+                document.getElementById('learningRate').value = 0.05;
             } else if (modelType === 'random_forest') {
                 nEstimatorsGroup.style.display = '';
                 learningRateGroup.style.display = 'none';
                 useGpuGroup.style.display = 'none';
+                document.querySelector('#nEstimatorsGroup label').textContent = 'Trees:';
+                document.getElementById('nEstimators').value = 300;
+                document.getElementById('maxDepth').value = 18;
             } else if (modelType === 'decision_tree') {
                 nEstimatorsGroup.style.display = 'none';
                 learningRateGroup.style.display = 'none';
                 useGpuGroup.style.display = 'none';
+                document.getElementById('maxDepth').value = 12;
             } else if (modelType === 'svm') {
                 nEstimatorsGroup.style.display = 'none';
                 learningRateGroup.style.display = 'none';
                 useGpuGroup.style.display = 'none';
+                document.getElementById('maxDepth').value = 12;
             } else if (modelType === 'cnn') {
                 // CNN uses n_estimators as epochs and supports GPU
                 nEstimatorsGroup.style.display = '';
                 document.querySelector('#nEstimatorsGroup label').textContent = 'Epochs (số lần training):';
-                document.getElementById('nEstimators').value = 50;
+                document.getElementById('nEstimators').value = 30;
                 learningRateGroup.style.display = 'none';
                 useGpuGroup.style.display = '';  // Show GPU option for CNN
             } else if (modelType === 'swin-unet') {
                 // Swin-UNet uses n_estimators as epochs and supports GPU
                 nEstimatorsGroup.style.display = '';
                 document.querySelector('#nEstimatorsGroup label').textContent = 'Epochs (số lần training):';
-                document.getElementById('nEstimators').value = 100;
+                document.getElementById('nEstimators').value = 80;
                 learningRateGroup.style.display = '';  // Show learning rate for Swin-UNet
-                document.querySelector('#learningRateGroup label').textContent = 'Learning Rate (mặc định: 0.0005):';
-                document.getElementById('learningRate').value = 0.0005;
+                document.querySelector('#learningRateGroup label').textContent = 'Learning Rate (mặc định: 0.0003):';
+                document.getElementById('learningRate').value = 0.0003;
                 useGpuGroup.style.display = '';  // Show GPU option for Swin-UNet
             } else if (modelType === 'mobilenet-lraspp') {
                 // MobileNetV3 + LR-ASPP uses n_estimators as epochs and supports GPU
                 nEstimatorsGroup.style.display = '';
                 document.querySelector('#nEstimatorsGroup label').textContent = 'Epochs (số lần training):';
-                document.getElementById('nEstimators').value = 60;
+                document.getElementById('nEstimators').value = 50;
                 learningRateGroup.style.display = '';  // Show learning rate for MobileNet
-                document.querySelector('#learningRateGroup label').textContent = 'Learning Rate (mặc định: 0.001):';
-                document.getElementById('learningRate').value = 0.001;
+                document.querySelector('#learningRateGroup label').textContent = 'Learning Rate (mặc định: 0.0008):';
+                document.getElementById('learningRate').value = 0.0008;
                 useGpuGroup.style.display = '';  // Show GPU option for MobileNet
             }