{ "_name_or_path": "microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext", "architectures": [ "BertForSequenceClassification" ], "attention_probs_dropout_prob": 0.1, "classifier_dropout": null, "hidden_act": "gelu", "hidden_dropout_prob": 0.1, "hidden_size": 768, "id2label": { "0": "Not Relevant", "1": "ML Protein Engineering", "2": "Meiosis", "3": "Chromatin", "4": "Microscopy", "5": "ML Code", "6": "Genome Engineering", "7": "Protein Engineering" }, "initializer_range": 0.02, "intermediate_size": 3072, "label2id": { "Chromatin": 3, "Genome Engineering": 6, "ML Code": 5, "ML Protein Engineering": 1, "Meiosis": 2, "Microscopy": 4, "Not Relevant": 0, "Protein Engineering": 7 }, "layer_norm_eps": 1e-12, "max_position_embeddings": 512, "model_type": "bert", "num_attention_heads": 12, "num_hidden_layers": 12, "pad_token_id": 0, "position_embedding_type": "absolute", "problem_type": "single_label_classification", "torch_dtype": "float32", "transformers_version": "4.44.2", "type_vocab_size": 2, "use_cache": true, "vocab_size": 30522 }