| # config.yaml | |
| ## Where the samples will be written | |
| save_data: run | |
| # Training files | |
| data: | |
| corpus_1: | |
| path_src: tr-os.tr-filtered.tr.subword.train | |
| path_tgt: tr-os.os-filtered.os.subword.train | |
| transforms: [filtertoolong] | |
| valid: | |
| path_src: tr-os.tr-filtered.tr.subword.dev | |
| path_tgt: tr-os.os-filtered.os.subword.dev | |
| transforms: [filtertoolong] | |
| # Vocabulary files, generated by onmt_build_vocab | |
| src_vocab: run/source.vocab | |
| tgt_vocab: run/target.vocab | |
| # Vocabulary size - should be the same as in sentence piece | |
| src_vocab_size: 50000 | |
| tgt_vocab_size: 50000 | |
| # Filter out source/target longer than n if [filtertoolong] enabled | |
| src_seq_length: 150 | |
| src_seq_length: 150 | |
| # Tokenization options | |
| src_subword_model: source.model | |
| tgt_subword_model: target.model | |
| # Where to save the log file and the output models/checkpoints | |
| log_file: train.log | |
| save_model: models/model.tros | |
| # Stop training if it does not imporve after n validations | |
| early_stopping: 4 | |
| # Default: 5000 - Save a model checkpoint for each n | |
| save_checkpoint_steps: 1500 | |
| # To save space, limit checkpoints to last n | |
| # keep_checkpoint: 6 | |
| seed: 3435 | |
| # Default: 100000 - Train the model to max n steps | |
| # Increase to 200000 or more for large datasets | |
| # For fine-tuning, add up the required steps to the original steps | |
| train_steps: 100000 | |
| # Default: 10000 - Run validation after n steps | |
| valid_steps: 10000 | |
| # Default: 4000 - for large datasets, try up to 8000 | |
| warmup_steps: 4000 | |
| report_every: 100 | |
| # Number of GPUs, and IDs of GPUs | |
| world_size: 1 | |
| gpu_ranks: [0] | |
| # Batching | |
| bucket_size: 262144 | |
| num_workers: 2 # Default: 2, set to 0 when RAM out of memory | |
| batch_type: "tokens" | |
| batch_size: 4096 # Tokens per batch, change when CUDA out of memory | |
| valid_batch_size: 2048 | |
| max_generator_batches: 2 | |
| accum_count: [4] | |
| accum_steps: [0] | |
| # Optimization | |
| model_dtype: "fp16" | |
| optim: "adam" | |
| learning_rate: 2 | |
| warmup_steps: 8000 | |
| decay_method: "noam" | |
| adam_beta2: 0.998 | |
| max_grad_norm: 0 | |
| label_smoothing: 0.1 | |
| param_init: 0 | |
| param_init_glorot: true | |
| normalization: "tokens" | |
| # Model | |
| encoder_type: transformer | |
| decoder_type: transformer | |
| position_encoding: true | |
| enc_layers: 6 | |
| dec_layers: 6 | |
| heads: 8 | |
| hidden_size: 512 | |
| word_vec_size: 512 | |
| transformer_ff: 2048 | |
| dropout_steps: [0] | |
| dropout: [0.1] | |
| attention_dropout: [0.1] | |