diff --git a/train.py b/train.py
index 762ee1d..b5085c2 100644
--- a/train.py
+++ b/train.py
@@ -23,21 +23,25 @@
 
 from model.model import TimeSeriesTransformer as TSTF
 
-# data parameters
-SPLIT = [0.9, 0.05, 0.05]
-
-# model parameters
-HEAD_SIZE = 32
-NUM_HEADS = 12
-FF_DIM = 32
-NUM_TRANSFORMER_BLOCKS = 12
-MLP_UNITS = [128]
-DROPOUT = 0.3
-MLP_DROPOUT = 0.3
-
-# training parameters
-BATCH_SIZE = 8
-EPOCHS = 800
+with open("parameters.json", "r") as file:
+    params = json.load(file)
+
+    # data parameters
+    SPLIT = params["split"]
+
+    # model parameters
+    HEAD_SIZE = params["head_size"]
+    NUM_HEADS = params["num_heads"]
+    FF_DIM = params["ff_dim"]
+    NUM_TRANSFORMER_BLOCKS = params["num_transformer_blocks"]
+    MLP_UNITS = params["mlp_units"]
+    DROPOUT = params["dropout"]
+    MLP_DROPOUT = params["mlp_dropout"]
+
+    # training parameters
+    BATCH_SIZE = params["batch_size"]
+    EPOCHS = params["epochs"]
+    del params
 
 def trim(dataframe, column):
 
diff --git a/train_cpu.py b/train_cpu.py
index d0d5ec9..de18b67 100644
--- a/train_cpu.py
+++ b/train_cpu.py
@@ -12,6 +12,7 @@
 #os.environ["XLA_PYTHON_CLIENT_PREALLOCATE"] = "false"
 
 import jax
+import json
 import numpy as np
 from pipe.pipe import SpectrogramPipe
 from pyspark.ml.feature import StringIndexer, IndexToString
@@ -24,21 +25,25 @@
 from model.autoencoder_smol import Autoencoder
 from model.model import TimeSeriesTransformer as TSTF
 
-# data parameters
-SPLIT = [0.9, 0.05, 0.05]
-
-# model parameters
-HEAD_SIZE = 32
-NUM_HEADS = 12
-FF_DIM = 32
-NUM_TRANSFORMER_BLOCKS = 12
-MLP_UNITS = [128]
-DROPOUT = 0.3
-MLP_DROPOUT = 0.3
-
-# training parameters
-BATCH_SIZE = 8
-EPOCHS = 800
+with open("parameters.json", "r") as file:
+    params = json.load(file)
+
+    # data parameters
+    SPLIT = params["split"]
+
+    # model parameters
+    HEAD_SIZE = params["head_size"]
+    NUM_HEADS = params["num_heads"]
+    FF_DIM = params["ff_dim"]
+    NUM_TRANSFORMER_BLOCKS = params["num_transformer_blocks"]
+    MLP_UNITS = params["mlp_units"]
+    DROPOUT = params["dropout"]
+    MLP_DROPOUT = params["mlp_dropout"]
+
+    # training parameters
+    BATCH_SIZE = params["batch_size"]
+    EPOCHS = params["epochs"]
+    del params
 
 def trim(dataframe, column):