Epoch-based training in PyTorch - Model Pipeline Trace

Model Pipeline - Epoch-based training

This pipeline shows how a simple model learns step-by-step by repeating passes over the data called epochs. Each epoch helps the model improve by adjusting itself to make better predictions.

Data Flow - 5 Stages

1Data Loading

1000 rows x 10 columns→Load raw data with 10 features per example→1000 rows x 10 columns

[[0.5, 1.2, ..., 0.3], [1.1, 0.7, ..., 0.9], ...]

↓

2Preprocessing

1000 rows x 10 columns→Normalize features to range 0-1→1000 rows x 10 columns

[[0.05, 0.12, ..., 0.03], [0.11, 0.07, ..., 0.09], ...]

↓

3Train/Test Split

1000 rows x 10 columns→Split data into 800 training and 200 testing rows→Train: 800 rows x 10 columns, Test: 200 rows x 10 columns

Train example: [0.05, 0.12, ..., 0.03], Test example: [0.09, 0.15, ..., 0.07]

↓

4Model Training

800 rows x 10 columns→Feed data into model for learning→Model weights updated

Weights start random, updated each epoch

↓

5Evaluation

200 rows x 10 columns→Model predicts on test data→200 predictions

[0, 1, 0, 0, 1, ...]

Training Trace - Epoch by Epoch

Loss
0.7 | *
0.6 | *
0.5 |  *
0.4 |   *
0.3 |    *
0.2 |
    +------------
     1 2 3 4 5 Epochs

Epoch	Loss ↓	Accuracy ↑	Observation
1	0.65	0.60	Model starts learning with moderate loss and accuracy
2	0.50	0.72	Loss decreases and accuracy improves as model adjusts
3	0.40	0.80	Model continues to learn, loss drops further
4	0.32	0.85	Good progress, model is more accurate
5	0.28	0.88	Loss stabilizes, accuracy nearing high level

Prediction Trace - 4 Layers

Layer 1: Input Layer

Layer 2: Hidden Layer (ReLU activation)

Layer 3: Output Layer (Sigmoid activation)

Layer 4: Prediction Threshold

Model Quiz - 3 Questions

What happens to the loss value as epochs increase?

A It increases steadily

B It stays the same

C It decreases steadily

D It randomly jumps up and down

Key Insight

Epoch-based training helps the model learn gradually by repeatedly adjusting its parameters. Watching loss decrease and accuracy increase over epochs shows the model is improving its predictions.