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--- |
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base_model: unsloth/gemma-7b-bnb-4bit |
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library_name: peft |
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license: mit |
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--- |
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# Model Card for Stock Advisor |
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This is a fine-tuned language model designed to provide stock market analysis and recommendations based on current market data and trends. |
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## Model Details |
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### Model Description |
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The Stock Advisor is a fine-tuned variant of the Gemma-7B model, optimized for providing stock market analysis and recommendations. The model has been trained to understand and analyze market trends, company performance metrics, and provide informed insights about stock investments. |
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- **Developed by:** Adeola Oladeji, Daniel Boadzie |
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- **Model type:** Language Model (Fine-tuned) |
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- **Language(s) (NLP):** English |
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- **License:** MIT |
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- **Finetuned from model:** unsloth/gemma-7b-bnb-4bit |
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### Model Sources |
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- **Repository:** [More Information Needed] |
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- **Paper:** [More Information Needed] |
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- **Demo:** [More Information Needed] |
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## Uses |
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### Direct Use |
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The model can be used to: |
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- Analyze current stock market trends |
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- Provide investment recommendations based on market data |
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- Explain market movements and their potential implications |
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- Offer insights into company performance metrics |
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### Downstream Use |
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- Integration into financial advisory platforms |
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- Stock market analysis tools |
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- Investment research applications |
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- Personal finance management systems |
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### Out-of-Scope Use |
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This model should not be used for: |
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- Guaranteed financial returns predictions |
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- Real-time trading decisions without human oversight |
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- Personal financial advice without proper regulatory compliance |
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- As a sole source for investment decisions |
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## Bias, Risks, and Limitations |
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- The model's analysis is based on historical data and may not account for unexpected market events |
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- Market predictions are inherently uncertain and should not be taken as financial guarantees |
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- The model may have biases towards well-known stocks or markets where more training data was available |
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- Performance may vary during unusual market conditions or black swan events |
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### Recommendations |
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- Users should always combine the model's insights with professional financial advice |
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- The model's outputs should be one of many tools used in investment decision-making |
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- Regular evaluation of the model's performance against current market conditions is recommended |
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- Users should be aware of local financial regulations and compliance requirements |
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## How to Get Started with the Model |
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```python |
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from peft import PeftModel, PeftConfig |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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# Load the base model |
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model_name = "unsloth/gemma-7b-bnb-4bit" |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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model = AutoModelForCausalLM.from_pretrained(model_name) |
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# Load the fine-tuned model |
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peft_model = PeftModel.from_pretrained(model, "path_to_your_finetuned_model") |
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``` |
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## Training Details |
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### Training Data |
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The model was fine-tuned on current stock market data including: |
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- Historical price movements |
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- Company financial reports |
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- Market news and analysis |
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- Trading volumes and patterns |
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[Specific dataset details needed] |
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### Training Procedure |
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#### Training Hyperparameters |
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- **Training regime:** 4-bit quantization with PEFT |
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- **Framework versions:** PEFT 0.13.2 |
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## Evaluation |
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### Testing Data, Factors & Metrics |
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#### Testing Data |
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- Recent market data |
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- Out-of-sample stock performance |
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- Historical market events |
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#### Factors |
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- Market conditions (bull/bear markets) |
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- Sector-specific performance |
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- Company size and market cap |
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- Market volatility levels |
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#### Metrics |
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- Prediction accuracy |
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- Recommendation quality |
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- Analysis comprehensiveness |
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- Risk assessment accuracy |
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### Results |
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[Specific evaluation results needed] |
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## Environmental Impact |
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- **Hardware Type:** [More Information Needed] |
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- **Hours used:** [More Information Needed] |
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- **Cloud Provider:** [More Information Needed] |
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- **Compute Region:** [More Information Needed] |
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- **Carbon Emitted:** [More Information Needed] |
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## Model Card Authors |
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- Adeola Oladeji |
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- Daniel Boadzie |
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## Model Card Contact |
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For questions and feedback about this model, please contact: |
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- Adeola Oladeji |
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- Daniel Boadzie |
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[Contact information needed] |
