EXP_NAME: "semsup_descs_100ep_newds_cosine" EXP_DESC: "SemSup Descriptions ran for 100 epochs" DATA: task_name: eurlex57k dataset_name: eurlex dataset_config_name: null max_seq_length: 512 overwrite_output_dir: true overwrite_cache: false pad_to_max_length: true load_from_local: true max_train_samples: null max_eval_samples: null max_predict_samples: null # train_file: ../training/datasets/eurlex4.3k/train_hr.jsonl # train_file: ../training/datasets/eurlex4.3k/train.jsonl # validation_file: ../training/datasets/eurlex4.3k/test_unseen.jsonl # test_file: ../training/datasets/eurlex4.3k/test_unseen.jsonl # validation_file: ../training/datasets/eurlex4.3k/test.jsonl # test_file: ../training/datasets/eurlex4.3k/test.jsonl train_file: ../training/datasets/eurlex4.3k/train_split1057_1000highfreq.jsonl validation_file: ../training/datasets/eurlex4.3k/test_unseen_split1057.jsonl test_file: ../training/datasets/eurlex4.3k/test_unseen_split1057.jsonl # validation_file: ../training/datasets/eurlex4.3k/test_unseen_hr.jsonl # test_file: ../training/datasets/eurlex4.3k/test_unseen_hr.jsonl label_max_seq_length: 96 descriptions_file: ../training/datasets/eurlex4.3k/heir_withdescriptions_4.3k_v1.json # descriptions_file: ../training/datasets/eurlex4.3k/heir_descriptions_4.3k_v1.json # descriptions_file: ../training/datasets/eurlex4.3k/curie_descriptions_4.3k_v1.json all_labels : ../training/datasets/eurlex4.3k/all_labels.txt test_labels: ../training/datasets/eurlex4.3k/unseen_labels_split1057.txt # test_labels: ../training/datasets/eurlex4.3k/unseen_labels.txt max_descs_per_label: 5 # contrastive_learning_samples: 1500 # cl_min_positive_descs: 1 # bm_short_file: ../training/datasets/eurlex4.3k/train_bmshort.txt MODEL: model_name_or_path: bert-base-uncased config_name: null tokenizer_name: null cache_dir: null use_fast_tokenizer: true model_revision: main use_auth_token: false ignore_mismatched_sizes: false negative_sampling: "none" semsup: true # label_model_name_or_path: prajjwal1/bert-small label_model_name_or_path: bert-base-uncased # label_model_name_or_path: prajjwal1/bert-tiny encoder_model_type: bert use_custom_optimizer: adamw output_learning_rate: 1.e-4 arch_type : 2 add_label_name: false normalize_embeddings: false tie_weights: true coil: true # use_precomputed_embeddings: ../training/datasets/eurlex4.3k/heir_withdescriptions_4.3k_v1_embs_bert_9_96.npy token_dim: 16 num_frozen_layers: 9 TRAINING: do_train: true do_eval: true per_device_train_batch_size: 1 gradient_accumulation_steps: 4 per_device_eval_batch_size: 1 learning_rate: 5.e-5 # Will point to input encoder lr, if user_custom_optimizer is False num_train_epochs: 10 save_steps: 10000 evaluation_strategy: steps eval_steps: 500 fp16: true fp16_opt_level: O1 lr_scheduler_type: "linear" # defaults to 'linear' dataloader_num_workers: 8 label_names: [labels] scenario: "unseen_labels" ddp_find_unused_parameters: false