| from transformers import PretrainedConfig | |
| from typing import List, Dict | |
| class ESGifyConfig(PretrainedConfig): | |
| model_type = "mpnet" | |
| def __init__( | |
| self, | |
| attention_probs_dropout_prob: float = 0.1, | |
| bos_token_id: int = 0, | |
| eos_token_id: int = 2, | |
| hidden_act: str = "gelu", | |
| hidden_dropout_prob: float = 0.1, | |
| hidden_size: int = 768, | |
| initializer_range: float = 0.02, | |
| intermediate_size: int = 3072, | |
| layer_norm_eps: float = 1e-05, | |
| max_position_embeddings: int = 514, | |
| num_attention_heads: int = 12, | |
| num_hidden_layers: int = 12, | |
| output_attentions: bool = True, | |
| pad_token_id: int = 1, | |
| relative_attention_num_buckets: int = 32, | |
| vocab_size: int = 30531, | |
| id2label: Dict = {"0": "Legal Proceedings & Law Violations", | |
| "1": "Biodiversity", | |
| "2": "Communities Health and Safety", | |
| "3": "Land Acquisition and Resettlement (S)", | |
| "4": "Emergencies (Social)", | |
| "5": "Corporate Governance", | |
| "6": "Responsible Investment & Greenwashing", | |
| "7": "Not Relevant to ESG", | |
| "8": "Economic Crime", | |
| "9": "Emergencies (Environmental)", | |
| "10": "Hazardous Materials Management", | |
| "11": "Environmental Management", | |
| "12": "Landscape Transformation", | |
| "13": "Human Rights", | |
| "14": "Climate Risks", | |
| "15": "Labor Relations Management", | |
| "16": "Freedom of Association and Right to Organise", | |
| "17": "Employee Health and Safety", | |
| "18": "Surface Water Pollution", | |
| "19": "Animal Welfare", | |
| "20": "Water Consumption", | |
| "21": "Disclosure", | |
| "22": "Product Safety and Quality", | |
| "23": "Greenhouse Gas Emissions", | |
| "24": "Indigenous People", | |
| "25": "Cultural Heritage", | |
| "26": "Air Pollution", | |
| "27": "Waste Management", | |
| "28": "Soil and Groundwater Impact", | |
| "29": "Forced Labour", | |
| "30": "Wastewater Management", | |
| "31": "Natural Resources", | |
| "32": "Physical Impacts", | |
| "33": "Values and Ethics", | |
| "34": "Risk Management and Internal Control", | |
| "35": "Supply Chain (Environmental)", | |
| "36": "Supply Chain (Social)", | |
| "37": "Discrimination", | |
| "38": "Minimum Age and Child Labour", | |
| "39": "Planning Limitations", | |
| "40": "Data Safety", | |
| "41": "Strategy Implementation", | |
| "42": "Energy Efficiency and Renewables", | |
| "43": "Land Acquisition and Resettlement (E)", | |
| "44": "Supply Chain (Economic / Governance)", | |
| "45": "Land Rehabilitation", | |
| "46": "Retrenchment" | |
| }, | |
| label2id: Dict = {"Legal Proceedings & Law Violations": "0", | |
| "Biodiversity": "1", | |
| "Communities Health and Safety": "2", | |
| "Land Acquisition and Resettlement (S)": "3", | |
| "Emergencies (Social)": "4", | |
| "Corporate Governance": "5", | |
| "Responsible Investment & Greenwashing": "6", | |
| "Not Relevant to ESG": "7", | |
| "Economic Crime": "8", | |
| "Emergencies (Environmental)": "9", | |
| "Hazardous Materials Management": "10", | |
| "Environmental Management": "11", | |
| "Landscape Transformation": "12", | |
| "Human Rights": "13", | |
| "Climate Risks": "14", | |
| "Labor Relations Management": "15", | |
| "Freedom of Association and Right to Organise": "16", | |
| "Employee Health and Safety": "17", | |
| "Surface Water Pollution": "18", | |
| "Animal Welfare": "19", | |
| "Water Consumption": "20", | |
| "Disclosure": "21", | |
| "Product Safety and Quality": "22", | |
| "Greenhouse Gas Emissions": "23", | |
| "Indigenous People": "24", | |
| "Cultural Heritage": "25", | |
| "Air Pollution": "26", | |
| "Waste Management": "27", | |
| "Soil and Groundwater Impact": "28", | |
| "Forced Labour": "29", | |
| "Wastewater Management": "30", | |
| "Natural Resources": "31", | |
| "Physical Impacts": "32", | |
| "Values and Ethics": "33", | |
| "Risk Management and Internal Control": "34", | |
| "Supply Chain (Environmental)": "35", | |
| "Supply Chain (Social)": "36", | |
| "Discrimination": "37", | |
| "Minimum Age and Child Labour": "38", | |
| "Planning Limitations": "39", | |
| "Data Safety": "40", | |
| "Strategy Implementation": "41", | |
| "Energy Efficiency and Renewables": "42", | |
| "Land Acquisition and Resettlement (E)": "43", | |
| "Supply Chain (Economic / Governance)": "44", | |
| "Land Rehabilitation": "45", | |
| "Retrenchment": "46"}, | |
| **kwargs, | |
| ): | |
| self.attention_probs_dropout_prob = attention_probs_dropout_prob | |
| self.bos_token_id = bos_token_id, | |
| self.eos_token_id = eos_token_id, | |
| self.hidden_act = hidden_act, | |
| self.hidden_dropout_prob = hidden_dropout_prob, | |
| self.hidden_size = hidden_size, | |
| self.initializer_range = initializer_range, | |
| self.intermediate_size = intermediate_size, | |
| self.layer_norm_eps = layer_norm_eps | |
| self.max_position_embeddings = max_position_embeddings, | |
| self.num_attention_heads = num_attention_heads, | |
| self.num_hidden_layers = num_hidden_layers, | |
| self.output_attentions = output_attentions, | |
| self.pad_token_id = pad_token_id, | |
| self.relative_attention_num_buckets = relative_attention_num_buckets, | |
| self.vocab_size = vocab_size, | |
| self.id2label = id2label, | |
| self.label2id = label2id | |
| super().__init__(**kwargs) |