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--- |
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language: |
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- zh |
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tags: |
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- bert |
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- financial-sentiment-analysis |
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- sentiment-analysis |
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license: "apache-2.0" |
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widget: |
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- text: "此外宁德时代上半年实现出口约2GWh，同比增加200%+。" |
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|
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--- |
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# Financial Sentiment Analysis in Chinese |
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This is a fine-tuned version of FinBERT, based on [bert-base-chinese](https://huggingface.co/bert-base-chinese), on a private dataset (around ~8k analyst report sentences) for sentiment analysis. |
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* Test Accuracy = 0.88 |
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* Test Macro F1 = 0.87 |
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* **Labels**: 0 -> Neutral; 1 -> Positive; 2 -> Negative |
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# Usage |
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``` |
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from transformers import TextClassificationPipeline |
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from transformers import AutoModelForSequenceClassification, TrainingArguments, Trainer |
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from transformers import BertTokenizerFast |
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model_path="./fin_sentiment_bert_zh/" |
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new_model = AutoModelForSequenceClassification.from_pretrained(model_path,output_attentions=True) |
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tokenizer = BertTokenizerFast.from_pretrained(model_path) |
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PipelineInterface = TextClassificationPipeline(model=new_model, tokenizer=tokenizer, return_all_scores=True) |
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label = PipelineInterface("此外宁德时代上半年实现出口约2GWh，同比增加200%+。") |
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print(label) |
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``` |
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``` |
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[[{'label': 'LABEL_0', 'score': 0.0007030126871541142}, {'label': 'LABEL_1', 'score': 0.9989339709281921}, {'label': 'LABEL_2', 'score': 0.000363016442861408}]] |
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``` |
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