It is pretty clear that your model is overfitting as your validation error is way higher than your training error.
This also means that more data allows your model to overfit less. If you are to have 20k examples I'm betting that your validation error will be slightly lower and your training error will be slightly higher.
However, I also see a plateau in your validation error, meaning that it is not likely to decrease a lot. If you want to decrease your validation error significantly, consider:
- Using a model that overfits less - either a different algorithm or set your parameters to a lower bias configuration.
- Using new features/information.
- Get more data, but again this is unlikely to diminish the validation error significanlty.