Dharshika10/cubeai_data_model

Model Details Model Description This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

• Model type: Causal Language Model (Fine-tuned GPT2)
• Language(s) (NLP): English
• License: Apache-2.
• Finetuned from model [optional]: distilbert/distilgpt2

Direct Use

This model can answer company-related questions from a dataset of structured Q&A pairs.

Bias, Risks, and Limitations

The model only knows what was in your dataset. It may give inaccurate or incomplete answers for questions outside that scope. It may repeat format-specific patterns or show overfitting if trained too long on a small dataset. It does not have any awareness of real-time data or external company knowledge.

Training Details

Training Data

Excel sheet: company_details.xlsx containing Question, Answer, and Split columns. Number of samples: len(data_sample) (replace with actual number).

Training Hyperparameters

Epochs: 200 Batch size: 32 Optimizer: Adam Learning rate: 5e-4 Loss: CrossEntropy (ignoring pad tokens)

Evaluation

Validation

Dataset split: 80% training, 20% validation Metrics used: Validation Loss

Environmental Impact

• Hardware Type: GPU (e.g., Tesla T4/Colab GPU)
• Hours used: Estimate (e.g., ~1 hour)
• Cloud Provider: Google Colab
• Compute Region: India or Global