upload pretrained model

README.md

@@ -1,3 +1,84 @@
 ---
 license: apache-2.0
+datasets:
+- tedlium3
+language:
+- en
+metrics:
+- wer
 ---
+### TedLium3 Zipformer
+
+Using the codes from this PR https://github.com/k2-fsa/icefall/pull/1125.
+
+The WERs are
+
+|                                    |     dev    |    test    | comment                                  |
+|------------------------------------|------------|------------|------------------------------------------|
+|          greedy search             | 6.74       | 6.16       | --epoch 50, --avg 22, --max-duration 500 |
+|      beam search (beam size 4)     | 6.56       | 5.95       | --epoch 50, --avg 22, --max-duration 500 |
+| modified beam search (beam size 4) | 6.54       | 6.00       | --epoch 50, --avg 22, --max-duration 500 |
+| fast beam search (set as default)  | 6.91       | 6.28       | --epoch 50, --avg 22, --max-duration 500 |
+
+The training command for reproducing is given below:
+
+```
+export CUDA_VISIBLE_DEVICES="0,1,2,3"
+
+./zipformer/train.py \
+  --use-fp16 true \
+  --world-size 4 \
+  --num-epochs 50 \
+  --start-epoch 0 \
+  --exp-dir zipformer/exp \
+  --max-duration 1000
+```
+
+The tensorboard training log can be found at
+https://tensorboard.dev/experiment/AKXbJha0S9aXyfmuvG4h5A/#scalars
+
+The decoding command is:
+```
+epoch=50
+avg=22
+
+## greedy search
+./zipformer/decode.py \
+  --epoch $epoch \
+  --avg $avg \
+  --exp-dir zipformer/exp \
+  --bpe-model ./data/lang_bpe_500/bpe.model \
+  --max-duration 500
+
+## beam search
+./zipformer/decode.py \
+  --epoch $epoch \
+  --avg $avg \
+  --exp-dir zipformer/exp \
+  --bpe-model ./data/lang_bpe_500/bpe.model \
+  --max-duration 500 \
+  --decoding-method beam_search \
+  --beam-size 4
+
+## modified beam search
+./zipformer/decode.py \
+  --epoch $epoch \
+  --avg $avg \
+  --exp-dir zipformer/exp \
+  --bpe-model ./data/lang_bpe_500/bpe.model \
+  --max-duration 500 \
+  --decoding-method modified_beam_search \
+  --beam-size 4
+
+## fast beam search
+./zipformer/decode.py \
+  --epoch $epoch \
+  --avg $avg \
+  --exp-dir ./zipformer/exp \
+  --bpe-model ./data/lang_bpe_500/bpe.model \
+  --max-duration 1500 \
+  --decoding-method fast_beam_search \
+  --beam 4 \
+  --max-contexts 4 \
+  --max-states 8
+```

data/lang_bpe_500/bpe.model

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f950ca4200a0611ae3a2b2cb561f34ed7f39ae554512dce54134c55aa29d7188
+size 244890

decoding_results/beam_search/log-decode-epoch-50-avg-22-beam_search-beam-size-4-use-averaged-model-2023-06-15-16-05-54

