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name: "Gorani-Persian_1"
data:
train: "datasets/Gorani-Persian/1/train"
dev: "datasets/Gorani-Persian/1/dev"
test: "datasets/Gorani-Persian/1/test"
level: "char"
lowercase: False
normalize: False
max_sent_length: 100
dataset_type: "plain"
src:
lang: "src"
voc_limit: 100
voc_min_freq: 5
level: "char"
trg:
lang: "trg"
voc_limit: 100
voc_min_freq: 5
level: "char"
training:
random_seed: 42
optimizer: "adam"
learning_rate: 0.001
learning_rate_min: 0.0002
weight_decay: 0.0
clip_grad_norm: 1.0
batch_size: 64
scheduling: "plateau"
patience: 10
decrease_factor: 0.5
early_stopping_metric: "loss"
epochs: 80
validation_freq: 1000
logging_freq: 100
eval_metric: "bleu"
model_dir: "models/Gorani-Persian"
overwrite: True
shuffle: True
use_cuda: True
max_output_length: 100
print_valid_sents: [0, 3, 6, 9]
keep_best_ckpts: -1
testing:
n_best: 1
beam_size: 4
beam_alpha: 1.0
eval_metrics: ["bleu", "chrf", "sequence_accuracy"]
max_output_length: 1000
batch_size: 10
batch_type: "sentence"
return_prob: "none"
model:
initializer: "xavier_uniform"
init_gain: 1.0
bias_initializer: "zeros"
embed_initializer: "xavier_uniform"
embed_init_gain: 1.0
encoder:
type: "transformer"
num_layers: 6
num_heads: 8
embeddings:
embedding_dim: 128
scale: True
# typically ff_size = 4 x hidden_size
hidden_size: 128
ff_size: 512
dropout: 0.2
layer_norm: "pre"
decoder:
type: "transformer"
num_layers: 6
num_heads: 8
embeddings:
embedding_dim: 128
scale: True
# typically ff_size = 4 x hidden_size
hidden_size: 128
ff_size: 512
dropout: 0.2
layer_norm: "pre" |