Stock Sentiment Analysis

This model is a fine-tuned version of microsoft/deberta-v3-base for stock sentiment analysis.

Model Details

  • Language: English
  • Task: Text Classification (Sentiment Analysis)
  • Classes: Positive, Neutral, Negative

Training

  • Evaluation Metric: F1 Score
  • Training Args: See training_args.bin for details.

Usage

from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("vinD27/stock_sentiment_analysis")
model = AutoModelForSequenceClassification.from_pretrained("vinD27/stock_sentiment_analysis")

text = "The stock market is performing well today."
inputs = tokenizer(text, return_tensors="pt")
outputs = model(**inputs)
print(outputs.logits)
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