pietrolesci
/

t5v1_1-base-mnli

+## Overview
+T5-Base v1.1 model trained to generate hypotheses given a premise and a label. Below the settings used to train it
+```yaml
+Experiment configurations
+├── datasets
+│   └── mnli_train:
+│         dataset_name: multi_nli
+│         dataset_config_name: null
+│         cache_dir: null
+│         input_fields:
+│         - premise
+│         - hypothesis
+│         target_field: label
+│         train_subset_names: null
+│         val_subset_names: validation_matched
+│         test_subset_names: none
+│         train_val_split: null
+│         limit_train_samples: null
+│         limit_val_samples: null
+│         limit_test_samples: null
+│         sampling_kwargs:
+│           sampling_strategy: random
+│           seed: 42
+│           replace: false
+│         align_labels_with_mapping: null
+│         avoid_consistency_check: false
+│         predict_label_mapping: null
+│       mnli:
+│         dataset_name: multi_nli
+│         dataset_config_name: null
+│         cache_dir: null
+│         input_fields:
+│         - premise
+│         - hypothesis
+│         target_field: label
+│         train_subset_names: none
+│         val_subset_names: none
+│         test_subset_names: validation_mismatched
+│         train_val_split: null
+│         limit_train_samples: null
+│         limit_val_samples: null
+│         limit_test_samples: null
+│         sampling_kwargs:
+│           sampling_strategy: random
+│           seed: 42
+│           replace: false
+│         align_labels_with_mapping: null
+│         avoid_consistency_check: false
+│         predict_label_mapping: null
+│
+├── data
+│   └── _target_: src.task.nli.data.NLIGenerationData.from_config
+│       main_dataset_name: null
+│       use_additional_as_test: null
+│       dataloader:
+│         batch_size: 64
+│         eval_batch_size: 100
+│         num_workers: 16
+│         pin_memory: true
+│         drop_last: false
+│         persistent_workers: false
+│         shuffle: true
+│         seed_dataloader: 42
+│         replacement: false
+│       processing:
+│         preprocessing_num_workers: 16
+│         preprocessing_batch_size: 1000
+│         load_from_cache_file: true
+│         padding: longest
+│         truncation: longest_first
+│         max_source_length: 128
+│         max_target_length: 128
+│         template: 'premise: $premise $label hypothesis: '
+│       tokenizer:
+│         _target_: transformers.AutoTokenizer.from_pretrained
+│         pretrained_model_name_or_path: google/t5-v1_1-base
+│         use_fast: true
+│
+├── task
+│   └── optimizer:
+│         name: Adafactor
+│         lr: 0.001
+│         weight_decay: 0.0
+│         no_decay:
+│         - bias
+│         - LayerNorm.weight
+│         decay_rate: -0.8
+│         clip_threshold: 1.0
+│         relative_step: false
+│         scale_parameter: false
+│         warmup_init: false
+│       scheduler:
+│         name: constant_schedule
+│       model:
+│         model_name_or_path: google/t5-v1_1-base
+│       checkpoint_path: null
+│       freeze: false
+│       seed_init_weight: 42
+│       _target_: src.task.nli.NLIGenerationTask.from_config
+│       generation:
+│         max_length: 128
+│         min_length: 3
+│         do_sample: true
+│         early_stopping: false
+│         num_beams: 1
+│         temperature: 1.0
+│         top_k: 50
+│         top_p: 0.95
+│         repetition_penalty: null
+│         length_penalty: null
+│         no_repeat_ngram_size: null
+│         encoder_no_repeat_ngram_size: null
+│         num_return_sequences: 1
+│         max_time: null
+│         max_new_tokens: null
+│         decoder_start_token_id: null
+│         use_cache: null
+│         num_beam_groups: null
+│         diversity_penalty: null
+│
+├── trainer
+│   └── _target_: pytorch_lightning.Trainer
+│       callbacks:
+│         lr_monitor:
+│           _target_: pytorch_lightning.callbacks.LearningRateMonitor
+│           logging_interval: step
+│           log_momentum: false
+│         model_checkpoint:
+│           _target_: pytorch_lightning.callbacks.ModelCheckpoint
+│           dirpath: ./checkpoints/
+│           filename: nli_generator_mnli-epoch={epoch:02d}-val_loss={val/aggregated_loss:.2f}
+│           monitor: val/aggregated_loss
+│           mode: min
+│           verbose: false
+│           save_last: true
+│           save_top_k: 1
+│           auto_insert_metric_name: false
+│           save_on_train_epoch_end: false
+│         rich_model_summary:
+│           _target_: pytorch_lightning.callbacks.RichModelSummary
+│           max_depth: 1
+│         log_grad_norm:
+│           _target_: src.core.callbacks.LogGradNorm
+│           norm_type: 2
+│           group_separator: /
+│           only_total: true
+│           on_step: true
+│           on_epoch: false
+│           prog_bar: true
+│         log_generated_text:
+│           _target_: src.core.callbacks.GenerateAndLogText
+│           dirpath: ./generated_text
+│           type: generated_text
+│           pop_keys_after_logging: true
+│           on_train: false
+│           on_validation: false
+│           on_test: true
+│           log_to_wandb: true
+│         wandb_log_dataset_sizes:
+│           _target_: src.core.callbacks.WandbLogDatasetSizes
+│       logger:
+│         wandb:
+│           _target_: pytorch_lightning.loggers.WandbLogger
+│           project: nli_debiasing
+│           entity: team_brushino
+│           name: nli_generator_mnli
+│           save_dir: ./
+│           offline: false
+│           log_model: false
+│           group: mnli
+│           job_type: generator
+│           tags:
+│           - nli_generator_mnli
+│           - seed=42
+│           - seed_dataloader=42
+│           notes: nli_generator_mnli_time=02-24-53
+│       enable_checkpointing: true
+│       enable_progress_bar: true
+│       enable_model_summary: true
+│       gradient_clip_val: 0.0
+│       gradient_clip_algorithm: null
+│       accelerator: gpu
+│       devices: auto
+│       gpus: null
+│       auto_select_gpus: true
+│       accumulate_grad_batches: 1
+│       max_epochs: 3
+│       min_epochs: 1
+│       max_steps: -1
+│       min_steps: null
+│       max_time: null
+│       num_sanity_val_steps: 2
+│       overfit_batches: 0.0
+│       fast_dev_run: false
+│       limit_train_batches: 1.0
+│       limit_val_batches: 1.0
+│       limit_test_batches: 1.0
+│       profiler: null
+│       detect_anomaly: false
+│       deterministic: false
+│       check_val_every_n_epoch: 1
+│       val_check_interval: 0.1
+│       log_every_n_steps: 10
+│       move_metrics_to_cpu: false
+│
+└── training
+    └── run_val_before_fit: false
+        run_val_after_fit: false
+        run_test_before_fit: false
+        run_test_after_fit: true
+        lr: 0.001
+        seed: 42
+        show_batch: false
+        batch_size: 64
+        eval_batch_size: 100
+        num_workers: 16
+        pin_memory: true
+        drop_last: false
+        persistent_workers: false
+        shuffle: true
+        seed_dataloader: 42
+        ignore_warnings: true
+        experiment_name: nli_generator_mnli
+```