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Upload config.yaml

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+
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+ name: "data_sp"
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+ joeynmt_version: "2.0.0"
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+
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+ data:
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+ train: "RESULTS_azb2fa/data/train"
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+ dev: "RESULTS_azb2fa/data/validation"
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+ test: "RESULTS_azb2fa/data/test"
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+ dataset_type: "huggingface"
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+ sample_dev_subset: 200
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+ src:
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+ lang: "azb"
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+ max_length: 100
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+ lowercase: False
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+ normalize: False
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+ level: "bpe"
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+ voc_limit: 2000
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+ voc_min_freq: 1
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+ voc_file: "RESULTS_azb2fa/data/vocab.txt"
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+ tokenizer_type: "sentencepiece"
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+ tokenizer_cfg:
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+ model_file: "RESULTS_azb2fa/data/sp.model"
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+
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+ trg:
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+ lang: "fa"
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+ max_length: 100
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+ lowercase: False
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+ normalize: False
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+ level: "bpe"
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+ voc_limit: 2000
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+ voc_min_freq: 1
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+ voc_file: "RESULTS_azb2fa/data/vocab.txt"
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+ tokenizer_type: "sentencepiece"
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+ tokenizer_cfg:
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+ model_file: "RESULTS_azb2fa/data/sp.model"
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+
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+
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+ testing:
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+ n_best: 1
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+ beam_size: 5
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+ beam_alpha: 1.0
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+ batch_size: 512
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+ batch_type: "token"
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+ max_output_length: 100
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+ eval_metrics: ["bleu"]
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+ #return_prob: "hyp"
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+ #return_attention: False
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+ sacrebleu_cfg:
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+ tokenize: "13a"
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+
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+ training:
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+ #load_model: "RESULTS_azb2fa/model/latest.ckpt"
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+ #reset_best_ckpt: False
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+ #reset_scheduler: False
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+ #reset_optimizer: False
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+ #reset_iter_state: False
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+ random_seed: 42
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+ optimizer: "adam"
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+ normalization: "tokens"
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+ adam_betas: [0.9, 0.999]
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+ scheduling: "warmupinversesquareroot"
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+ learning_rate_warmup: 2000
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+ learning_rate: 0.0002
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+ learning_rate_min: 0.00000001
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+ weight_decay: 0.0
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+ label_smoothing: 0.1
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+ loss: "crossentropy"
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+ batch_size: 512
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+ batch_type: "token"
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+ batch_multiplier: 4
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+ early_stopping_metric: "bleu"
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+ epochs: 500
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+ updates: 2000000000
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+ validation_freq: 1000
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+ logging_freq: 100
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+ model_dir: "RESULTS_azb2fa/model"
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+ overwrite: True
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+ shuffle: True
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+ use_cuda: True
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+ print_valid_sents: [0, 1, 2, 3]
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+ keep_best_ckpts: 3
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+
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+ model:
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+ initializer: "xavier"
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+ bias_initializer: "zeros"
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+ init_gain: 1.0
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+ embed_initializer: "xavier"
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+ embed_init_gain: 1.0
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+ tied_embeddings: True
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+ tied_softmax: True
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+ encoder:
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+ type: "transformer"
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+ num_layers: 2
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+ num_heads: 4
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+ embeddings:
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+ embedding_dim: 256
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+ scale: True
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+ dropout: 0.2
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+ # typically ff_size = 4 x hidden_size
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+ hidden_size: 256
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+ ff_size: 1024
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+ dropout: 0.1
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+ layer_norm: "pre"
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+ decoder:
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+ type: "transformer"
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+ num_layers: 2
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+ num_heads: 8
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+ embeddings:
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+ embedding_dim: 256
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+ scale: True
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+ dropout: 0.2
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+ # typically ff_size = 4 x hidden_size
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+ hidden_size: 256
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+ ff_size: 1024
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+ dropout: 0.1
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+ layer_norm: "pre"
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+