huanz

Huanz's group workspace

Group: composer_id-ASAP-perfmidi-sequence-CPWord-bpe0

1-8

of 8

Tags

Notes

Author

huanz

State

Finished

Start time

March 12th, 2023 1:44:01 PM

Runtime

2h 48m 46s

Tracked hours

2h 48m 39s

Run path

huanz/symrep/dpxdfo5o

Linux-3.10.0-1160.11.1.el7.x86_64-x86_64-with-glibc2.17

Python version

3.9.7

Git repository

git clone https://github.com/anusfoil/SymRep.git

Git state

git checkout -b "composer_id-ASAP-perfmidi-sequence-fold6" 7e0c86b8c3c48706312f7f33b136109d8f244962

Command

/homes/hz009/Research/SymRep/experiments/train.py experiment.fold_idx=6 experiment.grouped=1 experiment.dataset=ASAP experiment.symrep=sequence experiment.input_format=perfmidi experiment.lr=1e-5 sequence.mid_encoding=CPWord experiment.device=[0] experiment.batch_size=2

System Hardware

CPU count	40
Logical CPU count	80
GPU count	3
GPU type	Quadro RTX 6000

W&B CLI Version

0.13.10

Group

composer_id-ASAP-perfmidi-sequence-CPWord-bpe0

Config parameters are your model's inputs. Learn more

▶
Config parameters:{} 72 keys
- cfg/dataset/ASAP/dataset_dir:
  "/homes/hz009/Research/Datasets/asap-dataset/"
- cfg/dataset/ASAP/metadata_file:
  "/homes/hz009/Research/Datasets/asap-dataset/metadata-v1.3.csv"
- cfg/dataset/ATEPP/dataset_dir:
  "/homes/hz009/Research/Datasets/ATEPP-1.1/"
- cfg/dataset/ATEPP/metadata_file:
  "/homes/hz009/Research/Datasets/ATEPP-1.1/ATEPP-metadata-1.5.csv"
- cfg/dataset/PD/dataset_dir:
  "/homes/hz009/Research/Datasets/piano_difficulty/"
- cfg/dataset/PD/metadata_file:
  "/homes/hz009/Research/Datasets/piano_difficulty/labels.csv"
- cfg/experiment/artifact_dir:
  "huanz/symrep/model-g77vev0k:v19"
- cfg/experiment/batch_size:
  2
- cfg/experiment/checkpoint_dir:
  "checkpoints/composer_id-ASAP-perfmidi-sequence-fold6"
- cfg/experiment/checkpoint_file:
  "checkpoints/composer_id-ASAP-perfmidi-sequence-fold6/epoch=49-step=1850.ckpt"
- cfg/experiment/data_save_dir:
  "/import/c4dm-datasets-ext/symrep_assets/sequence/ASAP/perfmidi"
- cfg/experiment/dataset:
  "ASAP"
- ▶
  cfg/experiment/device:[] 1 item
  - 0:
    0
- cfg/experiment/emb_dim:
  32
- cfg/experiment/epoch:
  300
- cfg/experiment/es_patience:
  60
- cfg/experiment/es_threshold:
  0.005
- cfg/experiment/exp_name:
  "composer_id-ASAP-perfmidi-sequence-fold6"
- cfg/experiment/feat_level:
  0
- cfg/experiment/fold_idx:
  6
- cfg/experiment/group_name:
  "composer_id-ASAP-perfmidi-sequence-CPWord-bpe0"
- cfg/experiment/grouped:
  1
- cfg/experiment/input_format:
  "perfmidi"
- cfg/experiment/load_data:
  true
- cfg/experiment/load_model:
  false
- cfg/experiment/lr:
  0.00001
- cfg/experiment/lr_gamma:
  0.99
- cfg/experiment/random_seed:
  13
- cfg/experiment/restore_training:
  false
- cfg/experiment/symrep:
  "sequence"
- cfg/experiment/task:
  "composer_id"
- ▶
  cfg/graph/basic_edges:[] 7 items
- cfg/graph/bi_dir:
  true
- cfg/graph/conv_type:
  "SAGEConv"
- cfg/graph/dropout:
  0.2
- cfg/graph/edge_agg:
  "max"
- cfg/graph/hid_dim:
  256
- cfg/graph/homo:
  0
- cfg/graph/mid_window:
  0.03
- cfg/graph/n_layers:
  2
- cfg/graph/sage_agg:
  "lstm"
- cfg/matrix/bins:
  131
- cfg/matrix/n_channels:
  2
- ▶
  cfg/matrix/res_layers:[] 4 items
  - 0:
    1
  - 1:
    1
  - 2:
    1
  - 3:
    1
- cfg/matrix/resolution:
  600
- cfg/matrix/save_dir:
  "fix_time-(4|300|60|180)-600-0"
- model_backend:
  null
- model_frontend:
  null
- ▶
  segmentation:{} 5 keys
- ▶
  sequence:{} 13 keys

Summary metrics are your model's outputs. Learn more

▶
Summary metrics:{} 19 keys
- epoch:
  92
- ▶
  graph_0:{} 4 keys
  - _type:
    "graph-file"
  - path:
    "media/graph/graph_0_summary_61be513418e64ab1e511.graph.json"
  - sha256:
    "61be513418e64ab1e511debdf3c07bf986d33704a3979624600cd5585e29e51c"
  - size:
    8,226
- lr-Adam:
  0.00000001
- test_acc:
  0.5607476830482483
- test_auroc:
  0.7723361849784851
- test_fscore:
  0.23973797261714935
- train_acc_epoch:
  0.6546489596366882
- train_acc_step:
  0.5
- train_auroc_epoch:
  0.8134868144989014
- train_auroc_step:
  0.1818181872367859
- train_fscore_epoch:
  0.29051560163497925
- train_fscore_step:
  0.09090909361839294
- train_loss_epoch:
  1.0762674808502195
- train_loss_step:
  0.9760421514511108
- trainer/global_step:
  24,288
- val_acc:
  0.5733333230018616
- val_auroc:
  0.6802442073822021
- val_fscore:
  0.24441877007484436
- val_loss:
  1.1881918907165527