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README.md ADDED
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+ ---
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+ language:
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+ - ru
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+ tags:
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+ - sentiment
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+ - text-classification
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+ datasets:
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+ - RuTweetCorp
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+ ---
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+
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+ # RuBERT for Sentiment Analysis of Tweets
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+
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+ This is a [DeepPavlov/rubert-base-cased-conversational](https://huggingface.co/DeepPavlov/rubert-base-cased-conversational) model trained on [RuTweetCorp](https://study.mokoron.com/).
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+
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+ ## Labels
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+ 0: POSITIVE
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+ 1: NEGATIVE
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+
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+ ## How to use
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+ ```python
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+
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+ import torch
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+ from transformers import AutoModelForSequenceClassification
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+ from transformers import BertTokenizerFast
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+
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+ tokenizer = BertTokenizerFast.from_pretrained('blanchefort/rubert-base-cased-sentiment-mokoron')
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+ model = AutoModelForSequenceClassification.from_pretrained('blanchefort/rubert-base-cased-sentiment-mokoron', return_dict=True)
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+
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+ @torch.no_grad()
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+ def predict(text):
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+ inputs = tokenizer(text, max_length=512, padding=True, truncation=True, return_tensors='pt')
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+ outputs = model(**inputs)
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+ predicted = torch.nn.functional.softmax(outputs.logits, dim=1)
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+ predicted = torch.argmax(predicted, dim=1).numpy()
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+ return predicted
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+ ```
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+
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+
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+ ## Dataset used for model training
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+
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+ **[RuTweetCorp](https://study.mokoron.com/)**
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+
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+ > Рубцова Ю. Автоматическое построение и анализ корпуса коротких текстов (постов микроблогов) для задачи разработки и тренировки тонового классификатора // Инженерия знаний и технологии семантического веба. – 2012. – Т. 1. – С. 109-116.
config.json ADDED
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+ {
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+ "_name_or_path": "../huggingface/rubert-base-cased-sentiment-mokoron",
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+ "architectures": [
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+ "BertForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "directionality": "bidi",
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+ "gradient_checkpointing": false,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "output_past": true,
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+ "pad_token_id": 0,
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+ "pooler_fc_size": 768,
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+ "pooler_num_attention_heads": 12,
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+ "pooler_num_fc_layers": 3,
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+ "pooler_size_per_head": 128,
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+ "pooler_type": "first_token_transform",
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+ "return_dict": true,
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+ "type_vocab_size": 2,
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+ "vocab_size": 119547
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+ }
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vocab.txt ADDED
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