[2024-02-28 14:37:17,121][hydra][INFO] - 
estimator:
  accelerator: gpu
  precision: bf16-true
  deterministic: true
  tf32_mode: high
  convert_to_bettertransformer: false
callbacks:
  timer:
    _target_: energizer.active_learning.callbacks.Timer
  lr_monitor:
    _target_: energizer.callbacks.lr_monitor.LearningRateMonitor
  model_checkpoint:
    _target_: energizer.callbacks.model_checkpoint.ModelCheckpoint
    dirpath: .checkpoints
    stage: train
    frequency: 1:epoch
loggers:
  tensorboard:
    _target_: energizer.loggers.TensorBoardLogger
    root_dir: ./
    name: tb_logs
    version: null
data:
  batch_size: 32
  eval_batch_size: 128
  shuffle: true
  replacement: false
  data_seed: 42
  drop_last: false
  num_workers: 8
  pin_memory: true
  persistent_workers: false
  multiprocessing_context: null
  max_length: 512
fit:
  max_epochs: 20
  optimizer_kwargs:
    name: adamw
    lr: 3.0e-05
    init_kwargs:
      fused: true
  scheduler_kwargs:
    name: constant_schedule_with_warmup
    num_warmup_steps: 2000
  log_interval: 100
  enable_progress_bar: true
  limit_train_batches: null
  limit_validation_batches: null
model:
  name: bert-base-uncased
  revision: null
  seed: 42
log_interval: 100
enable_progress_bar: true
limit_batches: null
seed: 42
experiment_group: training
run_name: bert-base-uncased_2024-02-28T14-37-16
data_path: /home/pl487/coreset-project/data/processed
dataset: mnli

======================================================================
[2024-02-28 14:37:17,122][hydra][INFO] - Seed enabled: 42
[2024-02-28 14:37:17,496][hydra][INFO] - Label distribution:
{<RunningStage.TRAIN: 'train'>: {'0-(entailment)': 130899, '1-(neutral)': 130900, '2-(contradiction)': 130903}}
[2024-02-28 14:37:20,088][hydra][INFO] - Loggers: [<energizer.loggers.tensorboard.TensorBoardLogger object at 0x7efde1ce9ea0>]
[2024-02-28 14:37:20,088][hydra][INFO] - Callbacks: [<energizer.active_learning.callbacks.Timer object at 0x7efde11b6770>, <energizer.callbacks.lr_monitor.LearningRateMonitor object at 0x7efde11b67d0>, <energizer.callbacks.model_checkpoint.ModelCheckpoint object at 0x7efde11b5cf0>]
[2024-02-28 14:37:20,091][hydra][INFO] - Model summary:
Total num params: 109.5M
Of which trainable: 109.5M
With a memory footprint of 0.22GB
Total memory allocated 0.68GB
[2024-02-28 14:37:20,092][hydra][INFO] - Dataloading params:
SequenceClassificationDataloaderArgs(batch_size=32, eval_batch_size=128, num_workers=8, pin_memory=True, drop_last=False, persistent_workers=False, shuffle=True, replacement=False, data_seed=42, multiprocessing_context=None, max_length=512)
[2024-02-28 14:37:20,095][hydra][INFO] - Batch:
{<InputKeys.INPUT_IDS: 'input_ids'>: tensor([[  101, 17842,   102,  5368,   102]]), <InputKeys.ATT_MASK: 'attention_mask'>: tensor([[1, 1, 1, 1, 1]]), <InputKeys.LABELS: 'labels'>: tensor([0]), <InputKeys.ON_CPU: 'on_cpu'>: {<SpecialKeys.ID: 'uid'>: [278780]}}