# data location and config section
data:
  train_data_location: laos-vn/Train/train2023
  eval_data_location:  laos-vn/Dev/dev2023
  src_lang: .lo
  trg_lang: .vi
log_file_models: 'model.log'
lowercase: false
build_vocab_kwargs: # additional arguments for build_vocab. See torchtext.vocab.Vocab for mode details
#  max_size: 50000
  min_freq: 5
# model parameters section
device: cuda
d_model: 512
n_layers: 6
heads: 8
# inference section
eval_batch_size: 8
decode_strategy: BeamSearch
decode_strategy_kwargs:
  beam_size: 4 # beam search size
  length_normalize: 0.6 # recalculate beam position by length. Currently only work in default BeamSearch
  replace_unk: # tuple of layer/head attention to replace unknown words
    - 0 # layer
    - 0 # head
input_max_length: 200 # input longer than this value will be trimmed in inference. Note that this values are to be used during cached PE, hence, validation set with more than this much tokens will call a warning for the trimming.
max_length: 160 # only perform up to this much timestep during inference
train_max_length: 50 # training samples with this much length in src/trg will be discarded
# optimizer and learning arguments section
lr: 0.4
optimizer: Adam
optimizer_params:
  betas:
    - 0.9 # beta1
    - 0.98 # beta2
  eps: !!float 1e-9
n_warmup_steps: 8000
label_smoothing: 0.1
dropout: 0.1
# training config, evaluation, save & load section
batch_size: 64
epochs: 20
printevery: 200
save_checkpoint_epochs: 1
maximum_saved_model_eval: 5
maximum_saved_model_train: 5