Kind regards.

I am running a model using variational Bayes. I am able to run the model using a subsample of the data of 10K observations, but when I try with the full dataset of 500K observations I get the following error

```
fit_1 <- stan_model$variational(data = stan_data, seed = 2552, algorithm="meanfield")
```

```
Gradient evaluation took 0.444722 seconds
1000 transitions using 10 leapfrog steps per transition would take 4447.22 seconds.
Adjust your expectations accordingly!
Begin eta adaptation.
Iteration: 1 / 250 [ 0%] (Adaptation)
Iteration: 50 / 250 [ 20%] (Adaptation)
Iteration: 100 / 250 [ 40%] (Adaptation)
Iteration: 150 / 250 [ 60%] (Adaptation)
Iteration: 200 / 250 [ 80%] (Adaptation)
Success! Found best value [eta = 1] earlier than expected.
Begin stochastic gradient ascent.
iter ELBO delta_ELBO_mean delta_ELBO_med notes
100 -3055253.022 1.000 1.000
200 -2470920.159 0.618 1.000
300 -1904450.061 0.511 0.297
400 -1800385.422 0.398 0.297
500 -1710310.475 0.329 0.236
600 -1636503.457 0.282 0.236
700 -1678077.168 0.245 0.058
800 -1677583.595 0.214 0.058
stan::variational::normal_meanfield::calc_grad: The number of dropped evaluations has reached its maximum amount (10). Your model may be either severely ill-conditioned or misspecified.
```

- Operating System: Linux
- CmdStan Version: 2.34.1
- Compiler/Toolkit: gcc (GCC) 13.2.1 20230801