Yushi Ueda
commited on
Commit
•
1885523
1
Parent(s):
434e276
Update model
Browse files- README.md +237 -0
- exp/diar_stats_8k/train/feats_stats.npz +0 -0
- exp/diar_train_diar_raw/17epoch.pth +3 -0
- exp/diar_train_diar_raw/RESULTS.md +25 -0
- exp/diar_train_diar_raw/config.yaml +143 -0
- exp/diar_train_diar_raw/images/acc.png +0 -0
- exp/diar_train_diar_raw/images/backward_time.png +0 -0
- exp/diar_train_diar_raw/images/cf.png +0 -0
- exp/diar_train_diar_raw/images/der.png +0 -0
- exp/diar_train_diar_raw/images/fa.png +0 -0
- exp/diar_train_diar_raw/images/forward_time.png +0 -0
- exp/diar_train_diar_raw/images/gpu_max_cached_mem_GB.png +0 -0
- exp/diar_train_diar_raw/images/iter_time.png +0 -0
- exp/diar_train_diar_raw/images/loss.png +0 -0
- exp/diar_train_diar_raw/images/loss_att.png +0 -0
- exp/diar_train_diar_raw/images/loss_pit.png +0 -0
- exp/diar_train_diar_raw/images/mi.png +0 -0
- exp/diar_train_diar_raw/images/optim0_lr0.png +0 -0
- exp/diar_train_diar_raw/images/optim_step_time.png +0 -0
- exp/diar_train_diar_raw/images/sad_fr.png +0 -0
- exp/diar_train_diar_raw/images/sad_mr.png +0 -0
- exp/diar_train_diar_raw/images/train_time.png +0 -0
- meta.yaml +8 -0
README.md
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1 |
+
---
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tags:
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- espnet
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- audio
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- diarization
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language: noinfo
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datasets:
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- mini_librispeech
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license: cc-by-4.0
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---
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## ESPnet2 DIAR model
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### `espnet/YushiUeda_mini_librispeech_diar_train_diar_raw_valid.acc.best`
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This model was trained by Yushi Ueda using mini_librispeech recipe in [espnet](https://github.com/espnet/espnet/).
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### Demo: How to use in ESPnet2
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```bash
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cd espnet
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git checkout 650472b45a67612eaac09c7fbd61dc25f8ff2405
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pip install -e .
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cd egs2/mini_librispeech/diar1
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./run.sh --skip_data_prep false --skip_train true --download_model espnet/YushiUeda_mini_librispeech_diar_train_diar_raw_valid.acc.best
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```
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<!-- Generated by scripts/utils/show_diar_result.sh -->
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# RESULTS
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## Environments
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- date: `Tue Jan 4 16:43:34 EST 2022`
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- python version: `3.7.11 (default, Jul 27 2021, 14:32:16) [GCC 7.5.0]`
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- espnet version: `espnet 0.10.5a1`
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- pytorch version: `pytorch 1.9.0+cu102`
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- Git hash: `0b2a6786b6f627f47defaee22911b3c2dc04af2a`
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- Commit date: `Thu Dec 23 12:22:49 2021 -0500`
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## diar_train_diar_raw
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### DER
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dev_clean_2_ns2_beta2_500
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|threshold_median_collar|DER|
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|---|---|
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|result_th0.3_med11_collar0.0|32.28|
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|result_th0.3_med1_collar0.0|32.64|
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|result_th0.4_med11_collar0.0|30.43|
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|result_th0.4_med1_collar0.0|31.15|
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|result_th0.5_med11_collar0.0|29.45|
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|result_th0.5_med1_collar0.0|30.53|
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|result_th0.6_med11_collar0.0|29.52|
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|result_th0.6_med1_collar0.0|30.95|
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|result_th0.7_med11_collar0.0|30.92|
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|result_th0.7_med1_collar0.0|32.69|
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## DIAR config
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<details><summary>expand</summary>
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```
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config: conf/train_diar.yaml
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print_config: false
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log_level: INFO
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dry_run: false
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iterator_type: chunk
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output_dir: exp/diar_train_diar_raw
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ngpu: 1
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seed: 0
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num_workers: 1
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num_att_plot: 3
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dist_backend: nccl
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dist_init_method: env://
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dist_world_size: 4
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dist_rank: 0
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local_rank: 0
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dist_master_addr: localhost
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dist_master_port: 33757