@@ -0,0 +1,26 @@
+2023-06-15 16:05:54,523 INFO [decode.py:675] Decoding started
+2023-06-15 16:05:54,524 INFO [decode.py:681] Device: cuda:0
+2023-06-15 16:05:54,531 INFO [decode.py:691] {'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': '1.24.3', 'k2-build-type': 'Debug', 'k2-with-cuda': True, 'k2-git-sha1': '38211604d6a24b15f320578a1a38f6c12d7a711c', 'k2-git-date': 'Mon Jun 12 10:59:44 2023', 'lhotse-version': '1.15.0.dev+git.f1fd23d.clean', 'torch-version': '2.0.0+cu117', 'torch-cuda-available': True, 'torch-cuda-version': '11.7', 'python-version': '3.8', 'icefall-git-branch': 'ted/zipformer', 'icefall-git-sha1': '323a299-dirty', 'icefall-git-date': 'Tue Jun 13 04:47:15 2023', 'icefall-path': '/exp/draj/jsalt2023/icefall', 'k2-path': '/exp/draj/jsalt2023/k2/k2/python/k2/__init__.py', 'lhotse-path': '/exp/draj/jsalt2023/lhotse/lhotse/__init__.py', 'hostname': 'r2n02', 'IP address': '10.1.2.2'}, 'epoch': 50, 'iter': 0, 'avg': 22, 'use_averaged_model': True, 'exp_dir': PosixPath('zipformer/exp/v5'), 'bpe_model': 'data/lang_bpe_500/bpe.model', 'lang_dir': PosixPath('data/lang_bpe_500'), 'decoding_method': 'beam_search', 'beam_size': 4, 'beam': 20.0, 'ngram_lm_scale': 0.01, 'max_contexts': 8, 'max_states': 64, 'context_size': 2, 'max_sym_per_frame': 1, 'num_paths': 200, 'nbest_scale': 0.5, 'num_encoder_layers': '2,2,3,4,3,2', 'downsampling_factor': '1,2,4,8,4,2', 'feedforward_dim': '512,768,1024,1536,1024,768', 'num_heads': '4,4,4,8,4,4', 'encoder_dim': '192,256,384,512,384,256', 'query_head_dim': '32', 'value_head_dim': '12', 'pos_head_dim': '4', 'pos_dim': 48, 'encoder_unmasked_dim': '192,192,256,256,256,192', 'cnn_module_kernel': '31,31,15,15,15,31', 'decoder_dim': 512, 'joiner_dim': 512, 'causal': False, 'chunk_size': '16,32,64,-1', 'left_context_frames': '64,128,256,-1', 'manifest_dir': PosixPath('data/manifests'), 'max_duration': 500, 'bucketing_sampler': True, 'num_buckets': 30, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'res_dir': PosixPath('zipformer/exp/v5/beam_search'), 'suffix': 'epoch-50-avg-22-beam_search-beam-size-4-use-averaged-model', 'blank_id': 0, 'unk_id': 2, 'vocab_size': 500}
+2023-06-15 16:05:54,532 INFO [decode.py:693] About to create model
+2023-06-15 16:05:55,243 INFO [decode.py:760] Calculating the averaged model over epoch range from 28 (excluded) to 50
+2023-06-15 16:05:59,616 INFO [decode.py:794] Number of model parameters: 65549011
+2023-06-15 16:05:59,617 INFO [asr_datamodule.py:361] About to get dev cuts
+2023-06-15 16:05:59,620 INFO [asr_datamodule.py:366] About to get test cuts
+2023-06-15 16:07:14,020 INFO [decode.py:572] batch 0/?, cuts processed until now is 30
+2023-06-15 16:21:11,947 INFO [decode.py:588] The transcripts are stored in zipformer/exp/v5/beam_search/recogs-dev-beam_size_4-epoch-50-avg-22-beam_search-beam-size-4-use-averaged-model.txt
+2023-06-15 16:21:11,979 INFO [utils.py:562] [dev-beam_size_4] %WER 6.56% [1195 / 18226, 187 ins, 400 del, 608 sub ]
+2023-06-15 16:21:12,046 INFO [decode.py:601] Wrote detailed error stats to zipformer/exp/v5/beam_search/errs-dev-beam_size_4-epoch-50-avg-22-beam_search-beam-size-4-use-averaged-model.txt
+2023-06-15 16:21:12,047 INFO [decode.py:617] 
+For dev, WER of different settings are:
+beam_size_4	6.56	best for dev
+
+2023-06-15 16:22:30,203 INFO [decode.py:572] batch 0/?, cuts processed until now is 40
+2023-06-15 16:42:42,018 INFO [decode.py:572] batch 20/?, cuts processed until now is 1063
+2023-06-15 16:46:02,358 INFO [decode.py:588] The transcripts are stored in zipformer/exp/v5/beam_search/recogs-test-beam_size_4-epoch-50-avg-22-beam_search-beam-size-4-use-averaged-model.txt
+2023-06-15 16:46:02,413 INFO [utils.py:562] [test-beam_size_4] %WER 5.95% [1693 / 28430, 212 ins, 683 del, 798 sub ]
+2023-06-15 16:46:02,509 INFO [decode.py:601] Wrote detailed error stats to zipformer/exp/v5/beam_search/errs-test-beam_size_4-epoch-50-avg-22-beam_search-beam-size-4-use-averaged-model.txt
+2023-06-15 16:46:02,511 INFO [decode.py:617] 
+For test, WER of different settings are:
+beam_size_4	5.95	best for test
+
+2023-06-15 16:46:02,511 INFO [decode.py:825] Done!

