Loss: MelReconLoss: enable: true params: {loss_type: mae} ProsodyReconLoss: enable: true params: {loss_type: mae} Model: KanTtsSAMBERT: optimizer: params: betas: [0.9, 0.98] eps: 1.0e-09 lr: 0.001 weight_decay: 0.0 type: Adam params: MAS: false NSF: true SE: true decoder_attention_dropout: 0.1 decoder_dropout: 0.1 decoder_ffn_inner_dim: 1024 decoder_num_heads: 8 decoder_num_layers: 12 decoder_num_units: 128 decoder_prenet_units: [256, 256] decoder_relu_dropout: 0.1 dur_pred_lstm_units: 128 dur_pred_prenet_units: [128, 128] embedding_dim: 512 emotion_units: 32 encoder_attention_dropout: 0.1 encoder_dropout: 0.1 encoder_ffn_inner_dim: 1024 encoder_num_heads: 8 encoder_num_layers: 8 encoder_num_units: 128 encoder_projection_units: 32 encoder_relu_dropout: 0.1 max_len: 800 nsf_f0_global_maximum: 730.0 nsf_f0_global_minimum: 30.0 nsf_norm_type: global num_mels: 82 outputs_per_step: 3 postnet_dropout: 0.1 postnet_ffn_inner_dim: 512 postnet_filter_size: 41 postnet_fsmn_num_layers: 4 postnet_lstm_units: 128 postnet_num_memory_units: 256 postnet_shift: 17 predictor_dropout: 0.1 predictor_ffn_inner_dim: 256 predictor_filter_size: 41 predictor_fsmn_num_layers: 3 predictor_lstm_units: 128 predictor_num_memory_units: 128 predictor_shift: 0 speaker_units: 192 scheduler: params: {warmup_steps: 4000} type: NoamLR allow_cache: false audio_config: {fmax: 8000.0, fmin: 0.0, hop_length: 200, max_norm: 1.0, min_level_db: -100.0, n_fft: 2048, n_mels: 80, norm_type: mean_std, num_workers: 16, phone_level_feature: true, preemphasize: false, ref_level_db: 20, sampling_rate: 16000, symmetric: false, trim_silence: true, trim_silence_threshold_db: 60, wav_normalize: true, win_length: 1000} batch_size: 32 create_time: '2023-08-29 02:39:37' eval_interval_steps: 10000000000000000 git_revision_hash: d16755444c9baf23348213211a5ed9035458ecf0 grad_norm: 1.0 linguistic_unit: {cleaners: english_cleaners, lfeat_type_list: 'sy,tone,syllable_flag,word_segment,emo_category,speaker_category', speaker_list: F7} log_interval: 10 log_interval_steps: 50 model_type: sambert modelscope_version: 1.8.4 num_save_intermediate_results: 4 num_workers: 4 pin_memory: false remove_short_samples: false save_interval_steps: 200 train_max_steps: 2400202 train_steps: 202