niharikavats2397
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Browse filesThis is a Pfieffer adapter model for NER, trained on beth, partners and all data available in n2c2 dataset (previously i2b2). The name of head is 'ner' and can be loaded as per instruction in readme file.
- adapter_config.json +40 -0
- head_config.json +24 -0
- pytorch_adapter.bin +3 -0
- pytorch_model_head.bin +3 -0
adapter_config.json
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{
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"config": {
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"adapter_residual_before_ln": false,
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"cross_adapter": false,
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"factorized_phm_W": true,
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"factorized_phm_rule": false,
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"hypercomplex_nonlinearity": "glorot-uniform",
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"init_weights": "bert",
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"inv_adapter": null,
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"inv_adapter_reduction_factor": null,
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"is_parallel": false,
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"learn_phm": true,
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"leave_out": [],
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"ln_after": false,
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"ln_before": false,
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"mh_adapter": false,
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"non_linearity": "relu",
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"original_ln_after": true,
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"original_ln_before": true,
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"output_adapter": true,
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"phm_bias": true,
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"phm_c_init": "normal",
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"phm_dim": 4,
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"phm_init_range": 0.0001,
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"phm_layer": false,
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"phm_rank": 1,
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"reduction_factor": 2,
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"residual_before_ln": true,
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"scaling": 1.0,
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"shared_W_phm": false,
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"shared_phm_rule": true,
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"use_gating": false
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},
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"hidden_size": 768,
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"model_class": "BertAdapterModel",
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"model_name": "bert-base-uncased",
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"model_type": "bert",
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"name": "ner",
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"version": "0.1.0"
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}
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head_config.json
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{
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"config": {
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"activation_function": "tanh",
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"dropout_prob": null,
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"head_type": "tagging",
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"label2id": {
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"B-problem": 3,
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"B-test": 1,
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"B-treatment": 5,
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"I-problem": 4,
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"I-test": 2,
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"I-treatment": 6,
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"O": 0
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},
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"layers": 1,
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"num_labels": 7
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},
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"hidden_size": 768,
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"model_class": "BertAdapterModel",
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"model_name": "bert-base-uncased",
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"model_type": "bert",
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"name": "ner",
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"version": "0.1.0"
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}
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pytorch_adapter.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:37bd8c79c709565e71cbdc5abcaed47d4039652f73c03b3c36ac8ddd09ea8330
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size 28384166
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pytorch_model_head.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:2adcf9288356c020ccf1579f47d400ddb2c67d4e7f7faba3b9fa849d8f3b123e
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size 23066
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