CSQA GPT2-Large Context-Aware Model

This model is a GPT2-large based model fine-tuned for the CommonsenseQA (CSQA) task with context-aware capabilities.

Model Architecture

This is a multi-component model that includes:

Encoder Model: GPT2-large based encoder with adapter layers
Latent Model: GPT2-large based latent representation model with adapter layers
Decoder Model: GPT2-large based decoder with adapter layers
Projection Layers: Linear projections between encoder-latent and latent-decoder components

encoder.pt / encoder_model/: Encoder component weights and configuration
latent_model.pt / latent_model/: Latent model component weights and configuration
decoder.pt / decoder_model/: Decoder component weights and configuration
encoder_to_latent_model_proj.pt: Projection layer from encoder to latent model
latent_model_to_decoder_proj.pt: Projection layer from latent model to decoder
tokenizer/: GPT2 tokenizer files
config.json: Model configuration

This model was trained for the CommonsenseQA task and includes specialized components for context-aware reasoning.

The model was trained in multiple stages on the CommonsenseQA dataset, incorporating context-aware mechanisms to improve reasoning capabilities.