better score

This commit is contained in:
Michal Maciaszek 2020-12-08 20:50:35 +01:00
parent bb5d311df5
commit de3f755d2b
5 changed files with 892 additions and 893 deletions

View File

@ -1,462 +1,462 @@
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BIN
model.pkl

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@ -20,6 +20,7 @@ def dataframe_to_arrays(dataframe):
dataframe1["type"] = dataframe1["type"].astype('category').cat.codes
return dataframe1
#PREDICT_FILE_PATH = 'dev-0/in.tsv'
PREDICT_FILE_PATH = 'test-A/in.tsv'
def main():

View File

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View File

@ -2,10 +2,8 @@ import torch
import torch.nn as nn
import numpy as np
import pandas as pd
import sys
import torch.nn.functional as F
import pickle
from torch.utils.data import TensorDataset, DataLoader
TRAIN_FILE_PATH = 'train/train.tsv'
@ -15,7 +13,7 @@ def read_data_file(filepath):
df = pd.read_csv(filepath, sep='\t', header=None, index_col=None)
dataframe = df.iloc[:, [0,8,11]]
dataframe.columns = ['price','biggy','type']
#print(dataframe.size[0])
for x in range(len(dataframe)):
dataframe['biggy'].loc[x] = dataframe['biggy'].loc[x].replace(" ","")
#such dumb solution, well, but at least it works
@ -42,17 +40,17 @@ inputs_array_training, targets_array_training = dataframe_to_arrays(data)
inputs_training = torch.from_numpy(inputs_array_training).type(torch.float32)
targets_training = torch.from_numpy(targets_array_training).type(torch.float32)
print(inputs_training)
w = torch.tensor([7201.61492633873, 1,7201.500], requires_grad=True)
learning_rate = torch.tensor(0.000000000005)
weights = torch.tensor([1.0, 1.0,300000.0], requires_grad=True)
learning_rate = torch.tensor(0.00000000001)
print("training started")
for i in range(10000):
y_predicted = inputs_training @ w
for i in range(20000):
y_predicted = inputs_training @ weights
cost = torch.sum((y_predicted - targets_training) ** 2)
cost.backward()
with torch.no_grad():
w -= learning_rate * w.grad
w.requires_grad = True
weights -= learning_rate * weights.grad
weights.requires_grad = True
print(w)
pickle.dump(w, open('model.pkl', 'wb'))
print(weights)
pickle.dump(weights, open('model.pkl', 'wb'))