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| # ################################ | |
| # Model: wav2vec2 + DNN + CTC | |
| # Augmentation: SpecAugment | |
| # Authors: Sung-Lin Yeh 2021 | |
| # ################################ | |
| # Seed needs to be set at top of yaml, before objects with parameters are made | |
| seed: 1986 | |
| __set_seed: !apply:torch.manual_seed [!ref <seed>] | |
| output_folder: partly_frozen_splitted_wavlm/1986/ | |
| wer_file: !ref <output_folder>/wer.txt | |
| save_folder: !ref <output_folder>/save | |
| train_log: !ref <output_folder>/train_log.txt | |
| # URL for the biggest Fairseq english wav2vec2 model. | |
| # Data files | |
| data_folder: /gpfsscratch/rech/nou/uzn19yk/Libri/LibriSpeech/ # e,g./path/to/LibriSpeech | |
| # noise/ris dataset will automatically be downloaded | |
| data_folder_rirs: !ref <data_folder> | |
| train_splits: ["train-clean-100"] | |
| dev_splits: ["dev-clean"] | |
| test_splits: ["test-clean", "test-other"] | |
| skip_prep: False | |
| ckpt_interval_minutes: 25 # save checkpoint every N min | |
| csv_folder: /gpfsstore/rech/nou/uzn19yk/iwslt/splitted_clean_tunisian_csvs/ | |
| train_csv: test_salah_local.csv | |
| valid_csv: test_salah_local.csv | |
| test_csv: | |
| - test_salah_local.csv | |
| # Training parameters | |
| number_of_epochs: 12 | |
| lr: 1 | |
| lr_wav2vec: 0.0001 | |
| sorting: ascending | |
| auto_mix_prec: False | |
| sample_rate: 16000 | |
| avoid_if_longer_than: 10 | |
| # With data_parallel batch_size is split into N jobs | |
| # With DDP batch_size is multiplied by N jobs | |
| # Must be 3 per GPU to fit 32GB of VRAM | |
| batch_size: 1 | |
| test_batch_size: 1 | |
| # Dataloader options | |
| train_dataloader_opts: | |
| batch_size: !ref <batch_size> | |
| valid_dataloader_opts: | |
| batch_size: !ref <batch_size> | |
| test_dataloader_opts: | |
| batch_size: !ref <test_batch_size> | |
| # Model parameters | |
| activation: !name:torch.nn.LeakyReLU | |
| dnn_layers: 2 | |
| dnn_neurons: 1024 | |
| freeze_wav2vec: False | |
| # Outputs | |
| output_neurons: 41 # BPE size, index(blank/eos/bos) = 0 | |
| # Decoding parameters | |
| blank_index: 0 | |
| bos_index: 1 | |
| eos_index: 2 | |
| # | |
| # Functions and classes | |
| # | |
| epoch_counter: !new:speechbrain.utils.epoch_loop.EpochCounter | |
| limit: !ref <number_of_epochs> | |
| augmentation: !new:speechbrain.lobes.augment.TimeDomainSpecAugment | |
| sample_rate: !ref <sample_rate> | |
| speeds: [95, 100, 105] | |
| enc: !new:speechbrain.lobes.models.VanillaNN.VanillaNN | |
| input_shape: [null, null, 1024] | |
| activation: !ref <activation> | |
| dnn_blocks: !ref <dnn_layers> | |
| dnn_neurons: !ref <dnn_neurons> | |
| wav2vec2: !new:speechbrain.lobes.models.huggingface_wav2vec.HuggingFaceWav2Vec2 | |
| source: microsoft/wavlm-large | |
| output_norm: True | |
| freeze: False | |
| freeze_feature_extractor: True | |
| save_path: !ref <save_folder>/wav2vec2_hubert_checkpoint | |
| ##### | |
| # Uncomment this block if you prefer to use a Fairseq pretrained model instead | |
| # of a HuggingFace one. Here, we provide an URL that is obtained from the | |
| # Fairseq github for the multilingual XLSR. | |
| # | |
| #wav2vec2_url: https://dl.fbaipublicfiles.com/fairseq/wav2vec/wav2vec_vox_960h_pl.pt | |
| #wav2vec2: !new:speechbrain.lobes.models.fairseq_wav2vec.FairseqWav2Vec2 | |
| # pretrained_path: !ref <wav2vec2_url> | |
| # output_norm: True | |
| # freeze: False | |
| # save_path: !ref <save_folder>/wav2vec2_checkpoint/model.pt | |
| ctc_lin: !new:speechbrain.nnet.linear.Linear | |
| input_size: !ref <dnn_neurons> | |
| n_neurons: !ref <output_neurons> | |
| log_softmax: !new:speechbrain.nnet.activations.Softmax | |
| apply_log: True | |
| ctc_cost: !name:speechbrain.nnet.losses.ctc_loss | |
| blank_index: !ref <blank_index> | |
| modules: | |
| wav2vec2: !ref <wav2vec2> | |
| enc: !ref <enc> | |
| ctc_lin: !ref <ctc_lin> | |
| model: !new:torch.nn.ModuleList | |
| - [!ref <enc>, !ref <ctc_lin>] | |
| model_opt_class: !name:torch.optim.Adadelta | |
| lr: !ref <lr> | |
| rho: 0.95 | |
| eps: 1.e-8 | |
| wav2vec_opt_class: !name:torch.optim.Adam | |
| lr: !ref <lr_wav2vec> | |
| lr_annealing_model: !new:speechbrain.nnet.schedulers.NewBobScheduler | |
| initial_value: !ref <lr> | |
| improvement_threshold: 0.0025 | |
| annealing_factor: 0.8 | |
| patient: 0 | |
| lr_annealing_wav2vec: !new:speechbrain.nnet.schedulers.NewBobScheduler | |
| initial_value: !ref <lr_wav2vec> | |
| improvement_threshold: 0.0025 | |
| annealing_factor: 0.9 | |
| patient: 0 | |
| checkpointer: !new:speechbrain.utils.checkpoints.Checkpointer | |
| checkpoints_dir: !ref <save_folder> | |
| recoverables: | |
| wav2vec2: !ref <wav2vec2> | |
| model: !ref <model> | |
| scheduler_model: !ref <lr_annealing_model> | |
| scheduler_wav2vec: !ref <lr_annealing_wav2vec> | |
| counter: !ref <epoch_counter> | |
| train_logger: !new:speechbrain.utils.train_logger.FileTrainLogger | |
| save_file: !ref <train_log> | |
| error_rate_computer: !name:speechbrain.utils.metric_stats.ErrorRateStats | |
| cer_computer: !name:speechbrain.utils.metric_stats.ErrorRateStats | |
| split_tokens: True | |