I know that a laptop GPU with 2GB of RAM is not suitable for this purpose, but I wonder two settings -n_sample and batch_size from quick start.
When I leave -n_sample 10000, it does not start training at all because of CUDA memory error. I tried very small batch_size like 4 and it worked afterwards.
When I don’t touch batch_size in yaml config but decrease -n_sample to 1000 it also works too. But does it mean the system only knows the words from first 1000 sentences and makes up a translation from these words only?
And my last question about real word usage, should a source / target corpus pair contain at least 100M sentences? Is this a minimum for a reasonable translate ? What is the minimum system requirements for this corpus, train_steps and estimated time for these steps etc.
I need to propose a budget roughly. So having x graphic card, with y million of parallel sentences will do the job in z weeks/months training time type of recommendations will be very helpful in my case.
Thank you in advance.