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--- |
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widget: |
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- text: >- |
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NEW YORK (TheStreet) -- Microsoft (MSFT) - Get Free Report had its price |
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target raised to $39 from $38 by analysts at Jefferies who maintained their |
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'underperform' rating. In Thursday's pre-market trading session shares are |
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advancing 1.24% to $44.79. This action comes as Microsoft said yesterday |
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that it will eliminate up to 7,800 jobs mostly in its phone unit as it looks |
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to restructure its phone hardware business that has been struggling, the New |
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York Times reports. |
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example_title: MSFT news (positive) |
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- text: >- |
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Adobe Brings Major New Innovations to Video Tools SAN JOSE, |
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Calif.--(BUSINESS WIRE)--Today, ahead of the 2023 NAB Show – the preeminent |
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conference and exhibition driving the evolution of broadcast, media and |
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entertainment – Adobe (Nasdaq:ADBE) announced industry-first innovations |
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across its family of video applications, including AI-powered text-based |
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video editing and automated color tone-mapping capabilities in Premiere Pro. |
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SAN JOSE, Calif.--(BUSINESS WIRE). |
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example_title: ADBE news (neutral) |
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- text: >- |
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Unilever PLC (NYSE: UL)’s stock price has gone decline by -0.61 in |
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comparison to its previous close of 54.27, however, the company has |
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experienced a -1.61% decrease in its stock price over the last five trading |
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days. The Wall Street Journal reported on 10/24/22 that Dry Shampoo Recalled |
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Due to Potential Cancer-Causing Ingredient. |
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example_title: UL news (negative) |
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license: mit |
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--- |
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# Finetuned distilBERT model for stock news classification |
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This distilbert model was fine-tuned on 50.000 stock news articles using the HuggingFace adapter from Kern AI refinery. The articles consisted of the headlines plus abstract of the article. |
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For the finetuning, a single NVidia K80 was used for about four hours. |
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Join our Discord if you have questions about this model: https://discord.gg/MdZyqSxKbe |
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DistilBERT is a smaller, faster and lighter version of BERT. It was trained by distilling BERT base and has 40% less parameters than bert-base-uncased. |
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It runs 60% faster while preserving over 95% of BERT’s performances as measured on the GLUE language understanding benchmark. |
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DistilBERT does not have token-type embeddings, pooler and retains only half of the layers from Google’s BERT. |
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## Features |
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- The model can handle various text classification tasks, especially when it comes to stock and finance news sentiment classification. |
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- The output of the model are the three classes "positive", "neutral" and "negative" plus the models respective confidence score of the class. |
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- The model was fine-tuned on a custom datasets that was curated by Kern AI and labeled in our tool refinery. |
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- The model is currently supported by the PyTorch framework and can be easily deployed on various platforms using the HuggingFace Pipeline API. |
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## Usage |
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To use the model, you need to install the HuggingFace Transformers library: |
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```bash |
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pip install transformers |
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``` |
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Then you can load the model and the tokenizer from the HuggingFace Hub: |
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```python |
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from transformers import AutoModelForSequenceClassification, AutoTokenizer |
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model = AutoModelForSequenceClassification.from_pretrained("KernAI/stock-news-distilbert") |
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tokenizer = AutoTokenizer.from_pretrained("KernAI/stock-news-distilbert") |
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``` |
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To classify a single sentence or a sentence pair, you can use the HuggingFace Pipeline API: |
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```python |
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from transformers import pipeline |
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classifier = pipeline("text-classification", model=model, tokenizer=tokenizer) |
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result = classifier("This is a positive sentence.") |
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print(result) |
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# [{'label': 'POSITIVE', 'score': 0.9998656511306763}] |
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``` |