decoding_results/beam_search/wer-summary-dev-beam_size_4-epoch-50-avg-22-beam_search-beam-size-4-use-averaged-model.txt

@@ -0,0 +1,2 @@
+settings	WER
+beam_size_4	6.56

decoding_results/beam_search/wer-summary-test-beam_size_4-epoch-50-avg-22-beam_search-beam-size-4-use-averaged-model.txt

@@ -0,0 +1,2 @@
+settings	WER
+beam_size_4	5.95

decoding_results/fast_beam_search/log-decode-epoch-50-avg-22-beam-20.0-max-contexts-8-max-states-64-use-averaged-model-2023-06-15-16-02-29

@@ -0,0 +1,26 @@
+2023-06-15 16:02:29,961 INFO [decode.py:675] Decoding started
+2023-06-15 16:02:29,962 INFO [decode.py:681] Device: cuda:0
+2023-06-15 16:02:29,970 INFO [decode.py:691] {'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': '1.24.3', 'k2-build-type': 'Debug', 'k2-with-cuda': True, 'k2-git-sha1': '38211604d6a24b15f320578a1a38f6c12d7a711c', 'k2-git-date': 'Mon Jun 12 10:59:44 2023', 'lhotse-version': '1.15.0.dev+git.f1fd23d.clean', 'torch-version': '2.0.0+cu117', 'torch-cuda-available': True, 'torch-cuda-version': '11.7', 'python-version': '3.8', 'icefall-git-branch': 'ted/zipformer', 'icefall-git-sha1': '323a299-dirty', 'icefall-git-date': 'Tue Jun 13 04:47:15 2023', 'icefall-path': '/exp/draj/jsalt2023/icefall', 'k2-path': '/exp/draj/jsalt2023/k2/k2/python/k2/__init__.py', 'lhotse-path': '/exp/draj/jsalt2023/lhotse/lhotse/__init__.py', 'hostname': 'r2n02', 'IP address': '10.1.2.2'}, 'epoch': 50, 'iter': 0, 'avg': 22, 'use_averaged_model': True, 'exp_dir': PosixPath('zipformer/exp/v5'), 'bpe_model': 'data/lang_bpe_500/bpe.model', 'lang_dir': PosixPath('data/lang_bpe_500'), 'decoding_method': 'fast_beam_search', 'beam_size': 4, 'beam': 20.0, 'ngram_lm_scale': 0.01, 'max_contexts': 8, 'max_states': 64, 'context_size': 2, 'max_sym_per_frame': 1, 'num_paths': 200, 'nbest_scale': 0.5, 'num_encoder_layers': '2,2,3,4,3,2', 'downsampling_factor': '1,2,4,8,4,2', 'feedforward_dim': '512,768,1024,1536,1024,768', 'num_heads': '4,4,4,8,4,4', 'encoder_dim': '192,256,384,512,384,256', 'query_head_dim': '32', 'value_head_dim': '12', 'pos_head_dim': '4', 'pos_dim': 48, 'encoder_unmasked_dim': '192,192,256,256,256,192', 'cnn_module_kernel': '31,31,15,15,15,31', 'decoder_dim': 512, 'joiner_dim': 512, 'causal': False, 'chunk_size': '16,32,64,-1', 'left_context_frames': '64,128,256,-1', 'manifest_dir': PosixPath('data/manifests'), 'max_duration': 500, 'bucketing_sampler': True, 'num_buckets': 30, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'res_dir': PosixPath('zipformer/exp/v5/fast_beam_search'), 'suffix': 'epoch-50-avg-22-beam-20.0-max-contexts-8-max-states-64-use-averaged-model', 'blank_id': 0, 'unk_id': 2, 'vocab_size': 500}