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dist_launcher: null
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multiprocessing_distributed: true
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unused_parameters: false
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sharded_ddp: false
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cudnn_enabled: true
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cudnn_benchmark: false
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cudnn_deterministic: true
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collect_stats: false
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write_collected_feats: false
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max_epoch: 100
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patience: 3
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val_scheduler_criterion:
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- valid
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- loss
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early_stopping_criterion:
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- valid
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- loss
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- min
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best_model_criterion:
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- - valid
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- acc
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- max
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keep_nbest_models: 3
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nbest_averaging_interval: 0
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grad_clip: 5
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grad_clip_type: 2.0
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grad_noise: false
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accum_grad: 2
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no_forward_run: false
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resume: true
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train_dtype: float32
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use_amp: false
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log_interval: null
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use_matplotlib: true
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use_tensorboard: true
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use_wandb: false
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wandb_project: null
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wandb_id: null
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wandb_entity: null
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wandb_name: null
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wandb_model_log_interval: -1
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detect_anomaly: false
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pretrain_path: null
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init_param: []
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ignore_init_mismatch: false
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freeze_param: []
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num_iters_per_epoch: null
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batch_size: 16
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valid_batch_size: null
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batch_bins: 1000000
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valid_batch_bins: null
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train_shape_file:
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- exp/diar_stats_8k/train/speech_shape
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- exp/diar_stats_8k/train/spk_labels_shape
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valid_shape_file:
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- exp/diar_stats_8k/valid/speech_shape
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- exp/diar_stats_8k/valid/spk_labels_shape
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batch_type: folded
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valid_batch_type: null
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fold_length:
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- 80000
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- 800
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sort_in_batch: descending
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sort_batch: descending
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multiple_iterator: false
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chunk_length: 200000
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chunk_shift_ratio: 0.5
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num_cache_chunks: 64
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train_data_path_and_name_and_type:
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- - dump/raw/simu/data/train_clean_5_ns2_beta2_500/wav.scp
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- speech
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- sound
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- - dump/raw/simu/data/train_clean_5_ns2_beta2_500/espnet_rttm
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- spk_labels
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- rttm
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valid_data_path_and_name_and_type:
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- - dump/raw/simu/data/dev_clean_2_ns2_beta2_500/wav.scp
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- speech
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- sound
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- - dump/raw/simu/data/dev_clean_2_ns2_beta2_500/espnet_rttm
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- spk_labels
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- rttm
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allow_variable_data_keys: false
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max_cache_size: 0.0
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max_cache_fd: 32
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valid_max_cache_size: null
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optim: adam
