# train.yaml

## Where the samples will be written
save_data: dp2022/run2/example
## Where the vocab(s) will be written
src_vocab: dp2022/run2/example.vocab.src
tgt_vocab: dp2022/run2/example.vocab.tgt
# Prevent overwriting existing files in the folder
overwrite: False


# Corpus opts
data:
        corpus_1:
                path_src: dp2022/europarl-v7.sk-en.en
                path_tgt: dp2022/europarl-v7.sk-en.sk
        valid:
                path_src: dp2022/europarl-v7.clean.sk-en.en
                path_tgt: dp2022/europarl-v7.clean.sk-en.sk

# Vocabulary files that were just created
src_vocab: dp2022/run2/example.vocab.src
tgt_vocab: dp2022/run2/example.vocab.tgt

# Train on a single GPU
world_size: 1
gpu_ranks: [0]

# Where to save the checkpoints
save_model: dp2022/run2/model
save_checkpoint_steps: 1000
train_steps: 20000
valid_steps: 10000