The ML Training Progress Plotter draws a line chart from your training loss and validation loss numbers. Paste each series as comma-separated values, in epoch order. Click one button and the chart draws both lines together, with Epoch on the bottom axis and Loss on the side axis. Use this ML Training Progress Plotter to see if a model is still learning or starting to overfit.
How to use the ML Training Progress Plotter
- Paste your training numbers into the box labelled “Training Loss Data (comma-separated):”. Put one value per epoch, separated by commas.
- Paste your validation numbers into the box labelled “Validation Loss Data (comma-separated):”. This box is optional, but if you use it, it must hold the same count of values as the training box.
- Keep both lists in time order. The first value is epoch 1, the second is epoch 2, and so on.
- Click “Plot Training Progress”.
- Read the chart. The teal line is Training Loss and the pink line is Validation Loss, under the title “Training Progress”.
Change the values and click the button again to plot new numbers. A fresh chart replaces the old one.
Worked example
Use the example data shown on the tool itself. Training Loss Data: 0.5, 0.4, 0.3, 0.2, 0.15, 0.1, 0.08, 0.06. Validation Loss Data: 0.6, 0.5, 0.4, 0.3, 0.25, 0.2, 0.18, 0.15.
Both lists hold 8 values, so the chart shows epochs 1 to 8 at the bottom and Loss, starting at 0, on the side. Two smooth lines fall from left to right. The teal training line drops from 0.5 to 0.06. The pink validation line drops from 0.6 to 0.15 and stays above the training line the whole way. Both lines still fall at the end, so this run shows a model that is still improving, with no clear turn up that would signal overfitting.
Example results
| Input | What the chart shows |
|---|---|
| Training: 0.9, 0.7, 0.55. Validation: empty | One teal Training Loss line over epochs 1 to 3, falling |
| Training: 0.5, 0.4, 0.3. Validation: 0.6, 0.55, 0.52 | Two lines over 3 epochs. The pink validation line sits above the teal line |
| Training: 0.5, 0.4, 0.3, 0.2. Validation: 0.6, 0.5, 0.4 | No chart. An alert says the validation data length must match the training data length |
| Training: 0.5, abc, 0.3 | A chart with 2 points, 0.5 and 0.3. The word abc is skipped without a warning |
| Training: 1, 0.8, 0.85, 0.9 | One line that falls, then rises for two epochs. Loss is getting worse at the end |
Limits and good to know
- Training data is required. Validation data is optional, but its count must match the training count exactly, or no chart is drawn.
- Words and other non-numbers are removed without a warning. That changes the count of values and can shift points to the wrong epoch.
- Axis names are fixed: Epoch at the bottom and Loss on the side. The chart title is fixed as Training Progress, and the two line colours cannot be changed.
- The Loss axis always starts at 0. Small changes in large loss values can look flat.
- There is no save or download button for the chart. Take a screenshot if you need a copy.
- Numbers are plotted in the order you paste them. They are not sorted or checked.
Why is my result empty or wrong?
You see the alert “Please enter valid training data”. The training box is empty, or it holds no numbers at all. Paste comma-separated numbers into the training box first.
You see the alert about matching lengths. The two lists hold a different count of values. Count them again. One hidden cause: a word or stray text in a list is deleted by the tool, leaving it one value short.
A point is missing and the epochs look shifted. One value was not a clean number, such as 0..5, and it was skipped. Fix the typo so every value is a plain number, then plot again.
Your old chart vanished and no new chart came. The tool clears the old chart before it checks the lengths. Fix the count mismatch and click the button again to draw a fresh chart.
Why use this ML Training Progress Plotter?
It turns raw loss numbers from a training log into a clear picture in seconds, with no notebook, spreadsheet or code to open. Pasting the two series side by side makes the gap between training and validation loss easy to see. It is free, works in your browser, and asks for nothing but the numbers.
ML Training Progress Plotter – frequently asked questions
Is validation loss data required?
No. Validation data is optional and the chart draws with the training line alone. If you add validation values, their count must match the training count exactly.
What happens if the two lists have different lengths?
The tool shows an alert saying the validation data length must match the training data length, and it draws no chart. Add or remove values so both lists match.
Can I plot accuracy or other values instead of loss?
You can paste any per-epoch numbers and the tool will plot them in order. The axis and line labels still say Loss, so the chart works best for loss values.
Are my numbers uploaded anywhere?
No. Your values are read and plotted inside your browser with the Chart.js library loaded on the page. Nothing is sent to a server.
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