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
fromdistilbert-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
frombert-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.
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