Config hyperparameters for enhanced training

[KristinaUlicna]

PR contribution summary

Why is this PR useful / good for? Please describe the problem(s) you're trying to address.

• Includes weight decay + learning rate scheduler options
• Pretty-prints the epoch logging for easier legibility

List of proposed changes / linked issues & discussions

• ✅ Resolves [FEATURE REQUEST] Implement enhanced training hparams #146
• ✅ Resolves Customise the logger to print epochs into new lines #271

What should a reviewer concentrate their feedback on?

• 🏃 Test multiple runs with different config params (esp. scheduler)
• 💻 Code quality

What type of PR is this? (check all applicable)

• 🪄 Feature
• #️⃣ Documentation / code annotation
• 🧑‍💻 Code refactor / style
• 🔥 Performance Improvements

Added tests?

• 🙅 no, because they aren't needed

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PR review summary

Describe what this PR does & how you reviewed the individual items, where needed:

Some helper checks to tick off:

• Focus on image annotation
• Focus on model training
• Could any optimization be applied?
• Is there any redundant code?
• Are there any spelling errors?

In conclusion, after my review, I'd like to:

• 🙋 ask some clarifying questions
• 🙅 suggest some specific changes

[crangelsmith]

LGTM