pytorch/examples

example time_sequence_prediction does not produce expected output

Open

#247 opened on Oct 27, 2017

View on GitHub
 (5 comments) (1 reaction) (0 assignees)Python (9,429 forks)batch import
good first issue

Repository metrics

Stars
 (21,634 stars)
PR merge metrics
 (No merged PRs in 30d)

Description

https://github.com/pytorch/examples/tree/master/time_sequence_prediction

After a few steps, the loss suddenly jumps up and stays high: loss: 0.00101216329969 loss: 0.195070432582

the pdf0 is OK, pdf1 is OK but from pdf2 the graph becomes an "L "

Contributor guide

Research direction
Investigate the training loop in the time sequence prediction example (https://github.com/pytorch/examples/tree/master/time sequence prediction). The issue describes a sudden loss increase after a few steps and an 'L' shaped graph from pdf2 onward. Check for exploding gradients, learning rate issues, or incorrect sequence batching. Compare with well known implementations of LSTM for time series to identify potential bugs.
Tech stack
pytorchpython
Domain
machine learningai
Issue type
Bug
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
4
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
Half day
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
Stale
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Mostly clear
Prerequisites
PythonPyTorchRNN/LSTMTime series prediction
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
30