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optim_conf:
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lr: 0.01
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scheduler: noamlr
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scheduler_conf:
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warmup_steps: 1000
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num_spk: 2
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init: xavier_uniform
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input_size: null
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model_conf:
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attractor_weight: 1.0
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use_preprocessor: true
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frontend: default
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frontend_conf:
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fs: 8k
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hop_length: 128
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specaug: null
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specaug_conf: {}
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normalize: global_mvn
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normalize_conf:
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stats_file: exp/diar_stats_8k/train/feats_stats.npz
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encoder: transformer
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encoder_conf:
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input_layer: linear
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num_blocks: 2
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linear_units: 512
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dropout_rate: 0.1
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output_size: 256
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attention_heads: 4
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attention_dropout_rate: 0.0
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decoder: linear
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decoder_conf: {}
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label_aggregator: label_aggregator
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label_aggregator_conf: {}
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attractor: null
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attractor_conf: {}
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required:
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- output_dir
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version: 0.10.5a1
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distributed: true
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```
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</details>
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### Citing ESPnet
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```BibTex
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@inproceedings{watanabe2018espnet,
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author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Yalta and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
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title={{ESPnet}: End-to-End Speech Processing Toolkit},
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year={2018},
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booktitle={Proceedings of Interspeech},
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pages={2207--2211},
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doi={10.21437/Interspeech.2018-1456},
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url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
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}
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```
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or arXiv:
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|
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```bibtex
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@misc{watanabe2018espnet,
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title={ESPnet: End-to-End Speech Processing Toolkit},
|
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author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Yalta and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
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year={2018},
|
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eprint={1804.00015},
|
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archivePrefix={arXiv},
|
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+
primaryClass={cs.CL}
|
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+
}
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+
```
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exp/diar_stats_8k/train/feats_stats.npz
ADDED
Binary file (1.4 kB). View file
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exp/diar_train_diar_raw/17epoch.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:984810467c4181442cd8aa27e007c39a2c4cef280b1089024254a938f65e20f0
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size 4404388
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exp/diar_train_diar_raw/RESULTS.md
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<!-- Generated by scripts/utils/show_diar_result.sh -->
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# RESULTS
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+
## Environments
|
4 |
+
- date: `Tue Jan 4 16:43:34 EST 2022`
|
5 |
+
- python version: `3.7.11 (default, Jul 27 2021, 14:32:16) [GCC 7.5.0]`
|
6 |
+
- espnet version: `espnet 0.10.5a1`
|
7 |
+
- pytorch version: `pytorch 1.9.0+cu102`
|
8 |
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- Git hash: `0b2a6786b6f627f47defaee22911b3c2dc04af2a`
|
9 |
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- Commit date: `Thu Dec 23 12:22:49 2021 -0500`
|
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+
|
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## diar_train_diar_raw
|
12 |
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### DER
|
13 |
+
dev_clean_2_ns2_beta2_500
|
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+
|threshold_median_collar|DER|
|
15 |
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|---|---|
