cciboglu/bothspeech_detection_bert_pytorch_2.implementation

1{
2  "_name_or_path": "google-bert/bert-base-uncased",
3  "architectures": [
4    "BertForSequenceClassification"
5  ],
6  "attention_probs_dropout_prob": 0.1,
7  "classifier_dropout": null,
8  "gradient_checkpointing": false,
9  "hidden_act": "gelu",
10  "hidden_dropout_prob": 0.1,
11  "hidden_size": 768,
12  "id2label": {
13    "0": "NEGATIVE",
14    "1": "POSITIVE"
15  },
16  "initializer_range": 0.02,
17  "intermediate_size": 3072,
18  "label2id": {
19    "NEGATIVE": 0,
20    "POSITIVE": 1
21  },
22  "layer_norm_eps": 1e-12,
23  "max_position_embeddings": 512,
24  "model_type": "bert",
25  "num_attention_heads": 12,
26  "num_hidden_layers": 12,
27  "pad_token_id": 0,
28  "position_embedding_type": "absolute",
29  "problem_type": "single_label_classification",
30  "torch_dtype": "float32",
31  "transformers_version": "4.47.1",
32  "type_vocab_size": 2,
33  "use_cache": true,
34  "vocab_size": 30522
35}
36