add runs for first experiments

configs/hparams_search/focusMSE_150_optuna.yaml

@@ -14,6 +14,9 @@ optimized_metric: "val/mae_best"
 
 name: "focusMSE_150_hyperparameter_search"
 
+model:
+  _target_: src.models.focus_module.FocusMSELitModule
+
 # here we define Optuna hyperparameter search
 # it optimizes for value returned from function with @hydra.main decorator
 # docs: https://hydra.cc/docs/next/plugins/optuna_sweeper
@@ -49,8 +52,6 @@ hydra:
       datamodule.batch_size:
         type: categorical
         choices: [64, 128]
-      model:
-        _target_: src.models.focus_module.FocusMSELitModule
       model.lr:
         type: float
         low: 0.0001

logs/experiments/runs/focusMAE_150/2022-03-10_13-27-16/.hydra/config.yaml

@@ -0,0 +1,70 @@
+original_work_dir: ${hydra:runtime.cwd}
+data_dir: ${original_work_dir}/data
+print_config: true
+ignore_warnings: true
+train: true
+test: true
+seed: 12345
+name: focusMAE_150
+datamodule:
+  _target_: src.datamodules.focus_datamodule.FocusDataModule
+  data_dir: ${data_dir}/focus150
+  csv_file: ${data_dir}/focus150/metadata.csv
+  batch_size: 128
+  train_val_test_split_percentage:
+  - 0.7
+  - 0.15
+  - 0.15
+  num_workers: 0
+  pin_memory: false
+model:
+  _target_: src.models.focus_module.FocusLitModule
+  input_size: 67500
+  lin1_size: 128
+  lin2_size: 256
+  lin3_size: 64
+  output_size: 1
+  lr: 0.001
+  weight_decay: 0.0005
+callbacks:
+  model_checkpoint:
+    _target_: pytorch_lightning.callbacks.ModelCheckpoint
+    monitor: val/mae
+    mode: min
+    save_top_k: 1
+    save_last: true
+    verbose: false
+    dirpath: checkpoints/
+    filename: epoch_{epoch:03d}
+    auto_insert_metric_name: false
+  early_stopping:
+    _target_: pytorch_lightning.callbacks.EarlyStopping
+    monitor: val/mae
+    mode: min
+    patience: 100
+    min_delta: 0
+  model_summary:
+    _target_: pytorch_lightning.callbacks.RichModelSummary
+    max_depth: -1
+  rich_progress_bar:
+    _target_: pytorch_lightning.callbacks.RichProgressBar
+logger:
+  csv:
+    _target_: pytorch_lightning.loggers.csv_logs.CSVLogger
+    save_dir: .
+    name: csv/
+    prefix: ''
+  tensorboard:
+    _target_: pytorch_lightning.loggers.tensorboard.TensorBoardLogger
+    save_dir: tensorboard/
+    name: null
+    version: ${name}
+    log_graph: false
+    default_hp_metric: true
+    prefix: ''
+trainer:
+  _target_: pytorch_lightning.Trainer
+  gpus: 0
+  min_epochs: 1
+  max_epochs: 100
+  resume_from_checkpoint: null

logs/experiments/runs/focusMAE_150/2022-03-10_13-27-16/.hydra/hydra.yaml

@@ -0,0 +1,171 @@
+hydra:
+  run:
+    dir: logs/experiments/runs/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
+  sweep:
+    dir: logs/experiments/multiruns/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        log_colors:
+          DEBUG: purple
+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra: []
+    task:
+    - trainer.gpus=0
+    - experiment=focusMAE_150
+  job:
+    name: train
+    override_dirname: experiment=focusMAE_150,trainer.gpus=0
+    id: ???
+    num: ???
+    config_name: train.yaml
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.1.1
+    cwd: /usr/src/app
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /usr/src/app/configs
+      schema: file
+      provider: main
+    - path: hydra_plugins.hydra_colorlog.conf
+      schema: pkg
+      provider: hydra-colorlog
+    - path: ''
+      schema: structured
+      provider: schema
+    choices:
+      local: default.yaml
+      hparams_search: null
+      debug: null
+      experiment: focusMAE_150
+      log_dir: default.yaml
+      trainer: default.yaml
+      logger: many_loggers
+      callbacks: default.yaml
+      model: focus150.yaml
+      datamodule: focus150.yaml
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: colorlog
+      hydra/hydra_logging: colorlog
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

