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README.md
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# Stock Sentiment Analysis
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This model is a fine-tuned version of `microsoft/deberta-v3-base` for **stock sentiment analysis**.
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- **Classes**: Positive, Neutral, Negative
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## Training
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- Dataset: [Your Dataset Name or Description]
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- Evaluation Metric: F1 Score
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- Training Args: See `training_args.bin` for details.
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text = "The stock market is performing well today."
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inputs = tokenizer(text, return_tensors="pt")
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outputs = model(**inputs)
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print(outputs.logits)
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---
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license: apache-2.0
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language:
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- en
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metrics:
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- accuracy
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- precision
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- recall
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base_model:
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- microsoft/deberta-v3-base
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pipeline_tag: text-classification
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---
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# Stock Sentiment Analysis
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This model is a fine-tuned version of `microsoft/deberta-v3-base` for **stock sentiment analysis**.
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- **Classes**: Positive, Neutral, Negative
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## Training
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- Evaluation Metric: F1 Score
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- Training Args: See `training_args.bin` for details.
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text = "The stock market is performing well today."
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inputs = tokenizer(text, return_tensors="pt")
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outputs = model(**inputs)
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print(outputs.logits)
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