+2023-06-15 16:02:29,970 INFO [decode.py:693] About to create model
+2023-06-15 16:02:30,674 INFO [decode.py:760] Calculating the averaged model over epoch range from 28 (excluded) to 50
+2023-06-15 16:02:50,856 INFO [decode.py:794] Number of model parameters: 65549011
+2023-06-15 16:02:50,857 INFO [asr_datamodule.py:361] About to get dev cuts
+2023-06-15 16:02:50,860 INFO [asr_datamodule.py:366] About to get test cuts
+2023-06-15 16:02:56,598 INFO [decode.py:572] batch 0/?, cuts processed until now is 30
+2023-06-15 16:03:41,470 INFO [decode.py:588] The transcripts are stored in zipformer/exp/v5/fast_beam_search/recogs-dev-beam_20.0_max_contexts_8_max_states_64-epoch-50-avg-22-beam-20.0-max-contexts-8-max-states-64-use-averaged-model.txt
+2023-06-15 16:03:41,539 INFO [utils.py:562] [dev-beam_20.0_max_contexts_8_max_states_64] %WER 6.91% [1260 / 18226, 182 ins, 467 del, 611 sub ]
+2023-06-15 16:03:41,601 INFO [decode.py:601] Wrote detailed error stats to zipformer/exp/v5/fast_beam_search/errs-dev-beam_20.0_max_contexts_8_max_states_64-epoch-50-avg-22-beam-20.0-max-contexts-8-max-states-64-use-averaged-model.txt
+2023-06-15 16:03:41,602 INFO [decode.py:617] 
+For dev, WER of different settings are:
+beam_20.0_max_contexts_8_max_states_64	6.91	best for dev
+
+2023-06-15 16:03:44,090 INFO [decode.py:572] batch 0/?, cuts processed until now is 40
+2023-06-15 16:04:22,021 INFO [decode.py:572] batch 20/?, cuts processed until now is 1063
+2023-06-15 16:04:34,908 INFO [decode.py:588] The transcripts are stored in zipformer/exp/v5/fast_beam_search/recogs-test-beam_20.0_max_contexts_8_max_states_64-epoch-50-avg-22-beam-20.0-max-contexts-8-max-states-64-use-averaged-model.txt
+2023-06-15 16:04:34,954 INFO [utils.py:562] [test-beam_20.0_max_contexts_8_max_states_64] %WER 6.28% [1785 / 28430, 186 ins, 788 del, 811 sub ]
+2023-06-15 16:04:35,049 INFO [decode.py:601] Wrote detailed error stats to zipformer/exp/v5/fast_beam_search/errs-test-beam_20.0_max_contexts_8_max_states_64-epoch-50-avg-22-beam-20.0-max-contexts-8-max-states-64-use-averaged-model.txt
+2023-06-15 16:04:35,050 INFO [decode.py:617] 
+For test, WER of different settings are:
+beam_20.0_max_contexts_8_max_states_64	6.28	best for test
+
+2023-06-15 16:04:35,050 INFO [decode.py:825] Done!

