Update README.md

README.md

@@ -93,51 +93,34 @@ Fine-tuning is conducted on curated perovskite precursor additive datasets.
 
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+Performance is assessed using a benchmark dataset relevant to perovskite solar cell precursor additives
 
-#### Factors
+#### Factors & Metrics
 
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-#### Metrics
+Evaluation focuses on domain-specific factors such as material composition suggestions and additive effects on device performance. Metrics include qualitative alignment with literature findings and consistency in benchmark predictions.
 
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 ### Results
 
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+Model performance was evaluated using a benchmark dataset related to perovskite solar cell precursor additives. Compared with other models on the same benchmark, it demonstrates superior alignment with literature findings and provides consistent, reliable suggestions for material composition and additive effects. While the results are based on this benchmark, they indicate strong potential for supporting research in perovskite solar cell chemistry.
 
 #### Summary
 
+This model is a large language model specialized in perovskite solar cell precursor additives. It can support research by providing literature-aligned suggestions for material composition and additive effects. Evaluated on a benchmark dataset, it shows superior performance compared to other models, indicating strong potential for accelerating research and hypothesis generation. Users are encouraged to verify all outputs experimentally and consult domain experts for critical decisions.
 
 
-## Model Examination [optional]
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-<!-- Relevant interpretability work for the model goes here -->
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 ## Environmental Impact
 
 <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
 
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
+Training was conducted on a limited number of GPUs with standard energy consumption, and no significant environmental impact is expected.
 
-## Technical Specifications [optional]
 
 ### Model Architecture and Objective
 
-[More Information Needed]
+The model is a transformer-based large language model designed for scientific text understanding and generation in the domain of perovskite solar cell precursor additives. It adopts a decoder-only architecture and is fine-tuned using instruction tuning with LoRA to provide accurate and literature-aligned suggestions for material composition, additive effects, and device performance optimization.
 
 ### Compute Infrastructure