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semsankken/
xauusd_forex_lstm

Name: xauusd_forex_lstm
Availability: InStock

pytorch

ForexLSTM

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XAUUSD-H1 Forex LSTM Model

Fine-tuned LSTM for predicting next hourly Close price on XAUUSD (gold) data from 2008-2025.

Dataset: Hourly OHLCV from "XAUUSD_H1.csv" (~150k rows)
Input: Sequences of 60 timesteps with Open, High, Low, Close, Volume, SMA_20
Task: Regression (next Close price)
Training: 100 epochs, Adam optimizer, MSE loss
Evaluation: Test MSE ~ 0.9100
Usage: Load with PyTorch, use scaler for inverse transform.

Inference Example

python

import torch
import json
import joblib
import numpy as np

class ForexLSTM(torch.nn.Module):
    # ... (copy class definition)

model = ForexLSTM()
model.load_state_dict(torch.load("pytorch_model.bin"))
scaler = joblib.load("scaler.pkl")
# Prepare input sequence and predict as above

semsankken/xauusd_forex_lstm

XAUUSD-H1 Forex LSTM Model

Inference Example

semsankken/
xauusd_forex_lstm