diff --git a/VAE_model/models.py b/VAE_model/models.py
index 3adf218cd9bf2f2b3b6ecc715c4f0a747b2fbd0e..bc1f71ab3593a059c14ef4ed578d6be9f6d7ba43 100644
--- a/VAE_model/models.py
+++ b/VAE_model/models.py
@@ -40,8 +40,8 @@ class VAE(nn.Module):
         self.stride = stride
         self.num_pixels = img_size[1] * img_size[2]
         self.temperature = temperature
-        self.hidden_dim = 256  # Hidden dimension of linear layer
-        self.reshape = (256, 1, 1)  # Shape required to start transpose convs
+        self.hidden_dim = nb_filter_conv4*4  # Hidden dimension of linear layer
+        self.reshape = (self.hidden_dim, 1, 1)  # Shape required to start transpose convs
 
         # Calculate dimensions of latent distribution
         self.latent_cont_dim = 0
diff --git a/parameters_combinations/param_combinations_chairs_test.txt b/parameters_combinations/param_combinations_chairs_test.txt
index 39e45ce2fdf3508838fc0096d1176b0d7c69db55..3e0b6a78269c14c316f9469e2fb4f0748db5caca 100644
--- a/parameters_combinations/param_combinations_chairs_test.txt
+++ b/parameters_combinations/param_combinations_chairs_test.txt
@@ -1,4 +1,4 @@
---batch-size=64 --dataset=rendered_chairs --epochs=400 --latent_spec_cont=10 --lr=1e-4 --experiment-name=VAE_bs_64_conv_64_64_128_128 --gpu-devices 0 1 --nb-filter-conv1_64 --nb-filter-conv2=64 --nb-filter-conv3=128 --nb-filter-conv4=128
---batch-size=64 --dataset=rendered_chairs --epochs=400 --latent_spec_cont=10 --lr=1e-4 --experiment-name=VAE_bs_64_conv_128_128_256_256 --gpu-devices 0 1 --nb-filter-conv1_128 --nb-filter-conv2=128 --nb-filter-conv3=256 --nb-filter-conv4=256
---batch-size=64 --dataset=rendered_chairs --epochs=400 --latent_spec_cont=30 --lr=1e-4 --experiment-name=VAE_bs_64_conv_64_64_128_128_ls_30 --gpu-devices 0 1 --nb-filter-conv1_64 --nb-filter-conv2=64 --nb-filter-conv3=128 --nb-filter-conv4=128
---batch-size=64 --dataset=rendered_chairs --epochs=400 --latent_spec_cont=30 --lr=1e-4 --experiment-name=VAE_bs_64_conv_128_128_256_256_ls_30 --gpu-devices 0 1 --nb-filter-conv1_128 --nb-filter-conv2=128 --nb-filter-conv3=256 --nb-filter-conv4=256
+--batch-size=64 --dataset=rendered_chairs --epochs=4 --latent_spec_cont=10 --lr=1e-4 --experiment-name=VAE_bs_64_conv_64_64_128_128 --gpu-devices 0 1 --nb-filter-conv1=64 --nb-filter-conv2=64 --nb-filter-conv3=128 --nb-filter-conv4=128
+--batch-size=64 --dataset=rendered_chairs --epochs=400 --latent_spec_cont=10 --lr=1e-4 --experiment-name=VAE_bs_64_conv_128_128_256_256 --gpu-devices 0 1 --nb-filter-conv1=128 --nb-filter-conv2=128 --nb-filter-conv3=256 --nb-filter-conv4=256
+--batch-size=64 --dataset=rendered_chairs --epochs=400 --latent_spec_cont=30 --lr=1e-4 --experiment-name=VAE_bs_64_conv_64_64_128_128_ls_30 --gpu-devices 0 1 --nb-filter-conv1=64 --nb-filter-conv2=64 --nb-filter-conv3=128 --nb-filter-conv4=128
+--batch-size=64 --dataset=rendered_chairs --epochs=400 --latent_spec_cont=30 --lr=1e-4 --experiment-name=VAE_bs_64_conv_128_128_256_256_ls_30 --gpu-devices 0 1 --nb-filter-conv1=128 --nb-filter-conv2=128 --nb-filter-conv3=256 --nb-filter-conv4=256