logs/experiments/runs/focusMAE_150/2022-03-10_13-27-16/.hydra/overrides.yaml

@@ -0,0 +1,2 @@
+- trainer.gpus=0
+- experiment=focusMAE_150

logs/experiments/runs/focusMAE_150/2022-03-10_13-27-16/csv/version_0/hparams.yaml

@@ -0,0 +1,52 @@
+trainer:
+  _target_: pytorch_lightning.Trainer
+  gpus: 0
+  min_epochs: 1
+  max_epochs: 100
+  resume_from_checkpoint: null
+model:
+  _target_: src.models.focus_module.FocusLitModule
+  input_size: 67500
+  lin1_size: 128
+  lin2_size: 256
+  lin3_size: 64
+  output_size: 1
+  lr: 0.001
+  weight_decay: 0.0005
+datamodule:
+  _target_: src.datamodules.focus_datamodule.FocusDataModule
+  data_dir: /usr/src/app/data/focus150
+  csv_file: /usr/src/app/data/focus150/metadata.csv
+  batch_size: 128
+  train_val_test_split_percentage:
+  - 0.7
+  - 0.15
+  - 0.15
+  num_workers: 0
+  pin_memory: false
+seed: 12345
+callbacks:
+  model_checkpoint:
+    _target_: pytorch_lightning.callbacks.ModelCheckpoint
+    monitor: val/mae
+    mode: min
+    save_top_k: 1
+    save_last: true
+    verbose: false
+    dirpath: checkpoints/
+    filename: epoch_{epoch:03d}
+    auto_insert_metric_name: false
+  early_stopping:
+    _target_: pytorch_lightning.callbacks.EarlyStopping
+    monitor: val/mae
+    mode: min
+    patience: 100
+    min_delta: 0
+  model_summary:
+    _target_: pytorch_lightning.callbacks.RichModelSummary
+    max_depth: -1
+  rich_progress_bar:
+    _target_: pytorch_lightning.callbacks.RichProgressBar
+model/params/total: 8690561
+model/params/trainable: 8690561
+model/params/non_trainable: 0

logs/experiments/runs/focusMAE_150/2022-03-10_13-27-16/csv/version_0/metrics.csv

@@ -0,0 +1,202 @@
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logs/experiments/runs/focusMAE_150/2022-03-10_13-27-16/tensorboard/focusMAE_150/hparams.yaml

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+  gpus: 0
+  min_epochs: 1
+  max_epochs: 100
+  resume_from_checkpoint: null
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+  _target_: src.models.focus_module.FocusLitModule
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+  data_dir: /usr/src/app/data/focus150
+  csv_file: /usr/src/app/data/focus150/metadata.csv
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+    monitor: val/mae
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+  model_summary:
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+    max_depth: -1
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logs/experiments/runs/focusMAE_75/2022-03-10_14-07-57/.hydra/config.yaml

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+original_work_dir: ${hydra:runtime.cwd}
+data_dir: ${original_work_dir}/data
+print_config: true
+ignore_warnings: true
+train: true
+test: true
+seed: 12345
+name: focusMAE_75
+datamodule:
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+  data_dir: ${data_dir}/focus
+  csv_file: ${data_dir}/focus/metadata.csv
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logs/experiments/runs/focusMAE_75/2022-03-10_14-07-57/.hydra/hydra.yaml

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+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
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+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
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+      colorlog:
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+    id: ???
+    num: ???
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+      datamodule: focus.yaml
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logs/experiments/runs/focusMAE_75/2022-03-10_14-07-57/.hydra/overrides.yaml