decoding_results/fast_beam_search/wer-summary-dev-beam_20.0_max_contexts_8_max_states_64-epoch-50-avg-22-beam-20.0-max-contexts-8-max-states-64-use-averaged-model.txt

@@ -0,0 +1,2 @@
+settings	WER
+beam_20.0_max_contexts_8_max_states_64	6.91

decoding_results/fast_beam_search/wer-summary-test-beam_20.0_max_contexts_8_max_states_64-epoch-50-avg-22-beam-20.0-max-contexts-8-max-states-64-use-averaged-model.txt

@@ -0,0 +1,2 @@
+settings	WER
+beam_20.0_max_contexts_8_max_states_64	6.28

decoding_results/greedy_search/log-decode-epoch-50-avg-22-context-2-max-sym-per-frame-1-use-averaged-model-2023-06-15-15-55-01

@@ -0,0 +1,26 @@
+2023-06-15 15:55:01,021 INFO [decode.py:675] Decoding started
+2023-06-15 15:55:01,023 INFO [decode.py:681] Device: cuda:0
+2023-06-15 15:55:01,031 INFO [decode.py:691] {'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': '1.24.3', 'k2-build-type': 'Debug', 'k2-with-cuda': True, 'k2-git-sha1': '38211604d6a24b15f320578a1a38f6c12d7a711c', 'k2-git-date': 'Mon Jun 12 10:59:44 2023', 'lhotse-version': '1.15.0.dev+git.f1fd23d.clean', 'torch-version': '2.0.0+cu117', 'torch-cuda-available': True, 'torch-cuda-version': '11.7', 'python-version': '3.8', 'icefall-git-branch': 'ted/zipformer', 'icefall-git-sha1': '323a299-dirty', 'icefall-git-date': 'Tue Jun 13 04:47:15 2023', 'icefall-path': '/exp/draj/jsalt2023/icefall', 'k2-path': '/exp/draj/jsalt2023/k2/k2/python/k2/__init__.py', 'lhotse-path': '/exp/draj/jsalt2023/lhotse/lhotse/__init__.py', 'hostname': 'r2n04', 'IP address': '10.1.2.4'}, 'epoch': 50, 'iter': 0, 'avg': 22, 'use_averaged_model': True, 'exp_dir': PosixPath('zipformer/exp/v5'), 'bpe_model': 'data/lang_bpe_500/bpe.model', 'lang_dir': PosixPath('data/lang_bpe_500'), 'decoding_method': 'greedy_search', 'beam_size': 4, 'beam': 20.0, 'ngram_lm_scale': 0.01, 'max_contexts': 8, 'max_states': 64, 'context_size': 2, 'max_sym_per_frame': 1, 'num_paths': 200, 'nbest_scale': 0.5, 'num_encoder_layers': '2,2,3,4,3,2', 'downsampling_factor': '1,2,4,8,4,2', 'feedforward_dim': '512,768,1024,1536,1024,768', 'num_heads': '4,4,4,8,4,4', 'encoder_dim': '192,256,384,512,384,256', 'query_head_dim': '32', 'value_head_dim': '12', 'pos_head_dim': '4', 'pos_dim': 48, 'encoder_unmasked_dim': '192,192,256,256,256,192', 'cnn_module_kernel': '31,31,15,15,15,31', 'decoder_dim': 512, 'joiner_dim': 512, 'causal': False, 'chunk_size': '16,32,64,-1', 'left_context_frames': '64,128,256,-1', 'manifest_dir': PosixPath('data/manifests'), 'max_duration': 500, 'bucketing_sampler': True, 'num_buckets': 30, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'res_dir': PosixPath('zipformer/exp/v5/greedy_search'), 'suffix': 'epoch-50-avg-22-context-2-max-sym-per-frame-1-use-averaged-model', 'blank_id': 0, 'unk_id': 2, 'vocab_size': 500}
+2023-06-15 15:55:01,031 INFO [decode.py:693] About to create model
+2023-06-15 15:55:01,633 INFO [decode.py:760] Calculating the averaged model over epoch range from 28 (excluded) to 50
+2023-06-15 15:55:05,547 INFO [decode.py:794] Number of model parameters: 65549011
+2023-06-15 15:55:05,547 INFO [asr_datamodule.py:361] About to get dev cuts
+2023-06-15 15:55:05,550 INFO [asr_datamodule.py:366] About to get test cuts
+2023-06-15 15:55:08,961 INFO [decode.py:572] batch 0/?, cuts processed until now is 30
+2023-06-15 15:55:22,921 INFO [zipformer.py:1728] name=None, attn_weights_entropy = tensor([3.8087, 3.2133, 3.5770, 3.0500], device='cuda:0')
+2023-06-15 15:55:27,056 INFO [decode.py:588] The transcripts are stored in zipformer/exp/v5/greedy_search/recogs-dev-greedy_search-epoch-50-avg-22-context-2-max-sym-per-frame-1-use-averaged-model.txt
+2023-06-15 15:55:27,088 INFO [utils.py:562] [dev-greedy_search] %WER 6.74% [1228 / 18226, 178 ins, 443 del, 607 sub ]
+2023-06-15 15:55:27,156 INFO [decode.py:601] Wrote detailed error stats to zipformer/exp/v5/greedy_search/errs-dev-greedy_search-epoch-50-avg-22-context-2-max-sym-per-frame-1-use-averaged-model.txt
+2023-06-15 15:55:27,158 INFO [decode.py:617] 
+For dev, WER of different settings are:
+greedy_search	6.74	best for dev
+
+2023-06-15 15:55:28,580 INFO [decode.py:572] batch 0/?, cuts processed until now is 40
+2023-06-15 15:55:49,101 INFO [decode.py:588] The transcripts are stored in zipformer/exp/v5/greedy_search/recogs-test-greedy_search-epoch-50-avg-22-context-2-max-sym-per-frame-1-use-averaged-model.txt
+2023-06-15 15:55:49,150 INFO [utils.py:562] [test-greedy_search] %WER 6.16% [1751 / 28430, 197 ins, 725 del, 829 sub ]
+2023-06-15 15:55:49,248 INFO [decode.py:601] Wrote detailed error stats to zipformer/exp/v5/greedy_search/errs-test-greedy_search-epoch-50-avg-22-context-2-max-sym-per-frame-1-use-averaged-model.txt
+2023-06-15 15:55:49,290 INFO [decode.py:617] 
+For test, WER of different settings are:
+greedy_search	6.16	best for test
+
+2023-06-15 15:55:49,290 INFO [decode.py:825] Done!

