metadata

model-index:
  - name: Existence Analysis
    results:
      - task:
          type: text-classification
        dataset:
          name: niltheory/ExistenceTypes
          type: parquet
        metrics:
          - name: Existence Analysis 00
            type: Existence Analysis 00
            value: 70
        source:
          name: Open LLM Leaderboard
          url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
language:
  - en
metrics:
  - accuracy

Existence Analysis Model (EAM)

Created for: Compendium Terminum, IP
Base Model: bert-large-cased-whole-word-masking

Iterative Development

Iteration #1:

Initial Model: Utilized distilBert for foundational training.
Dataset Size: 96 entries.
Outcome: Established baseline for accuracy metrics.

Iteration #2:

Model Upgrade: Transitioned to bert-base-uncased from distilbert-base-uncased.
Dataset Expansion: Increased from 96 to 296 entries.
Performance: Improved accuracy scores; identified edge cases for refinement.

Iteration #3:

Model Upgrade: Transitioned to bert-large-cased-whole-word-masking from bert-base-uncased.
Advancements: Enhanced contextual sensitivity and accuracy.
Results: Demonstrated more nuanced understanding and sensitivity in predictions.

Observations

Each iteration has contributed to the model's evolving sophistication, leading to improved interpretive performance and accuracy.
Continuous evaluation, especially in complex or ambiguous cases, is pivotal for future enhancements.