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+- trainer.gpus=0
+- experiment=focusMAE_75

logs/experiments/runs/focusMAE_75/2022-03-10_14-07-57/csv/version_0/hparams.yaml

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+    max_depth: -1
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logs/experiments/runs/focusMAE_75/2022-03-10_14-07-57/tensorboard/focusMAE_75/hparams.yaml

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+trainer:
+  _target_: pytorch_lightning.Trainer
+  gpus: 0
+  min_epochs: 1
+  max_epochs: 100
+  resume_from_checkpoint: null
+model:
+  _target_: src.models.focus_module.FocusLitModule
+  input_size: 16875
+  lin1_size: 128
+  lin2_size: 256
+  lin3_size: 64
+  output_size: 1
+  lr: 0.001
+  weight_decay: 0.0005
+datamodule:
+  _target_: src.datamodules.focus_datamodule.FocusDataModule
+  data_dir: /usr/src/app/data/focus
+  csv_file: /usr/src/app/data/focus/metadata.csv
+  batch_size: 128
+  train_val_test_split_percentage:
+  - 0.7
+  - 0.15
+  - 0.15
+  num_workers: 0
+  pin_memory: false
+seed: 12345
+callbacks:
+  model_checkpoint:
+    _target_: pytorch_lightning.callbacks.ModelCheckpoint
+    monitor: val/mae
+    mode: min
+    save_top_k: 1
+    save_last: true
+    verbose: false
+    dirpath: checkpoints/
+    filename: epoch_{epoch:03d}
+    auto_insert_metric_name: false
+  early_stopping:
+    _target_: pytorch_lightning.callbacks.EarlyStopping
+    monitor: val/mae
+    mode: min
+    patience: 100
+    min_delta: 0
+  model_summary:
+    _target_: pytorch_lightning.callbacks.RichModelSummary
+    max_depth: -1
+  rich_progress_bar:
+    _target_: pytorch_lightning.callbacks.RichProgressBar
+model/params/total: 2210561
+model/params/trainable: 2210561
+model/params/non_trainable: 0

logs/experiments/runs/focusMSE_150/2022-03-10_13-11-24/.hydra/config.yaml

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+original_work_dir: ${hydra:runtime.cwd}
+data_dir: ${original_work_dir}/data
+print_config: true
+ignore_warnings: true
+train: true
+test: true
+seed: 12345
+name: focusMSE_150
+datamodule:
+  _target_: src.datamodules.focus_datamodule.FocusDataModule
+  data_dir: ${data_dir}/focus150
+  csv_file: ${data_dir}/focus150/metadata.csv
+  batch_size: 128
+  train_val_test_split_percentage:
+  - 0.7
+  - 0.15
+  - 0.15
+  num_workers: 0
+  pin_memory: false
+model:
+  _target_: src.models.focus_module.FocusMSELitModule
+  input_size: 67500
+  lin1_size: 128
+  lin2_size: 256
+  lin3_size: 64
+  output_size: 1
+  lr: 0.001
+  weight_decay: 0.0005
+callbacks:
+  model_checkpoint:
+    _target_: pytorch_lightning.callbacks.ModelCheckpoint
+    monitor: val/mae
+    mode: min
+    save_top_k: 1
+    save_last: true
+    verbose: false
+    dirpath: checkpoints/
+    filename: epoch_{epoch:03d}
+    auto_insert_metric_name: false
+  early_stopping:
+    _target_: pytorch_lightning.callbacks.EarlyStopping
+    monitor: val/mae
+    mode: min
+    patience: 100
+    min_delta: 0
+  model_summary:
+    _target_: pytorch_lightning.callbacks.RichModelSummary
+    max_depth: -1
+  rich_progress_bar:
+    _target_: pytorch_lightning.callbacks.RichProgressBar
+logger:
+  csv:
+    _target_: pytorch_lightning.loggers.csv_logs.CSVLogger
+    save_dir: .
+    name: csv/
+    prefix: ''
+  tensorboard:
+    _target_: pytorch_lightning.loggers.tensorboard.TensorBoardLogger
+    save_dir: tensorboard/
+    name: null
+    version: ${name}
+    log_graph: false
+    default_hp_metric: true
+    prefix: ''
+trainer:
+  _target_: pytorch_lightning.Trainer
+  gpus: 0
+  min_epochs: 1
+  max_epochs: 100
+  resume_from_checkpoint: null