decoding_results/greedy_search/wer-summary-dev-greedy_search-epoch-50-avg-22-context-2-max-sym-per-frame-1-use-averaged-model.txt

@@ -0,0 +1,2 @@
+settings	WER
+greedy_search	6.74

decoding_results/greedy_search/wer-summary-test-greedy_search-epoch-50-avg-22-context-2-max-sym-per-frame-1-use-averaged-model.txt

@@ -0,0 +1,2 @@
+settings	WER
+greedy_search	6.16

decoding_results/modified_beam_search/log-decode-epoch-50-avg-22-modified_beam_search-beam-size-4-use-averaged-model-2023-06-15-15-56-46

@@ -0,0 +1,8 @@
+2023-06-15 15:56:46,258 INFO [decode.py:675] Decoding started
+2023-06-15 15:56:46,260 INFO [decode.py:681] Device: cuda:0
+2023-06-15 15:56:46,268 INFO [decode.py:691] {'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': '1.24.3', 'k2-build-type': 'Debug', 'k2-with-cuda': True, 'k2-git-sha1': '38211604d6a24b15f320578a1a38f6c12d7a711c', 'k2-git-date': 'Mon Jun 12 10:59:44 2023', 'lhotse-version': '1.15.0.dev+git.f1fd23d.clean', 'torch-version': '2.0.0+cu117', 'torch-cuda-available': True, 'torch-cuda-version': '11.7', 'python-version': '3.8', 'icefall-git-branch': 'ted/zipformer', 'icefall-git-sha1': '323a299-dirty', 'icefall-git-date': 'Tue Jun 13 04:47:15 2023', 'icefall-path': '/exp/draj/jsalt2023/icefall', 'k2-path': '/exp/draj/jsalt2023/k2/k2/python/k2/__init__.py', 'lhotse-path': '/exp/draj/jsalt2023/lhotse/lhotse/__init__.py', 'hostname': 'r2n04', 'IP address': '10.1.2.4'}, 'epoch': 50, 'iter': 0, 'avg': 22, 'use_averaged_model': True, 'exp_dir': PosixPath('zipformer/exp/v5'), 'bpe_model': 'data/lang_bpe_500/bpe.model', 'lang_dir': PosixPath('data/lang_bpe_500'), 'decoding_method': 'modified_beam_search', 'beam_size': 4, 'beam': 20.0, 'ngram_lm_scale': 0.01, 'max_contexts': 8, 'max_states': 64, 'context_size': 2, 'max_sym_per_frame': 1, 'num_paths': 200, 'nbest_scale': 0.5, 'num_encoder_layers': '2,2,3,4,3,2', 'downsampling_factor': '1,2,4,8,4,2', 'feedforward_dim': '512,768,1024,1536,1024,768', 'num_heads': '4,4,4,8,4,4', 'encoder_dim': '192,256,384,512,384,256', 'query_head_dim': '32', 'value_head_dim': '12', 'pos_head_dim': '4', 'pos_dim': 48, 'encoder_unmasked_dim': '192,192,256,256,256,192', 'cnn_module_kernel': '31,31,15,15,15,31', 'decoder_dim': 512, 'joiner_dim': 512, 'causal': False, 'chunk_size': '16,32,64,-1', 'left_context_frames': '64,128,256,-1', 'manifest_dir': PosixPath('data/manifests'), 'max_duration': 500, 'bucketing_sampler': True, 'num_buckets': 30, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'res_dir': PosixPath('zipformer/exp/v5/modified_beam_search'), 'suffix': 'epoch-50-avg-22-modified_beam_search-beam-size-4-use-averaged-model', 'blank_id': 0, 'unk_id': 2, 'vocab_size': 500}
+2023-06-15 15:56:46,268 INFO [decode.py:693] About to create model
+2023-06-15 15:56:46,927 INFO [decode.py:760] Calculating the averaged model over epoch range from 28 (excluded) to 50
+2023-06-15 15:56:51,104 INFO [decode.py:794] Number of model parameters: 65549011
+2023-06-15 15:56:51,104 INFO [asr_datamodule.py:361] About to get dev cuts
+2023-06-15 15:56:51,106 INFO [asr_datamodule.py:366] About to get test cuts

decoding_results/modified_beam_search/log-decode-epoch-50-avg-22-modified_beam_search-beam-size-4-use-averaged-model-2023-06-15-15-58-01

