config.json

{
  "_name_or_path": "bert-base-uncased",
  "architectures": [
    "BertForSequenceClassification"
  ],
  "attention_probs_dropout_prob": 0.1,
  "classifier_dropout": null,
  "gradient_checkpointing": false,
  "hidden_act": "gelu",
  "hidden_dropout_prob": 0.1,
  "hidden_size": 768,
  "id2label": {
    "0": "secrecy rate",
    "1": "markov geographic model",
    "2": "graph convolution networks",
    "3": "convolutional neural network",
    "4": "computed tomography",
    "5": "betweenness centrality",
    "6": "forward error correction",
    "7": "fusion center",
    "8": "random vaccination",
    "9": "adversarial risk analysis",
    "10": "nash equilibrium",
    "11": "maximum likelihood",
    "12": "synthetic aperture radar",
    "13": "sound pressure level",
    "14": "support vector machine",
    "15": "high performance computing",
    "16": "access point",
    "17": "downlink",
    "18": "strictly piecewise",
    "19": "atomic , independent , declarative , and absolute",
    "20": "shortest dependency path",
    "21": "multi - layer same - resolution compressed",
    "22": "marginal contribution",
    "23": "spectral angle distance",
    "24": "information retrieval",
    "25": "resource description framework",
    "26": "atomic function computation",
    "27": "part of speech",
    "28": "long term evolution",
    "29": "mean squared error",
    "30": "permutation invariant training",
    "31": "minimum generation error",
    "32": "alternating least squares",
    "33": "reinforcement learning",
    "34": "machine learning",
    "35": "recurrent neural network",
    "36": "recurrent weighted average",
    "37": "question answering",
    "38": "multiple parallel instances",
    "39": "gaussian process",
    "40": "base station",
    "41": "receiver operating characteristic",
    "42": "threshold algorithm",
    "43": "click through rates",
    "44": "virtual machine",
    "45": "test case prioritization",
    "46": "neural network",
    "47": "belief propagation",
    "48": "contention adaptions",
    "49": "dynamic induction control",
    "50": "information embedding cost",
    "51": "lifelong metric learning",
    "52": "linear programming",
    "53": "multiple description coding",
    "54": "latent dirichlet allocation",
    "55": "collaborative filtering",
    "56": "medium access control",
    "57": "description logics",
    "58": "radio frequency",
    "59": "adaptive radix tree",
    "60": "integer linear programming",
    "61": "minimum risk training",
    "62": "constructive interference",
    "63": "line of sight",
    "64": "deep belief network",
    "65": "average precision",
    "66": "dropped pronoun",
    "67": "rate distortion function",
    "68": "intellectual property",
    "69": "geometric programming",
    "70": "gaussian mixture model",
    "71": "language model",
    "72": "adversarially robust distillation",
    "73": "controlled natural language",
    "74": "federated learning",
    "75": "augmented reality",
    "76": "matrix factorization",
    "77": "principal component analysis",
    "78": "node classification",
    "79": "smart object",
    "80": "poisson point process",
    "81": "attention network",
    "82": "constrained least squares",
    "83": "global positioning system",
    "84": "prepositional phrase",
    "85": "artificial neural network",
    "86": "directed belief net",
    "87": "false positive rate",
    "88": "latent semantic analysis",
    "89": "artificial intelligence",
    "90": "model predictive control",
    "91": "genetic algorithm",
    "92": "access part'",
    "93": "sensing application recently",
    "94": "mutual information",
    "95": "universal dependencies",
    "96": "secrecy outage probability",
    "97": "statistical compressed sensing",
    "98": "information bottleneck",
    "99": "ergodic sum capacity",
    "100": "image signal processor",
    "101": "particle swarm optimization",
    "102": "differential rectifier",
    "103": "technical debt",
    "104": "deep learning",
    "105": "hybrid monte carlo",
    "106": "ordinary differential equation",
    "107": "scalar multiplication",
    "108": "inductive logic programming",
    "109": "simulated annealing",
    "110": "entity set expansion",
    "111": "autism spectrum disorders",
    "112": "artificial bee colony",
    "113": "property graph",
    "114": "centralized solution",
    "115": "social status",
    "116": "taint dependency sequences",
    "117": "expectation maximization",
    "118": "machine translation",
    "119": "dynamic vision sensor",
    "120": "automatic speech recognition",
    "121": "user equipment",
    "122": "random neural networks",
    "123": "mean absolute error",
    "124": "bayesian network",
    "125": "singular value decomposition",
    "126": "multimedia event detection",
    "127": "median recovery error",
    "128": "nearest neighbor",
    "129": "friendly jamming",
    "130": "formal methods",
    "131": "intraclass correlation coefficient",
    "132": "central cloud",
    "133": "cumulative activation",
    "134": "mitral valve",
    "135": "discriminative correlation filter",
    "136": "transformation error",
    "137": "relation extraction",
    "138": "linear discriminant analysis",
    "139": "integrated circuit",
    "140": "stochastic block model",
    "141": "information extraction",
    "142": "socially assistive robots",
    "143": "hierarchical attention network",
