dathudeptrai
commited on
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Parent(s):
44a8cd7
π€ Update config, processor and checkpoint for Tacotron2 KSS Korean.
Browse files- config.yml +87 -0
- model.h5 +3 -0
- processor.json +1 -0
config.yml
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# This is the hyperparameter configuration file for Tacotron2 v1.
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# Please make sure this is adjusted for the KSS dataset. If you want to
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# apply to the other dataset, you might need to carefully change some parameters.
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# This configuration performs 200k iters but 65k iters is enough to get a good models.
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###########################################################
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# FEATURE EXTRACTION SETTING #
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###########################################################
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hop_size: 256 # Hop size.
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format: "npy"
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###########################################################
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# NETWORK ARCHITECTURE SETTING #
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###########################################################
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model_type: "tacotron2"
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tacotron2_params:
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dataset: "kss"
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embedding_hidden_size: 512
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initializer_range: 0.02
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embedding_dropout_prob: 0.1
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n_speakers: 1
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n_conv_encoder: 5
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encoder_conv_filters: 512
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encoder_conv_kernel_sizes: 5
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encoder_conv_activation: 'relu'
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encoder_conv_dropout_rate: 0.5
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encoder_lstm_units: 256
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n_prenet_layers: 2
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prenet_units: 256
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prenet_activation: 'relu'
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prenet_dropout_rate: 0.5
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n_lstm_decoder: 1
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reduction_factor: 1
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decoder_lstm_units: 1024
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attention_dim: 128
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attention_filters: 32
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attention_kernel: 31
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n_mels: 80
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n_conv_postnet: 5
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postnet_conv_filters: 512
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postnet_conv_kernel_sizes: 5
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postnet_dropout_rate: 0.1
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attention_type: "lsa"
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###########################################################
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# DATA LOADER SETTING #
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###########################################################
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batch_size: 32 # Batch size for each GPU with assuming that gradient_accumulation_steps == 1.
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remove_short_samples: true # Whether to remove samples the length of which are less than batch_max_steps.
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allow_cache: true # Whether to allow cache in dataset. If true, it requires cpu memory.
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mel_length_threshold: 32 # remove all targets has mel_length <= 32
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is_shuffle: true # shuffle dataset after each epoch.
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use_fixed_shapes: true # use_fixed_shapes for training (2x speed-up)
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# refer (https://github.com/dathudeptrai/TensorflowTTS/issues/34#issuecomment-642309118)
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###########################################################
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# OPTIMIZER & SCHEDULER SETTING #
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###########################################################
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optimizer_params:
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initial_learning_rate: 0.001
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end_learning_rate: 0.00001
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decay_steps: 150000 # < train_max_steps is recommend.
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warmup_proportion: 0.02
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weight_decay: 0.001
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gradient_accumulation_steps: 1
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var_train_expr: null # trainable variable expr (eg. 'embeddings|decoder_cell' )
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# must separate by |. if var_train_expr is null then we
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# training all variable
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###########################################################
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# INTERVAL SETTING #
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###########################################################
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train_max_steps: 200000 # Number of training steps.
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save_interval_steps: 2000 # Interval steps to save checkpoint.
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eval_interval_steps: 500 # Interval steps to evaluate the network.
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log_interval_steps: 200 # Interval steps to record the training log.
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start_schedule_teacher_forcing: 200001 # don't need to apply schedule teacher forcing.
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start_ratio_value: 0.5 # start ratio of scheduled teacher forcing.
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schedule_decay_steps: 50000 # decay step scheduled teacher forcing.
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end_ratio_value: 0.0 # end ratio of scheduled teacher forcing.
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###########################################################
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# OTHER SETTING #
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###########################################################
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num_save_intermediate_results: 1 # Number of results to be saved as intermediate results.
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model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:2dd15872b504b05d4af015cdfe506beede54537a05c7cc723a5d5554c0ded6d2
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size 127830576
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processor.json
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{"symbol_to_id": {"pad": 0, "-": 7, "!": 2, "'": 3, "(": 4, ")": 5, ",": 6, ".": 8, ":": 9, ";": 10, "?": 11, " ": 12, "\u1100": 13, "\u1101": 14, "\u1102": 15, "\u1103": 16, "\u1104": 17, "\u1105": 18, "\u1106": 19, "\u1107": 20, "\u1108": 21, "\u1109": 22, "\u110a": 23, "\u110b": 24, "\u110c": 25, "\u110d": 26, "\u110e": 27, "\u110f": 28, "\u1110": 29, "\u1111": 30, "\u1112": 31, "\u1161": 32, "\u1162": 33, "\u1163": 34, "\u1164": 35, "\u1165": 36, "\u1166": 37, "\u1167": 38, "\u1168": 39, "\u1169": 40, "\u116a": 41, "\u116b": 42, "\u116c": 43, "\u116d": 44, "\u116e": 45, "\u116f": 46, "\u1170": 47, "\u1171": 48, "\u1172": 49, "\u1173": 50, "\u1174": 51, "\u1175": 52, "\u11a8": 53, "\u11a9": 54, "\u11aa": 55, "\u11ab": 56, "\u11ac": 57, "\u11ad": 58, "\u11ae": 59, "\u11af": 60, "\u11b0": 61, "\u11b1": 62, "\u11b2": 63, "\u11b3": 64, "\u11b4": 65, "\u11b5": 66, "\u11b6": 67, "\u11b7": 68, "\u11b8": 69, "\u11b9": 70, "\u11ba": 71, "\u11bb": 72, "\u11bc": 73, "\u11bd": 74, "\u11be": 75, "\u11bf": 76, "\u11c0": 77, "\u11c1": 78, "\u11c2": 79, "eos": 80}, "id_to_symbol": {"0": "pad", "1": "-", "2": "!", "3": "'", "4": "(", "5": ")", "6": ",", "7": "-", "8": ".", "9": ":", "10": ";", "11": "?", "12": " ", "13": "\u1100", "14": "\u1101", "15": "\u1102", "16": "\u1103", "17": "\u1104", "18": "\u1105", "19": "\u1106", "20": "\u1107", "21": "\u1108", "22": "\u1109", "23": "\u110a", "24": "\u110b", "25": "\u110c", "26": "\u110d", "27": "\u110e", "28": "\u110f", "29": "\u1110", "30": "\u1111", "31": "\u1112", "32": "\u1161", "33": "\u1162", "34": "\u1163", "35": "\u1164", "36": "\u1165", "37": "\u1166", "38": "\u1167", "39": "\u1168", "40": "\u1169", "41": "\u116a", "42": "\u116b", "43": "\u116c", "44": "\u116d", "45": "\u116e", "46": "\u116f", "47": "\u1170", "48": "\u1171", "49": "\u1172", "50": "\u1173", "51": "\u1174", "52": "\u1175", "53": "\u11a8", "54": "\u11a9", "55": "\u11aa", "56": "\u11ab", "57": "\u11ac", "58": "\u11ad", "59": "\u11ae", "60": "\u11af", "61": "\u11b0", "62": "\u11b1", "63": "\u11b2", "64": "\u11b3", "65": "\u11b4", "66": "\u11b5", "67": "\u11b6", "68": "\u11b7", "69": "\u11b8", "70": "\u11b9", "71": "\u11ba", "72": "\u11bb", "73": "\u11bc", "74": "\u11bd", "75": "\u11be", "76": "\u11bf", "77": "\u11c0", "78": "\u11c1", "79": "\u11c2", "80": "eos"}, "speakers_map": {"kss": 0}, "processor_name": "KSSProcessor"}
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