|
16 |
+
|result_th0.3_med11_collar0.0|32.28|
|
17 |
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|result_th0.3_med1_collar0.0|32.64|
|
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|result_th0.4_med11_collar0.0|30.43|
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|result_th0.4_med1_collar0.0|31.15|
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|result_th0.5_med11_collar0.0|29.45|
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|result_th0.5_med1_collar0.0|30.53|
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|result_th0.6_med11_collar0.0|29.52|
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|result_th0.6_med1_collar0.0|30.95|
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|result_th0.7_med11_collar0.0|30.92|
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|result_th0.7_med1_collar0.0|32.69|
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exp/diar_train_diar_raw/config.yaml
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|
1 |
+
config: conf/train_diar.yaml
|
2 |
+
print_config: false
|
3 |
+
log_level: INFO
|
4 |
+
dry_run: false
|
5 |
+
iterator_type: chunk
|
6 |
+
output_dir: exp/diar_train_diar_raw
|
7 |
+
ngpu: 1
|
8 |
+
seed: 0
|
9 |
+
num_workers: 1
|
10 |
+
num_att_plot: 3
|
11 |
+
dist_backend: nccl
|
12 |
+
dist_init_method: env://
|
13 |
+
dist_world_size: 4
|
14 |
+
dist_rank: 0
|
15 |
+
local_rank: 0
|
16 |
+
dist_master_addr: localhost
|
17 |
+
dist_master_port: 33757
|
18 |
+
dist_launcher: null
|
19 |
+
multiprocessing_distributed: true
|
20 |
+
unused_parameters: false
|
21 |
+
sharded_ddp: false
|
22 |
+
cudnn_enabled: true
|
23 |
+
cudnn_benchmark: false
|
24 |
+
cudnn_deterministic: true
|
25 |
+
collect_stats: false
|
26 |
+
write_collected_feats: false
|
27 |
+
max_epoch: 100
|
28 |
+
patience: 3
|
29 |
+
val_scheduler_criterion:
|
30 |
+
- valid
|
31 |
+
- loss
|
32 |
+
early_stopping_criterion:
|
33 |
+
- valid
|
34 |
+
- loss
|
35 |
+
- min
|
36 |
+
best_model_criterion:
|
37 |
+
- - valid
|
38 |
+
- acc
|
39 |
+
- max
|
40 |
+
keep_nbest_models: 3
|
41 |
+
nbest_averaging_interval: 0
|
42 |
+
grad_clip: 5
|
43 |
+
grad_clip_type: 2.0
|
44 |
+
grad_noise: false
|
45 |
+
accum_grad: 2
|
46 |
+
no_forward_run: false
|
47 |
+
resume: true
|
48 |
+
train_dtype: float32
|
49 |
+
use_amp: false
|
50 |
+
log_interval: null
|
51 |
+
use_matplotlib: true
|
52 |
+
use_tensorboard: true
|
53 |
+
use_wandb: false
|
54 |
+
wandb_project: null
|
55 |
+
wandb_id: null
|
56 |
+
wandb_entity: null
|
57 |
+
wandb_name: null
|
58 |
+
wandb_model_log_interval: -1
|
59 |
+
detect_anomaly: false
|
60 |
+
pretrain_path: null
|
61 |
+
init_param: []
|
62 |
+
ignore_init_mismatch: false
|
63 |
+
freeze_param: []
|
64 |
+
num_iters_per_epoch: null
|
65 |
+
batch_size: 16
|
66 |
+
valid_batch_size: null
|
67 |
+
batch_bins: 1000000
|
68 |
+
valid_batch_bins: null
|
69 |
+
train_shape_file:
|
70 |
+
- exp/diar_stats_8k/train/speech_shape
|
71 |
+
- exp/diar_stats_8k/train/spk_labels_shape
|
72 |
+
valid_shape_file:
|
73 |
+
- exp/diar_stats_8k/valid/speech_shape
|
74 |
+
- exp/diar_stats_8k/valid/spk_labels_shape
|
75 |
+
batch_type: folded
|
76 |
+
valid_batch_type: null
|
77 |
+
fold_length:
|
78 |
+
- 80000
|
79 |
+
- 800
|
80 |
+
sort_in_batch: descending
|
81 |
+
sort_batch: descending
|
82 |
+
multiple_iterator: false
|
83 |
+
chunk_length: 200000
|
84 |
+
chunk_shift_ratio: 0.5
|
85 |
+
num_cache_chunks: 64
|
86 |
+
train_data_path_and_name_and_type:
|
87 |
+
- - dump/raw/simu/data/train_clean_5_ns2_beta2_500/wav.scp
|
88 |
+
- speech
|
89 |
+
- sound
|
90 |
+
- - dump/raw/simu/data/train_clean_5_ns2_beta2_500/espnet_rttm
|
91 |
+
- spk_labels
|
92 |
+
- rttm
|
93 |
+
valid_data_path_and_name_and_type:
|
94 |
+
- - dump/raw/simu/data/dev_clean_2_ns2_beta2_500/wav.scp
|
95 |
+
- speech
|
96 |
+
- sound
|
97 |
+
- - dump/raw/simu/data/dev_clean_2_ns2_beta2_500/espnet_rttm
|
98 |
+
- spk_labels
|
99 |
+
- rttm
|
100 |
+
allow_variable_data_keys: false
|
101 |
+
max_cache_size: 0.0
|
102 |
+
max_cache_fd: 32
|
103 |
+
valid_max_cache_size: null
|
104 |
+
optim: adam
|
105 |
+
optim_conf:
|
106 |
+
lr: 0.01
|
107 |
+
scheduler: noamlr
|
108 |
+
scheduler_conf:
|
109 |
+
warmup_steps: 1000
|
110 |
+
num_spk: 2
|
111 |
+
init: xavier_uniform
|
112 |
+
input_size: null
|
113 |
+
model_conf:
|
114 |
+
attractor_weight: 1.0
|
115 |
+
use_preprocessor: true
|
116 |
+
frontend: default
|
117 |
+
frontend_conf:
|
118 |
+
fs: 8k
|
119 |
+
hop_length: 128
|
120 |
+
specaug: null
|
121 |
+
specaug_conf: {}
|
122 |
+
normalize: global_mvn
|
123 |
+
normalize_conf:
|
124 |
+
stats_file: exp/diar_stats_8k/train/feats_stats.npz
|
125 |
+
encoder: transformer
|
126 |
+
encoder_conf:
|
127 |
+
input_layer: linear
|
128 |
+
num_blocks: 2
|
129 |
+
linear_units: 512
|
130 |
+
dropout_rate: 0.1
|
131 |
+
output_size: 256
|
132 |
+
attention_heads: 4
|
133 |
+
attention_dropout_rate: 0.0
|
134 |
+
decoder: linear
|
135 |
+
decoder_conf: {}
|
136 |
+
label_aggregator: label_aggregator
|
137 |
+
label_aggregator_conf: {}
|
138 |
+
attractor: null
|
139 |
+
attractor_conf: {}
|
140 |
+
required:
|
141 |
+
- output_dir
|
142 |
+
version: 0.10.5a1
|
143 |
+
distributed: true
|
exp/diar_train_diar_raw/images/acc.png
ADDED
exp/diar_train_diar_raw/images/backward_time.png
ADDED
exp/diar_train_diar_raw/images/cf.png
ADDED
exp/diar_train_diar_raw/images/der.png
ADDED
exp/diar_train_diar_raw/images/fa.png
ADDED
exp/diar_train_diar_raw/images/forward_time.png
ADDED
exp/diar_train_diar_raw/images/gpu_max_cached_mem_GB.png
ADDED
exp/diar_train_diar_raw/images/iter_time.png
ADDED
exp/diar_train_diar_raw/images/loss.png
ADDED
exp/diar_train_diar_raw/images/loss_att.png
ADDED
exp/diar_train_diar_raw/images/loss_pit.png
ADDED
exp/diar_train_diar_raw/images/mi.png
ADDED
exp/diar_train_diar_raw/images/optim0_lr0.png
ADDED
exp/diar_train_diar_raw/images/optim_step_time.png
ADDED
exp/diar_train_diar_raw/images/sad_fr.png
ADDED
exp/diar_train_diar_raw/images/sad_mr.png
ADDED
exp/diar_train_diar_raw/images/train_time.png
ADDED
meta.yaml
ADDED
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
espnet: 0.10.5a1
|
2 |
+
files:
|
3 |
+
model_file: exp/diar_train_diar_raw/17epoch.pth
|
4 |
+
python: "3.7.11 (default, Jul 27 2021, 14:32:16) \n[GCC 7.5.0]"
|
5 |
+
timestamp: 1641332630.356345
|
6 |
+
torch: 1.9.0+cu102
|
7 |
+
yaml_files:
|
8 |
+
train_config: exp/diar_train_diar_raw/config.yaml
|