First version of pubmed-based model for doing e2e temporal ie.
Browse files- added_tokens.json +1 -0
- config.json +114 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +1 -0
- tokenizer.json +0 -0
- tokenizer_config.json +1 -0
- vocab.txt +0 -0
added_tokens.json
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{"</e>": 28896, "<neg>": 28902, "<cr>": 28901, "</a1>": 28898, "<a1>": 28897, "<e>": 28895, "<a2>": 28899, "</a2>": 28900}
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config.json
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{
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"architectures": [
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"CnlpModelForClassification"
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],
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"encoder_config": {
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"_name_or_path": "microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract",
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"add_cross_attention": false,
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"architectures": [
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"BertForMaskedLM"
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],
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"attention_probs_dropout_prob": 0.1,
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"bad_words_ids": null,
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"bos_token_id": null,
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"chunk_size_feed_forward": 0,
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"classifier_dropout": null,
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"cross_attention_hidden_size": null,
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"decoder_start_token_id": null,
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"diversity_penalty": 0.0,
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"do_sample": false,
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"early_stopping": false,
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"encoder_no_repeat_ngram_size": 0,
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"eos_token_id": null,
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"finetuning_task": null,
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"forced_bos_token_id": null,
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"forced_eos_token_id": null,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "LABEL_0",
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"1": "LABEL_1"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"is_decoder": false,
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"is_encoder_decoder": false,
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"label2id": {
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"LABEL_0": 0,
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"LABEL_1": 1
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},
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"layer_norm_eps": 1e-12,
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"length_penalty": 1.0,
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"max_length": 20,
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"max_position_embeddings": 512,
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"min_length": 0,
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"model_type": "bert",
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"no_repeat_ngram_size": 0,
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"num_attention_heads": 12,
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"num_beam_groups": 1,
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"num_beams": 1,
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"num_hidden_layers": 12,
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"num_return_sequences": 1,
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"output_attentions": false,
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"output_hidden_states": false,
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"output_scores": false,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"prefix": null,
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"problem_type": null,
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"pruned_heads": {},
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"remove_invalid_values": false,
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"repetition_penalty": 1.0,
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"return_dict": true,
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"return_dict_in_generate": false,
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"sep_token_id": null,
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"task_specific_params": null,
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"temperature": 1.0,
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"tie_encoder_decoder": false,
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"tie_word_embeddings": true,
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"tokenizer_class": null,
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"top_k": 50,
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"top_p": 1.0,
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"torch_dtype": null,
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"torchscript": false,
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"transformers_version": "4.15.0",
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"type_vocab_size": 2,
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"use_bfloat16": false,
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"use_cache": true,
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"vocab_size": 28903
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},
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"encoder_name": "microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract",
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"finetuning_task": [
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"timex",
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"event",
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"tlink-sent"
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],
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"layer": 11,
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"model_type": "cnlpt",
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"num_labels_list": [
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17,
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9,
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2
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],
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"num_rel_attention_heads": 256,
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"num_tokens": -1,
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"rel_attention_head_dims": 64,
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"relations": [
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false,
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false,
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true
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],
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"tagger": [
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true,
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true,
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false
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],
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"tokens": false,
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"torch_dtype": "float32",
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"transformers_version": "4.15.0",
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"use_prior_tasks": false,
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"vocab_size": 28903
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}
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pytorch_model.bin
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:85c4f832882fc7e563ca7be6885d525bf3db846dca9e8149d638862c3c1ac21c
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size 538615407
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special_tokens_map.json
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{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "additional_special_tokens": ["<e>", "</e>", "<a1>", "</a1>", "<a2>", "</a2>", "<cr>", "<neg>"]}
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tokenizer.json
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tokenizer_config.json
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{"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "add_prefix_space": true, "additional_special_tokens": ["<e>", "</e>", "<a1>", "</a1>", "<a2>", "</a2>", "<cr>", "<neg>"], "special_tokens_map_file": null, "name_or_path": "microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract", "do_basic_tokenize": true, "never_split": null, "tokenizer_class": "BertTokenizer"}
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vocab.txt
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The diff for this file is too large to render.
See raw diff
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