@@ -0,0 +1,27 @@
+2023-06-15 15:58:01,483 INFO [decode.py:675] Decoding started
+2023-06-15 15:58:01,484 INFO [decode.py:681] Device: cuda:0
+2023-06-15 15:58:01,492 INFO [decode.py:691] {'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': '1.24.3', 'k2-build-type': 'Debug', 'k2-with-cuda': True, 'k2-git-sha1': '38211604d6a24b15f320578a1a38f6c12d7a711c', 'k2-git-date': 'Mon Jun 12 10:59:44 2023', 'lhotse-version': '1.15.0.dev+git.f1fd23d.clean', 'torch-version': '2.0.0+cu117', 'torch-cuda-available': True, 'torch-cuda-version': '11.7', 'python-version': '3.8', 'icefall-git-branch': 'ted/zipformer', 'icefall-git-sha1': '323a299-dirty', 'icefall-git-date': 'Tue Jun 13 04:47:15 2023', 'icefall-path': '/exp/draj/jsalt2023/icefall', 'k2-path': '/exp/draj/jsalt2023/k2/k2/python/k2/__init__.py', 'lhotse-path': '/exp/draj/jsalt2023/lhotse/lhotse/__init__.py', 'hostname': 'r2n04', 'IP address': '10.1.2.4'}, 'epoch': 50, 'iter': 0, 'avg': 22, 'use_averaged_model': True, 'exp_dir': PosixPath('zipformer/exp/v5'), 'bpe_model': 'data/lang_bpe_500/bpe.model', 'lang_dir': PosixPath('data/lang_bpe_500'), 'decoding_method': 'modified_beam_search', 'beam_size': 4, 'beam': 20.0, 'ngram_lm_scale': 0.01, 'max_contexts': 8, 'max_states': 64, 'context_size': 2, 'max_sym_per_frame': 1, 'num_paths': 200, 'nbest_scale': 0.5, 'num_encoder_layers': '2,2,3,4,3,2', 'downsampling_factor': '1,2,4,8,4,2', 'feedforward_dim': '512,768,1024,1536,1024,768', 'num_heads': '4,4,4,8,4,4', 'encoder_dim': '192,256,384,512,384,256', 'query_head_dim': '32', 'value_head_dim': '12', 'pos_head_dim': '4', 'pos_dim': 48, 'encoder_unmasked_dim': '192,192,256,256,256,192', 'cnn_module_kernel': '31,31,15,15,15,31', 'decoder_dim': 512, 'joiner_dim': 512, 'causal': False, 'chunk_size': '16,32,64,-1', 'left_context_frames': '64,128,256,-1', 'manifest_dir': PosixPath('data/manifests'), 'max_duration': 500, 'bucketing_sampler': True, 'num_buckets': 30, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'res_dir': PosixPath('zipformer/exp/v5/modified_beam_search'), 'suffix': 'epoch-50-avg-22-modified_beam_search-beam-size-4-use-averaged-model', 'blank_id': 0, 'unk_id': 2, 'vocab_size': 500}
+2023-06-15 15:58:01,492 INFO [decode.py:693] About to create model
+2023-06-15 15:58:02,075 INFO [decode.py:760] Calculating the averaged model over epoch range from 28 (excluded) to 50
+2023-06-15 15:58:05,955 INFO [decode.py:794] Number of model parameters: 65549011
+2023-06-15 15:58:05,956 INFO [asr_datamodule.py:361] About to get dev cuts
+2023-06-15 15:58:05,958 INFO [asr_datamodule.py:366] About to get test cuts
+2023-06-15 15:58:15,345 INFO [decode.py:572] batch 0/?, cuts processed until now is 30
+2023-06-15 15:59:30,951 INFO [decode.py:588] The transcripts are stored in zipformer/exp/v5/modified_beam_search/recogs-dev-beam_size_4-epoch-50-avg-22-modified_beam_search-beam-size-4-use-averaged-model.txt
+2023-06-15 15:59:30,981 INFO [utils.py:562] [dev-beam_size_4] %WER 6.54% [1192 / 18226, 188 ins, 402 del, 602 sub ]
+2023-06-15 15:59:31,044 INFO [decode.py:601] Wrote detailed error stats to zipformer/exp/v5/modified_beam_search/errs-dev-beam_size_4-epoch-50-avg-22-modified_beam_search-beam-size-4-use-averaged-model.txt
+2023-06-15 15:59:31,045 INFO [decode.py:617] 
+For dev, WER of different settings are:
+beam_size_4	6.54	best for dev
+
+2023-06-15 15:59:36,799 INFO [decode.py:572] batch 0/?, cuts processed until now is 40
+2023-06-15 16:01:10,193 INFO [decode.py:572] batch 20/?, cuts processed until now is 1063
+2023-06-15 16:01:25,571 INFO [zipformer.py:1728] name=None, attn_weights_entropy = tensor([1.9471, 2.3907, 3.3421, 3.0589], device='cuda:0')
+2023-06-15 16:01:28,902 INFO [decode.py:588] The transcripts are stored in zipformer/exp/v5/modified_beam_search/recogs-test-beam_size_4-epoch-50-avg-22-modified_beam_search-beam-size-4-use-averaged-model.txt
+2023-06-15 16:01:28,948 INFO [utils.py:562] [test-beam_size_4] %WER 6.00% [1707 / 28430, 204 ins, 699 del, 804 sub ]
+2023-06-15 16:01:29,043 INFO [decode.py:601] Wrote detailed error stats to zipformer/exp/v5/modified_beam_search/errs-test-beam_size_4-epoch-50-avg-22-modified_beam_search-beam-size-4-use-averaged-model.txt
+2023-06-15 16:01:29,044 INFO [decode.py:617] 
+For test, WER of different settings are:
+beam_size_4	6.0	best for test
+
+2023-06-15 16:01:29,044 INFO [decode.py:825] Done!

