config.json

{
  "_name_or_path": "microsoft/Multilingual-MiniLM-L12-H384",
  "architectures": [
    "BertForSequenceClassification"
  ],
  "attention_probs_dropout_prob": 0.1,
  "classifier_dropout": null,
  "hidden_act": "gelu",
  "hidden_dropout_prob": 0.1,
  "hidden_size": 384,
  "id2label": {
    "0": "buy_coin",
    "1": "sell_coin",
    "2": "current_coin_price",
    "3": "predict_signal",
    "4": "check_human",
    "5": "affirm",
    "6": "deny",
    "7": "goodbye",
    "8": "greet",
    "9": "inform",
    "10": "thankyou",
    "11": "help",
    "12": "human_handoff",
    "13": "out_of_scope",
    "14": "check_image"
  },
  "initializer_range": 0.02,
  "intermediate_size": 1536,
  "label2id": {
    "affirm": 5,
    "buy_coin": 0,
    "check_human": 4,
    "check_image": 14,
    "current_coin_price": 2,
    "deny": 6,
    "goodbye": 7,
    "greet": 8,
    "help": 11,
    "human_handoff": 12,
    "inform": 9,
    "out_of_scope": 13,
    "predict_signal": 3,
    "sell_coin": 1,
    "thankyou": 10
  },
  "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",
  "tokenizer_class": "XLMRobertaTokenizer",
  "torch_dtype": "float32",
  "transformers_version": "4.40.2",
  "type_vocab_size": 2,
  "use_cache": true,
  "vocab_size": 250037
}