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long-coref

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long-coref
File size: 4,090 Bytes 
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{
    "dataset_reader": {
        "type": "coref",
        "max_sentences": 110,
        "max_span_width": 30,
        "token_indexers": {
            "tokens": {
                "type": "pretrained_transformer_mismatched",
                "max_length": 512,
                "model_name": "SpanBERT/spanbert-large-cased"
            }
        }
    },
    "model": {
        "type": "coref",
        "antecedent_feedforward": {
            "activations": "relu",
            "dropout": 0.3,
            "hidden_dims": 1500,
            "input_dim": 9296,
            "num_layers": 2
        },
        "coarse_to_fine": true,
        "context_layer": {
            "type": "pass_through",
            "input_dim": 1024
        },
        "feature_size": 20,
        "inference_order": 2,
        "initializer": {
            "regexes": [
                [
                    ".*_span_updating_gated_sum.*weight",
                    {
                        "type": "xavier_normal"
                    }
                ],
                [
                    ".*linear_layers.*weight",
                    {
                        "type": "xavier_normal"
                    }
                ],
                [
                    ".*scorer.*weight",
                    {
                        "type": "xavier_normal"
                    }
                ],
                [
                    "_distance_embedding.weight",
                    {
                        "type": "xavier_normal"
                    }
                ],
                [
                    "_span_width_embedding.weight",
                    {
                        "type": "xavier_normal"
                    }
                ],
                [
                    "_context_layer._module.weight_ih.*",
                    {
                        "type": "xavier_normal"
                    }
                ],
                [
                    "_context_layer._module.weight_hh.*",
                    {
                        "type": "orthogonal"
                    }
                ]
            ]
        },
        "max_antecedents": 50,
        "max_span_width": 30,
        "mention_feedforward": {
            "activations": "relu",
            "dropout": 0.3,
            "hidden_dims": 1500,
            "input_dim": 3092,
            "num_layers": 2
        },
        "spans_per_word": 0.4,
        "text_field_embedder": {
            "token_embedders": {
                "tokens": {
                    "type": "pretrained_transformer_mismatched",
                    "max_length": 512,
                    "model_name": "SpanBERT/spanbert-large-cased"
                }
            }
        }
    },
    "train_data_path": "/home/dirkg/tank/data/conll12/train.english.v4_gold_conll",
    "validation_data_path": "/home/dirkg/tank/data/conll12/dev.english.v4_gold_conll",
    "test_data_path": "/home/dirkg/tank/data/conll12/test.english.v4_gold_conll",
    "trainer": {
        "learning_rate_scheduler": {
            "type": "slanted_triangular",
            "cut_frac": 0.06
        },
        "num_epochs": 40,
        "optimizer": {
            "type": "huggingface_adamw",
            "lr": 0.0003,
            "parameter_groups": [
                [
                    [
                        ".*transformer.*"
                    ],
                    {
                        "lr": 1e-05
                    }
                ]
            ]
        },
        "patience": 10,
        "validation_metric": "+coref_f1"
    },
    "data_loader": {
        "batch_sampler": {
            "type": "bucket",
            "batch_size": 1,
            "sorting_keys": [
                "text"
            ]
        }
    },
    "validation_dataset_reader": {
        "type": "coref",
        "max_span_width": 30,
        "token_indexers": {
            "tokens": {
                "type": "pretrained_transformer_mismatched",
                "max_length": 512,
                "model_name": "SpanBERT/spanbert-large-cased"
            }
        }
    }
}