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[2023-12-06 22:55:27,054][hydra][INFO] - |
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estimator: |
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accelerator: gpu |
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precision: 32 |
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deterministic: true |
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tf32_mode: high |
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callbacks: |
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timer: |
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_target_: energizer.active_learning.callbacks.Timer |
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save_outputs: |
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_target_: src.callbacks.SaveOutputs |
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dirpath: ./logs/ |
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instance_level: false |
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batch_level: false |
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epoch_level: false |
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early_stopping: |
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_target_: energizer.callbacks.early_stopping.EarlyStopping |
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monitor: train/avg_f1_minclass |
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stage: train |
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interval: epoch |
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mode: max |
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min_delta: 1.0e-05 |
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patience: 10 |
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stopping_threshold: null |
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divergence_threshold: null |
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verbose: true |
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model_checkpoint: |
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_target_: energizer.callbacks.model_checkpoint.ModelCheckpoint |
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dirpath: .checkpoints |
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monitor: train/avg_f1_minclass |
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stage: train |
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mode: max |
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save_last: false |
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save_top_k: 1 |
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verbose: true |
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loggers: |
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tensorboard: |
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_target_: energizer.loggers.TensorBoardLogger |
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root_dir: ./ |
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name: tb_logs |
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version: null |
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data: |
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batch_size: 32 |
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eval_batch_size: 256 |
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num_workers: 32 |
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pin_memory: true |
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drop_last: false |
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persistent_workers: true |
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shuffle: true |
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seed: 123456 |
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replacement: false |
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max_length: 512 |
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active_data: |
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budget: 100 |
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positive_budget: 5 |
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seed: 123456 |
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fit: |
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min_steps: 100 |
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max_epochs: 10 |
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learning_rate: 4.0e-05 |
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optimizer: adamw |
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log_interval: 1 |
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enable_progress_bar: false |
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limit_train_batches: null |
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limit_validation_batches: null |
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active_fit: |
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max_budget: 5000 |
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query_size: 25 |
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reinit_model: true |
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limit_pool_batches: null |
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limit_test_batches: null |
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test: |
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log_interval: 1 |
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enable_progress_bar: false |
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limit_batches: null |
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strategy: |
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name: randomsubset_entropy |
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args: |
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seed: 42 |
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subpool_size: 10000 |
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model: |
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name: deberta_v3-base |
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seed: 654321 |
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dataset: |
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name: agnews-business-.01 |
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text_column: text |
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label_column: labels |
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uid_column: uid |
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prepared_path: /rds/user/pl487/hpc-work/anchoral/data/prepared/agnews-business-.01 |
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processed_path: /rds/user/pl487/hpc-work/anchoral/data/processed/agnews |
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minority_classes: |
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- 1 |
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index_metric: all-mpnet-base-v2_cosine |
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log_interval: 1 |
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enable_progress_bar: false |
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limit_batches: null |
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seed: 42 |
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experiment_group: deberta_v3-base/new |
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run_name: agnews-business-.01/deberta_v3-base_randomsubset_entropy_2023-12-06T10-52-24 |
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data_path: /rds/user/pl487/hpc-work/anchoral/data |
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|
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====================================================================== |
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[2023-12-06 22:55:27,061][hydra][INFO] - Running active learning with strategy {'name': 'randomsubset_entropy', 'args': {'seed': 42, 'subpool_size': 10000}} |
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[2023-12-06 22:55:27,066][hydra][INFO] - Seed enabled: 42 |
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[2023-12-06 22:55:28,031][hydra][INFO] - Labelled size: 100 Pool size: 90810 Test size: 7600 |
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Label distribution: |
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| | labels | count | perc | |
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|---:|:---------|--------:|-------:| |
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| 0 | Negative | 95 | 0.95 | |
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| 1 | Positive | 5 | 0.05 | |
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[2023-12-06 22:55:28,047][hydra][INFO] - Batch: |
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{<InputKeys.INPUT_IDS: 'input_ids'>: tensor([[ 1, 1864, 294, 41142, 2729, 2152, 19979, 53884, 5147, 1050, |
|
279, 7439, 2298, 927, 7710, 70907, 2]]), <InputKeys.ATT_MASK: 'attention_mask'>: tensor([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]), <InputKeys.LABELS: 'labels'>: tensor([0]), <InputKeys.ON_CPU: 'on_cpu'>: {<SpecialKeys.ID: 'uid'>: [122709]}} |
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[2023-12-06 22:55:29,725][hydra][INFO] - Loggers: {'tensorboard': <energizer.loggers.tensorboard.TensorBoardLogger object at 0x14a30c192220>} |
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[2023-12-06 22:55:29,725][hydra][INFO] - Callbacks: {'timer': <energizer.active_learning.callbacks.Timer object at 0x14a30c2a2610>, 'save_outputs': <src.callbacks.SaveOutputs object at 0x14a306a5f130>, 'early_stopping': <energizer.callbacks.early_stopping.EarlyStopping object at 0x14a30c22c520>, 'model_checkpoint': <energizer.callbacks.model_checkpoint.ModelCheckpoint object at 0x14a30c22c760>} |
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[2023-12-06 22:55:29,748][hydra][INFO] - |
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| Name | Type | Params |
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---------------------------------------------- |
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0 | deberta | DebertaV2Model | 183 M |
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1 | pooler | ContextPooler | 590 K |
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2 | classifier | Linear | 1.5 K |
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3 | dropout | StableDropout | 0 |
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---------------------------------------------- |
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184 M Trainable params |
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0 Non-trainable params |
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184 M Total params |
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737.695 Total estimated model params size (MB) |
|
0.00 GB CUDA Memory used |
|
[2023-12-07 04:52:47,054][submitit][INFO] - Job has timed out. Ran 357 minutes out of requested 360 minutes. |
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[2023-12-07 04:52:47,085][submitit][WARNING] - Caught signal SIGUSR2 on gpu-q-77: this job is timed-out. |
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[2023-12-07 04:52:47,118][submitit][INFO] - Calling checkpoint method. |
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[2023-12-07 04:52:47,150][submitit][INFO] - Job not requeued because: timed-out too many times. |
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[2023-12-07 04:52:47,150][submitit][WARNING] - Bypassing signal SIGCONT |
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[2023-12-07 04:52:47,154][submitit][INFO] - Job completed successfully |
|
|