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name: "enaf_transformer"
data:
src: "en"
trg: "af"
train: "data/enaf/train.bpe"
dev: "data/enaf/dev.bpe"
test: "data/enaf/test.bpe"
level: "bpe"
lowercase: False
max_sent_length: 100
src_vocab: "data/enaf/vocab.txt"
trg_vocab: "data/enaf/vocab.txt"
testing:
beam_size: 5
alpha: 1.0
training:
#load_model: "/content/drive/My Drive/masakhane/en-af-baseline/models/enaf_transformer/1.ckpt" # if uncommented, load a pre-trained model from this checkpoint
#load_model: "/content/drive/My Drive/masakhane/en-af-baseline/joeynmt/models/enaf_transformer/3500.ckpt" # if uncommented, load a pre-trained model from this checkpoint
random_seed: 42
optimizer: "adam"
normalization: "tokens"
adam_betas: [0.9, 0.999]
scheduling: "noam" # Try switching to Elan scheduling
learning_rate_decay_length: 5000 # number of steps to reduce by the decay factor for Elan method
learning_rate_peak: 0.002 # peak for Elan scheduler (default: 1)
learning_rate_warmup: 2000 # warmup steps for Elan scheduler
learning_rate_factor: 1 # factor for Noam scheduler (used with Transformer)
learning_rate_warmup: 1000 # warmup steps for Noam scheduler (used with Transformer)
patience: 8
decrease_factor: 0.7
loss: "crossentropy"
learning_rate: 0.0002
learning_rate_min: 0.00000001
weight_decay: 0.0
label_smoothing: 0.1
batch_size: 4096
batch_type: "token"
eval_batch_size: 3600
eval_batch_type: "token"
batch_multiplier: 1
early_stopping_metric: "ppl"
epochs: 30 # TODO: Decrease for when playing around and checking of working. Around 30 is sufficient to check if its working at all
validation_freq: 500 # 4000 # Decrease this for testing
logging_freq: 100
eval_metric: "bleu"
model_dir: "models/enaf_transformer"
overwrite: True
shuffle: True
use_cuda: True
max_output_length: 100
print_valid_sents: [0, 1, 2, 3]
keep_last_ckpts: 3
model:
initializer: "xavier"
bias_initializer: "zeros"
init_gain: 1.0
embed_initializer: "xavier"
embed_init_gain: 1.0
tied_embeddings: True
tied_softmax: True
encoder:
type: "transformer"
num_layers: 3
num_heads: 8
embeddings:
embedding_dim: 512
scale: True
dropout: 0.
# typically ff_size = 4 x hidden_size
hidden_size: 512
ff_size: 2048
dropout: 0.3
decoder:
type: "transformer"
num_layers: 3
num_heads: 8
embeddings:
embedding_dim: 512
scale: True
dropout: 0.
# typically ff_size = 4 x hidden_size
hidden_size: 512
ff_size: 2048
dropout: 0.25
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