decoding_results/modified_beam_search/wer-summary-dev-beam_size_4-epoch-50-avg-22-modified_beam_search-beam-size-4-use-averaged-model.txt

@@ -0,0 +1,2 @@
+settings	WER
+beam_size_4	6.54

decoding_results/modified_beam_search/wer-summary-test-beam_size_4-epoch-50-avg-22-modified_beam_search-beam-size-4-use-averaged-model.txt

@@ -0,0 +1,2 @@
+settings	WER
+beam_size_4	6.0

exp/decode.sh

@@ -0,0 +1,12 @@
+export CUDA_VISIBLE_DEVICES="0"
+for m in greedy_search beam_search fast_beam_search modified_beam_search; do
+  ./zipformer/decode.py \
+      --epoch 50 \
+      --avg 22 \
+      --use-averaged-model True \
+      --exp-dir zipformer/exp \
+      --max-duration 500 \
+      --causal 0 \
+      --decoding-method $m \
+      --beam-size 4
+done

exp/export.sh

@@ -0,0 +1,6 @@
+./zipformer/export.py \
+  --exp-dir ./zipformer/exp \
+  --bpe-model data/lang_bpe_500/bpe.model \
+  --epoch 50 \
+  --avg 22 \
+  --jit 1

exp/jit_script.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:254527e341deea8496867da1ea086efa2a33e2ec3c624bb5dc3727bb3f03e9c2
+size 264940478

exp/pretrained.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f533966f4811c5c3d343b307dca956f9b9d63accbf7035b9bcfc4102c584d2e5
+size 262605742

exp/tensorboard/events.out.tfevents.1686808592.r2n01.160747.0

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+version https://git-lfs.github.com/spec/v1
+oid sha256:512da5ba3cbf0b75738c65c1afc259a9b13907f3e8242b704971dca0b9341bed
+size 272322

exp/train.sh

@@ -0,0 +1,10 @@
+export CUDA_VISIBLE_DEVICES="0,1,2,3"
+./zipformer/train.py \
+  --world-size 4 \
+  --num-epochs 50 \
+  --start-epoch 1 \
+  --use-fp16 1 \
+  --exp-dir zipformer/exp \
+  --causal 0 \
+  --max-duration 1000 \
+  --master-port 12345

test_wavs/trans.txt

@@ -0,0 +1,3 @@
+DanBarber_2010-219 well the last year this property had six hundred thousand birds on it
+RobertGupta_2010U-15 and he was talking about invisible demons and smoke and how someone was poisoning him in his sleep and i was afraid not for myself but i was afraid that i was going to lose him that he was going to sink into one of his states
+DanielKahneman_2010-157 goes very different ways depending on how you think and whether you think of the remembering self or you think of the experiencing self this is going to influence policy i think in years to come in the united states efforts are being made