Text Classification Example Project
Here’s a public example project to give you a taste of neptune.ai’s API and the app.
It’s a text classification project that shows how to use Neptune for NLP tasks. It also surfaces the Neptune+Optuna integration for hyperparameter optimization sweep tracking.
You can just open the project and play with the app, no registration is needed. And if you want to see the code behind it, go to the example’s GitHub repo.
What’s in this NLP text classification example project?
Here are a few most important things you can see in the project:
- Runs table and comparison charts – when you open the project, you will land in the Runs table view.
You can easily change the columns that are visible in the runs table or filter the runs.
- In the Compare runs tab, you can switch from Charts comparison to Images comparison or Side-by-side comparison. If you’ve logged artifacts, you can also compare datasets between runs.
In the side-by-side comparison, check the boxes “Rows with diffs only” and “Show cell changes”. This way, analyzing results is much easier.
By the way, you can choose which runs you want to compare by clicking the eye icon in the runs table.
- You can also inspect a single run. Click the Runs details tab at the top of your screen, and you’ll land in the single run’s view. Just below the name of the run, you can see different dashboards.
The first one is the All metadata dashboard with everything that was logged to Neptune (organized in a folder-like structure). Then, there are Charts, Images, Monitoring, Source code, and more.
- At the end of the list, you can see some custom dashboards that combine different metadata types in one place.
- This example showcases Neptune’s model registry functionality as well. In the Models tab, you can see registered models and their versions.
- Finally, take a look at the Project metadata tab. You’ll find there all the metadata that was logged at the project instead of the run level.
Other useful resources
Explore other example projects, e.g. tabular data example project or time series forecasting example project.
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