    "144": "deep reinforcement learning",
    "145": "logistic regression",
    "146": "message passing interface",
    "147": "bug reports",
    "148": "alzheimer 's disease",
    "149": "data science and analytics",
    "150": "automatic differentiation",
    "151": "conditional random field",
    "152": "false negatives",
    "153": "sequential monte carlo",
    "154": "basic question",
    "155": "physical access",
    "156": "point multiplication",
    "157": "leicester scientific corpus",
    "158": "transformation encoder",
    "159": "deep convolutional neural network",
    "160": "thompson sampling",
    "161": "orthogonal least square",
    "162": "acquaintance vaccination",
    "163": "rate - selective",
    "164": "dynamic assignment ratio",
    "165": "multiple description",
    "166": "million song dataset",
    "167": "machine type communications",
    "168": "self attention network",
    "169": "term frequency",
    "170": "portable document format",
    "171": "parameter server",
    "172": "physical machines",
    "173": "exponential moving average",
    "174": "matrix pair beamformer",
    "175": "optimal transport",
    "176": "finite element method",
    "177": "differential evolution",
    "178": "product - based neural network",
    "179": "mean average conceptual similarity",
    "180": "power splitting",
    "181": "parkinson 's disease",
    "182": "new persian",
    "183": "artifact disentanglement network",
    "184": "statistical machine translation",
    "185": "manifold geometry matching",
    "186": "batch normalization",
    "187": "rank residual constraint",
    "188": "oblivious transfer",
    "189": "positive pointwise mutual information",
    "190": "triad significance profile",
    "191": "reverse classification accuracy",
    "192": "fully connected",
    "193": "corresponding arcs",
    "194": "maximum a posteriori",
    "195": "false positive",
    "196": "certain natural language",
    "197": "strategic dependency",
    "198": "strictly local",
    "199": "internet protocol",
    "200": "foveal tilt effects",
    "201": "dynamic cluster",
    "202": "domain name system",
    "203": "mean average precision",
    "204": "semantic role labeling",
    "205": "recurrent convolution",
    "206": "optical character recognition",
    "207": "charging current",
    "208": "low resolution",
    "209": "power system operations",
    "210": "compressive sensing",
    "211": "optimal power flow",
    "212": "deep context prediction",
    "213": "secondary users",
    "214": "o - d demand estimation",
    "215": "fully convolutional neural network",
    "216": "maximal ratio combining",
    "217": "quantile random forest",
    "218": "adaptive threshold",
    "219": "situation entity",
    "220": "relay station",
    "221": "discrete choice models",
    "222": "random forest",
    "223": "left ventricle",
    "224": "artificial noise"
  },
  "initializer_range": 0.02,
  "intermediate_size": 3072,
  "label2id": {
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    "access point": 16,
    "acquaintance vaccination": 162,
    "adaptive radix tree": 59,
    "adaptive threshold": 218,
    "adversarial risk analysis": 9,
    "adversarially robust distillation": 72,
    "alternating least squares": 32,
    "alzheimer 's disease": 148,
    "artifact disentanglement network": 183,
    "artificial bee colony": 112,
    "artificial intelligence": 89,
    "artificial neural network": 85,
    "artificial noise": 224,
    "atomic , independent , declarative , and absolute": 19,
    "atomic function computation": 26,
    "attention network": 81,
    "augmented reality": 75,
    "autism spectrum disorders": 111,
    "automatic differentiation": 150,
    "automatic speech recognition": 120,
    "average precision": 65,
    "base station": 40,
    "basic question": 154,
    "batch normalization": 186,
    "bayesian network": 124,
    "belief propagation": 47,
    "betweenness centrality": 5,
    "bug reports": 147,
    "central cloud": 132,
    "centralized solution": 114,
    "certain natural language": 196,
    "charging current": 207,
    "click through rates": 43,
    "collaborative filtering": 55,
    "compressive sensing": 210,
    "computed tomography": 4,
    "conditional random field": 151,
    "constrained least squares": 82,
    "constructive interference": 62,
    "contention adaptions": 48,
    "controlled natural language": 73,
    "convolutional neural network": 3,
    "corresponding arcs": 193,
    "cumulative activation": 133,
    "data science and analytics": 149,
    "deep belief network": 64,
    "deep context prediction": 212,
    "deep convolutional neural network": 159,
    "deep learning": 104,
    "deep reinforcement learning": 144,
    "description logics": 57,
    "differential evolution": 177,
    "differential rectifier": 102,
    "directed belief net": 86,
    "discrete choice models": 221,
    "discriminative correlation filter": 135,
    "domain name system": 202,
    "downlink": 17,
    "dropped pronoun": 66,
    "dynamic assignment ratio": 164,
    "dynamic cluster": 201,
    "dynamic induction control": 49,
    "dynamic vision sensor": 119,
    "entity set expansion": 110,
    "ergodic sum capacity": 99,
    "expectation maximization": 117,
    "exponential moving average": 173,
    "false negatives": 152,
    "false positive": 195,
    "false positive rate": 87,
