exp/streaming/modified_beam_search/log-decode-epoch-30-avg-9-streaming-chunk-size-32-use-averaged-model-2023-06-21-10-06-49

2023-06-21 10:06:49,545 INFO [streaming_decode.py:483] Decoding started
2023-06-21 10:06:49,546 INFO [streaming_decode.py:489] Device: cuda:0
2023-06-21 10:06:49,547 INFO [lexicon.py:168] Loading pre-compiled data/lang_phone/Linv.pt
2023-06-21 10:06:49,549 INFO [streaming_decode.py:497] {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 0, 'log_interval': 50, 'reset_interval': 200, 'valid_interval': 3000, 'feature_dim': 80, 'subsampling_factor': 4, 'warm_step': 2000, 'env_info': {'k2-version': '1.23.4', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': '9426c9f730820d291f5dcb06be337662595fa7b4', 'k2-git-date': 'Sun Feb 5 17:35:01 2023', 'lhotse-version': '1.15.0.dev+git.00d3e36.clean', 'torch-version': '1.13.1+cu117', 'torch-cuda-available': True, 'torch-cuda-version': '11.7', 'python-version': '3.1', 'icefall-git-branch': 'master', 'icefall-git-sha1': 'd3f5d01-dirty', 'icefall-git-date': 'Wed May 31 04:15:45 2023', 'icefall-path': '/root/icefall', 'k2-path': '/usr/local/lib/python3.10/dist-packages/k2/__init__.py', 'lhotse-path': '/root/lhotse/lhotse/__init__.py', 'hostname': 'bookbot-k2', 'IP address': '127.0.0.1'}, 'epoch': 30, 'iter': 0, 'avg': 9, 'use_averaged_model': True, 'exp_dir': PosixPath('pruned_transducer_stateless7_streaming/exp'), 'lang_dir': 'data/lang_phone', 'decoding_method': 'modified_beam_search', 'num_active_paths': 4, 'beam': 4, 'max_contexts': 4, 'max_states': 32, 'context_size': 2, 'num_decode_streams': 1500, 'num_encoder_layers': '2,4,3,2,4', 'feedforward_dims': '1024,1024,2048,2048,1024', 'nhead': '8,8,8,8,8', 'encoder_dims': '384,384,384,384,384', 'attention_dims': '192,192,192,192,192', 'encoder_unmasked_dims': '256,256,256,256,256', 'zipformer_downsampling_factors': '1,2,4,8,2', 'cnn_module_kernels': '31,31,31,31,31', 'decoder_dim': 512, 'joiner_dim': 512, 'short_chunk_size': 50, 'num_left_chunks': 4, 'decode_chunk_len': 32, 'manifest_dir': PosixPath('data/fbank'), 'max_duration': 200.0, 'bucketing_sampler': True, 'num_buckets': 30, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'drop_last': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'input_strategy': 'PrecomputedFeatures', 'res_dir': PosixPath('pruned_transducer_stateless7_streaming/exp/streaming/modified_beam_search'), 'suffix': 'epoch-30-avg-9-streaming-chunk-size-32-use-averaged-model', 'blank_id': 0, 'unk_id': 7, 'vocab_size': 33}
2023-06-21 10:06:49,550 INFO [streaming_decode.py:499] About to create model
2023-06-21 10:06:50,126 INFO [zipformer.py:405] At encoder stack 4, which has downsampling_factor=2, we will combine the outputs of layers 1 and 3, with downsampling_factors=2 and 8.
2023-06-21 10:06:50,130 INFO [streaming_decode.py:566] Calculating the averaged model over epoch range from 21 (excluded) to 30
2023-06-21 10:06:53,715 INFO [streaming_decode.py:588] Number of model parameters: 69471350
2023-06-21 10:06:53,715 INFO [multidataset.py:122] About to get LibriVox test cuts
2023-06-21 10:06:53,715 INFO [multidataset.py:124] Loading LibriVox in lazy mode
2023-06-21 10:06:53,716 INFO [multidataset.py:133] About to get FLEURS test cuts
2023-06-21 10:06:53,716 INFO [multidataset.py:135] Loading FLEURS in lazy mode
2023-06-21 10:06:53,717 INFO [multidataset.py:144] About to get Common Voice test cuts
2023-06-21 10:06:53,717 INFO [multidataset.py:146] Loading Common Voice in lazy mode
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2023-06-21 10:07:19,334 INFO [streaming_decode.py:425] The transcripts are stored in pruned_transducer_stateless7_streaming/exp/streaming/modified_beam_search/recogs-test-librivox-epoch-30-avg-9-streaming-chunk-size-32-use-averaged-model.txt
2023-06-21 10:07:19,369 INFO [utils.py:561] [test-librivox-num_active_paths_4] %WER 4.78% [1748 / 36594, 298 ins, 852 del, 598 sub ]
2023-06-21 10:07:19,449 INFO [streaming_decode.py:436] Wrote detailed error stats to pruned_transducer_stateless7_streaming/exp/streaming/modified_beam_search/errs-test-librivox-epoch-30-avg-9-streaming-chunk-size-32-use-averaged-model.txt
2023-06-21 10:07:19,449 INFO [streaming_decode.py:450] 
For test-librivox, WER of different settings are:
num_active_paths_4	4.78	best for test-librivox

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2023-06-21 10:08:32,133 INFO [streaming_decode.py:425] The transcripts are stored in pruned_transducer_stateless7_streaming/exp/streaming/modified_beam_search/recogs-test-fleurs-epoch-30-avg-9-streaming-chunk-size-32-use-averaged-model.txt
2023-06-21 10:08:32,229 INFO [utils.py:561] [test-fleurs-num_active_paths_4] %WER 11.83% [11074 / 93580, 1827 ins, 4283 del, 4964 sub ]
2023-06-21 10:08:32,533 INFO [streaming_decode.py:436] Wrote detailed error stats to pruned_transducer_stateless7_streaming/exp/streaming/modified_beam_search/errs-test-fleurs-epoch-30-avg-9-streaming-chunk-size-32-use-averaged-model.txt
2023-06-21 10:08:32,533 INFO [streaming_decode.py:450] 
For test-fleurs, WER of different settings are:
num_active_paths_4	11.83	best for test-fleurs

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2023-06-21 10:10:52,211 INFO [streaming_decode.py:425] The transcripts are stored in pruned_transducer_stateless7_streaming/exp/streaming/modified_beam_search/recogs-test-commonvoice-epoch-30-avg-9-streaming-chunk-size-32-use-averaged-model.txt
2023-06-21 10:10:52,342 INFO [utils.py:561] [test-commonvoice-num_active_paths_4] %WER 14.54% [19305 / 132787, 3354 ins, 7699 del, 8252 sub ]
2023-06-21 10:10:52,643 INFO [streaming_decode.py:436] Wrote detailed error stats to pruned_transducer_stateless7_streaming/exp/streaming/modified_beam_search/errs-test-commonvoice-epoch-30-avg-9-streaming-chunk-size-32-use-averaged-model.txt
2023-06-21 10:10:52,643 INFO [streaming_decode.py:450] 
For test-commonvoice, WER of different settings are:
num_active_paths_4	14.54	best for test-commonvoice

2023-06-21 10:10:52,643 INFO [streaming_decode.py:618] Done!