"""Exact training call used for this model. Run from inside this directory:
    python train.py
Retrains model.bin from train.txt in place (dim=128/epoch=25 -- the winner of a capacity
sweep against dim=64/epoch=10 and dim=256/epoch=25; dim256 added nothing further, see
README.md)."""
import fasttext

HPARAMS = dict(dim=128, epoch=25, lr=0.3, wordNgrams=2, minCount=3, bucket=2_000_000)

model = fasttext.train_supervised(input="train.txt", **HPARAMS)
model.save_model("model.bin")
print("saved model.bin")