    "federated learning": 74,
    "finite element method": 176,
    "formal methods": 130,
    "forward error correction": 6,
    "foveal tilt effects": 200,
    "friendly jamming": 129,
    "fully connected": 192,
    "fully convolutional neural network": 215,
    "fusion center": 7,
    "gaussian mixture model": 70,
    "gaussian process": 39,
    "genetic algorithm": 91,
    "geometric programming": 69,
    "global positioning system": 83,
    "graph convolution networks": 2,
    "hierarchical attention network": 143,
    "high performance computing": 15,
    "hybrid monte carlo": 105,
    "image signal processor": 100,
    "inductive logic programming": 108,
    "information bottleneck": 98,
    "information embedding cost": 50,
    "information extraction": 141,
    "information retrieval": 24,
    "integer linear programming": 60,
    "integrated circuit": 139,
    "intellectual property": 68,
    "internet protocol": 199,
    "intraclass correlation coefficient": 131,
    "language model": 71,
    "latent dirichlet allocation": 54,
    "latent semantic analysis": 88,
    "left ventricle": 223,
    "leicester scientific corpus": 157,
    "lifelong metric learning": 51,
    "line of sight": 63,
    "linear discriminant analysis": 138,
    "linear programming": 52,
    "logistic regression": 145,
    "long term evolution": 28,
    "low resolution": 208,
    "machine learning": 34,
    "machine translation": 118,
    "machine type communications": 167,
    "manifold geometry matching": 185,
    "marginal contribution": 22,
    "markov geographic model": 1,
    "matrix factorization": 76,
    "matrix pair beamformer": 174,
    "maximal ratio combining": 216,
    "maximum a posteriori": 194,
    "maximum likelihood": 11,
    "mean absolute error": 123,
    "mean average conceptual similarity": 179,
    "mean average precision": 203,
    "mean squared error": 29,
    "median recovery error": 127,
    "medium access control": 56,
    "message passing interface": 146,
    "million song dataset": 166,
    "minimum generation error": 31,
    "minimum risk training": 61,
    "mitral valve": 134,
    "model predictive control": 90,
    "multi - layer same - resolution compressed": 21,
    "multimedia event detection": 126,
    "multiple description": 165,
    "multiple description coding": 53,
    "multiple parallel instances": 38,
    "mutual information": 94,
    "nash equilibrium": 10,
    "nearest neighbor": 128,
    "neural network": 46,
    "new persian": 182,
    "node classification": 78,
    "o - d demand estimation": 214,
    "oblivious transfer": 188,
    "optical character recognition": 206,
    "optimal power flow": 211,
    "optimal transport": 175,
    "ordinary differential equation": 106,
    "orthogonal least square": 161,
    "parameter server": 171,
    "parkinson 's disease": 181,
    "part of speech": 27,
    "particle swarm optimization": 101,
    "permutation invariant training": 30,
    "physical access": 155,
    "physical machines": 172,
    "point multiplication": 156,
    "poisson point process": 80,
    "portable document format": 170,
    "positive pointwise mutual information": 189,
    "power splitting": 180,
    "power system operations": 209,
    "prepositional phrase": 84,
    "principal component analysis": 77,
    "product - based neural network": 178,
    "property graph": 113,
    "quantile random forest": 217,
    "question answering": 37,
    "radio frequency": 58,
    "random forest": 222,
    "random neural networks": 122,
    "random vaccination": 8,
    "rank residual constraint": 187,
    "rate - selective": 163,
    "rate distortion function": 67,
    "receiver operating characteristic": 41,
    "recurrent convolution": 205,
    "recurrent neural network": 35,
    "recurrent weighted average": 36,
    "reinforcement learning": 33,
    "relation extraction": 137,
    "relay station": 220,
    "resource description framework": 25,
    "reverse classification accuracy": 191,
    "scalar multiplication": 107,
    "secondary users": 213,
    "secrecy outage probability": 96,
    "secrecy rate": 0,
    "self attention network": 168,
    "semantic role labeling": 204,
    "sensing application recently": 93,
    "sequential monte carlo": 153,
    "shortest dependency path": 20,
    "simulated annealing": 109,
    "singular value decomposition": 125,
    "situation entity": 219,
    "smart object": 79,
    "social status": 115,
    "socially assistive robots": 142,
    "sound pressure level": 13,
    "spectral angle distance": 23,
    "statistical compressed sensing": 97,
    "statistical machine translation": 184,
    "stochastic block model": 140,
    "strategic dependency": 197,
    "strictly local": 198,
    "strictly piecewise": 18,
    "support vector machine": 14,
    "synthetic aperture radar": 12,
    "taint dependency sequences": 116,
    "technical debt": 103,
    "term frequency": 169,
    "test case prioritization": 45,
    "thompson sampling": 160,
    "threshold algorithm": 42,
    "transformation encoder": 158,
    "transformation error": 136,
    "triad significance profile": 190,
    "universal dependencies": 95,
    "user equipment": 121,
    "virtual machine": 44
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  "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",
  "transformers_version": "4.34.1",
  "type_vocab_size": 2,
  "use_cache": true,
  "vocab_size": 30522
}