Upload preprocessing_kwargs.json

preprocessing_kwargs.json

@@ -1 +1 @@
-{"description": "duplicating qanom training data ", "model_type": "t5", "train_dataset": "joint_qanom", "test_dataset": "qanom", "train_epochs": 5, "fp16": true, "batch_size": 12, "source_prefix": "<predicate-type>", "preprocess_input_func": "input_predicate_marker", "use_bilateral_predicate_marker": true, "overwrite_output_dir": true, "wandb_run_name": "2021-12-16--00:13:35_5ep_t5_joint_qanom_factor=14"}
+{"overwrite_output_dir": true, "predict_with_generate": true, "debug_mode": false, "append_verb_form": true, "use_bilateral_predicate_marker": true, "fp16": true, "load_best_model_at_end": true, "do_eval_on": "validation", "per_device_train_batch_size": 12, "per_device_eval_batch_size": 12, "save_strategy": "steps", "logging_strategy": "steps", "evaluation_strategy": "steps", "logging_steps": 500, "eval_steps": 500, "save_steps": 500, "metric_for_best_model": "eval_loss", "predicate_marker_type": "generic", "description": "optimal joint config from sweep, mainly for qanom", "model_type": "t5", "train_dataset": "joint_qanom", "train_epochs": 20, "qanom_joint_factor": 14, "dir_switch": "joint_optimal", "gradient_accumulation_steps": 14, "learning_rate": 0.001, "dropout_rate": 0.1, "seed": 44, "source_prefix": "parse: ", "preprocess_input_func": "input_predicate_marker", "num_beams": 5}