logs/experiments/runs/focusMSE_150/2022-03-10_13-11-24/.hydra/hydra.yaml

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+hydra:
+  run:
+    dir: logs/experiments/runs/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
+  sweep:
+    dir: logs/experiments/multiruns/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        log_colors:
+          DEBUG: purple
+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra: []
+    task:
+    - trainer.gpus=0
+    - experiment=focusMSE_150
+  job:
+    name: train
+    override_dirname: experiment=focusMSE_150,trainer.gpus=0
+    id: ???
+    num: ???
+    config_name: train.yaml
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.1.1
+    cwd: /usr/src/app
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /usr/src/app/configs
+      schema: file
+      provider: main
+    - path: hydra_plugins.hydra_colorlog.conf
+      schema: pkg
+      provider: hydra-colorlog
+    - path: ''
+      schema: structured
+      provider: schema
+    choices:
+      local: default.yaml
+      hparams_search: null
+      debug: null
+      experiment: focusMSE_150
+      log_dir: default.yaml
+      trainer: default.yaml
+      logger: many_loggers
+      callbacks: default.yaml
+      model: focus150.yaml
+      datamodule: focus150.yaml
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: colorlog
+      hydra/hydra_logging: colorlog
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

logs/experiments/runs/focusMSE_150/2022-03-10_13-11-24/.hydra/overrides.yaml

@@ -0,0 +1,2 @@
+- trainer.gpus=0
+- experiment=focusMSE_150

logs/experiments/runs/focusMSE_150/2022-03-10_13-11-24/csv/version_0/hparams.yaml

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+trainer:
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+  gpus: 0
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+  max_epochs: 100
+  resume_from_checkpoint: null
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+  lin2_size: 256
+  lin3_size: 64
+  output_size: 1
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+datamodule:
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+  data_dir: /usr/src/app/data/focus150
+  csv_file: /usr/src/app/data/focus150/metadata.csv
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+  train_val_test_split_percentage:
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+seed: 12345
+callbacks:
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+    monitor: val/mae
+    mode: min
+    save_top_k: 1
+    save_last: true
+    verbose: false
+    dirpath: checkpoints/
+    filename: epoch_{epoch:03d}
+    auto_insert_metric_name: false
+  early_stopping:
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+    monitor: val/mae
+    mode: min
+    patience: 100
+    min_delta: 0
+  model_summary:
+    _target_: pytorch_lightning.callbacks.RichModelSummary
+    max_depth: -1
+  rich_progress_bar:
+    _target_: pytorch_lightning.callbacks.RichProgressBar
+model/params/total: 8690561
+model/params/trainable: 8690561
+model/params/non_trainable: 0

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+  gpus: 0
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+  data_dir: /usr/src/app/data/focus150
+  csv_file: /usr/src/app/data/focus150/metadata.csv
+  batch_size: 128
+  train_val_test_split_percentage:
+  - 0.7
+  - 0.15
+  - 0.15
+  num_workers: 0
+  pin_memory: false
+seed: 12345
+callbacks:
+  model_checkpoint:
+    _target_: pytorch_lightning.callbacks.ModelCheckpoint
+    monitor: val/mae
+    mode: min
+    save_top_k: 1
+    save_last: true
+    verbose: false
+    dirpath: checkpoints/
+    filename: epoch_{epoch:03d}
+    auto_insert_metric_name: false
+  early_stopping:
+    _target_: pytorch_lightning.callbacks.EarlyStopping
+    monitor: val/mae
+    mode: min
+    patience: 100
+    min_delta: 0
+  model_summary:
+    _target_: pytorch_lightning.callbacks.RichModelSummary
+    max_depth: -1
+  rich_progress_bar:
+    _target_: pytorch_lightning.callbacks.RichProgressBar
+model/params/total: 8690561
+model/params/trainable: 8690561
+model/params/non_trainable: 0