| { | |
| "_name_or_path": "TimSchopf/nlp_taxonomy_classifier", | |
| "adapters": { | |
| "adapters": {}, | |
| "config_map": {}, | |
| "fusion_config_map": {}, | |
| "fusions": {} | |
| }, | |
| "architectures": [ | |
| "BertForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "classifier_dropout": null, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "Multilinguality", | |
| "1": "Term Extraction", | |
| "2": "Cognitive Modeling", | |
| "3": "Information Extraction & Text Mining", | |
| "4": "Responsible & Trustworthy NLP", | |
| "5": "Numerical Reasoning", | |
| "6": "Phonology", | |
| "7": "Code-Switching", | |
| "8": "Reasoning", | |
| "9": "Topic Modeling", | |
| "10": "Speech Recognition", | |
| "11": "Natural Language Interfaces", | |
| "12": "Representation Learning", | |
| "13": "Coreference Resolution", | |
| "14": "Dialogue Response Generation", | |
| "15": "Syntactic Text Processing", | |
| "16": "Data-to-Text Generation", | |
| "17": "Ethical NLP", | |
| "18": "Knowledge Representation", | |
| "19": "Cross-Lingual Transfer", | |
| "20": "Visual Data in NLP", | |
| "21": "Text Segmentation", | |
| "22": "Textual Inference", | |
| "23": "Aspect-based Sentiment Analysis", | |
| "24": "Information Retrieval", | |
| "25": "Open Information Extraction", | |
| "26": "Text Error Correction", | |
| "27": "Question Answering", | |
| "28": "Syntactic Parsing", | |
| "29": "Text Clustering", | |
| "30": "Summarization", | |
| "31": "Event Extraction", | |
| "32": "Paraphrasing", | |
| "33": "Polarity Analysis", | |
| "34": "Named Entity Recognition", | |
| "35": "Text Style Transfer", | |
| "36": "Text Classification", | |
| "37": "Machine Reading Comprehension", | |
| "38": "Dialogue Systems & Conversational Agents", | |
| "39": "Captioning", | |
| "40": "Semantic Parsing", | |
| "41": "Semantic Search", | |
| "42": "Text Complexity", | |
| "43": "Chunking", | |
| "44": "Code Generation", | |
| "45": "Typology", | |
| "46": "Fact & Claim Verification", | |
| "47": "Text Generation", | |
| "48": "Linguistics & Cognitive NLP", | |
| "49": "Opinion Mining", | |
| "50": "Structured Data in NLP", | |
| "51": "Machine Translation", | |
| "52": "Language Models", | |
| "53": "Semantic Similarity", | |
| "54": "Knowledge Graph Reasoning", | |
| "55": "Programming Languages in NLP", | |
| "56": "Document Retrieval", | |
| "57": "Linguistic Theories", | |
| "58": "Robustness in NLP", | |
| "59": "Text Normalization", | |
| "60": "Argument Mining", | |
| "61": "Emotion Analysis", | |
| "62": "Commonsense Reasoning", | |
| "63": "Tagging", | |
| "64": "Phonetics", | |
| "65": "Word Sense Disambiguation", | |
| "66": "Passage Retrieval", | |
| "67": "Stylistic Analysis", | |
| "68": "Green & Sustainable NLP", | |
| "69": "Indexing", | |
| "70": "Speech & Audio in NLP", | |
| "71": "Discourse & Pragmatics", | |
| "72": "Semantic Text Processing", | |
| "73": "Morphology", | |
| "74": "Multimodality", | |
| "75": "Relation Extraction", | |
| "76": "Question Generation", | |
| "77": "Psycholinguistics", | |
| "78": "Sentiment Analysis", | |
| "79": "Intent Recognition", | |
| "80": "Low-Resource NLP", | |
| "81": "Explainability & Interpretability in NLP" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "Argument Mining": 60, | |
| "Aspect-based Sentiment Analysis": 23, | |
| "Captioning": 39, | |
| "Chunking": 43, | |
| "Code Generation": 44, | |
| "Code-Switching": 7, | |
| "Cognitive Modeling": 2, | |
| "Commonsense Reasoning": 62, | |
| "Coreference Resolution": 13, | |
| "Cross-Lingual Transfer": 19, | |
| "Data-to-Text Generation": 16, | |
| "Dialogue Response Generation": 14, | |
| "Dialogue Systems & Conversational Agents": 38, | |
| "Discourse & Pragmatics": 71, | |
| "Document Retrieval": 56, | |
| "Emotion Analysis": 61, | |
| "Ethical NLP": 17, | |
| "Event Extraction": 31, | |
| "Explainability & Interpretability in NLP": 81, | |
| "Fact & Claim Verification": 46, | |
| "Green & Sustainable NLP": 68, | |
| "Indexing": 69, | |
| "Information Extraction & Text Mining": 3, | |
| "Information Retrieval": 24, | |
| "Intent Recognition": 79, | |
| "Knowledge Graph Reasoning": 54, | |
| "Knowledge Representation": 18, | |
| "Language Models": 52, | |
| "Linguistic Theories": 57, | |
| "Linguistics & Cognitive NLP": 48, | |
| "Low-Resource NLP": 80, | |
| "Machine Reading Comprehension": 37, | |
| "Machine Translation": 51, | |
| "Morphology": 73, | |
| "Multilinguality": 0, | |
| "Multimodality": 74, | |
| "Named Entity Recognition": 34, | |
| "Natural Language Interfaces": 11, | |
| "Numerical Reasoning": 5, | |
| "Open Information Extraction": 25, | |
| "Opinion Mining": 49, | |
| "Paraphrasing": 32, | |
| "Passage Retrieval": 66, | |
| "Phonetics": 64, | |
| "Phonology": 6, | |
| "Polarity Analysis": 33, | |
| "Programming Languages in NLP": 55, | |
| "Psycholinguistics": 77, | |
| "Question Answering": 27, | |
| "Question Generation": 76, | |
| "Reasoning": 8, | |
| "Relation Extraction": 75, | |
| "Representation Learning": 12, | |
| "Responsible & Trustworthy NLP": 4, | |
| "Robustness in NLP": 58, | |
| "Semantic Parsing": 40, | |
| "Semantic Search": 41, | |
| "Semantic Similarity": 53, | |
| "Semantic Text Processing": 72, | |
| "Sentiment Analysis": 78, | |
| "Speech & Audio in NLP": 70, | |
| "Speech Recognition": 10, | |
| "Structured Data in NLP": 50, | |
| "Stylistic Analysis": 67, | |
| "Summarization": 30, | |
| "Syntactic Parsing": 28, | |
| "Syntactic Text Processing": 15, | |
| "Tagging": 63, | |
| "Term Extraction": 1, | |
| "Text Classification": 36, | |
| "Text Clustering": 29, | |
| "Text Complexity": 42, | |
| "Text Error Correction": 26, | |
| "Text Generation": 47, | |
| "Text Normalization": 59, | |
| "Text Segmentation": 21, | |
| "Text Style Transfer": 35, | |
| "Textual Inference": 22, | |
| "Topic Modeling": 9, | |
| "Typology": 45, | |
| "Visual Data in NLP": 20, | |
| "Word Sense Disambiguation": 65 | |
| }, | |
| "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": "multi_label_classification", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.24.0", | |
| "type_vocab_size": 2, | |
| "use_cache": true, | |
| "vocab_size": 31090 | |
| } | |