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.gitattributes

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-*.pt filter=lfs diff=lfs merge=lfs -text
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Bert_Bahasa_Sentiment

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+Subproject commit a3888e36909329469565a9c26a07e3d32e29d8f4

README.md

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-from transformers import AutoTokenizer, AutoModelForSequenceClassification
-
-tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
-
-model = AutoModelForSequenceClassification.from_pretrained('techthiyanes/Bert_Bahasa_Sentiment')
-
-inputs = tokenizer("saya tidak", return_tensors="pt")
-
-labels = torch.tensor([1]).unsqueeze(0) 
-
-outputs = model(**inputs, labels=labels)
-
-loss = outputs.loss
-
-logits = outputs.logits
-
-outputs

config.json

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-{
-  "_name_or_path": "test-idtweet/checkpoint-4680",
-  "architectures": [
-    "BertForSequenceClassification"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "directionality": "bidi",
-  "gradient_checkpointing": false,
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "id2label": {
-    "0": "LABEL_0",
-    "1": "LABEL_1",
-    "2": "LABEL_2"
-  },
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "label2id": {
-    "LABEL_0": 0,
-    "LABEL_1": 1,
-    "LABEL_2": 2
-  },
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "pad_token_id": 0,
-  "pooler_fc_size": 768,
-  "pooler_num_attention_heads": 12,
-  "pooler_num_fc_layers": 3,
-  "pooler_size_per_head": 128,
-  "pooler_type": "first_token_transform",
-  "position_embedding_type": "absolute",
-  "transformers_version": "4.5.1",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 105879
-}

pytorch_model.bin

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special_tokens_map.json

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-{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}

tokenizer_config.json

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training_args.bin

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