license: apache-2.0
language:
- en
base_model:
- distilbert/distilgpt2
pipeline_tag: text-classification
library_name: transformers
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