216 lines
5.8 KiB
Markdown
216 lines
5.8 KiB
Markdown
---
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license: llama3.1
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datasets:
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- BAAI/OPI
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language:
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- en
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pipeline_tag: text-generation
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tags:
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- Life Science
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- AI4Science
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- Biology
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- Protein
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- LLM
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- Instruction
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base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
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---
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# Github:
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https://github.com/baaihealth/opi
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# Paper:
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[OPI: An Open Instruction Dataset for Adapting Large Language Models to Protein-Related Tasks](https://neurips.cc/virtual/2024/105921) has been accepted by [NeurIPS 2024 Workshop: Foundation Models for Science: Progress, Opportunities, and Challenges](https://neurips.cc/virtual/2024/workshop/84714).
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# Model Card of OPI-Llama-3.1-8B-Instruct
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OPI-Llama-3.1-8B-Instruct was fine-tuned from the Meta-Llama-3.1-8B-Instruct model using the complete OPI training set (i.e.,[OPI_full_1.61M_train.json](https://huggingface.co/datasets/BAAI/OPI/blob/main/OPI_DATA/OPI_full_1.61M_train.json)).
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For more details of training and testing, please visit [https://github.com/baaihealth/opi](https://github.com/baaihealth/opi).
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# Evaluation of OPI-Llama-3.1-8B-Instruct on 9 tasks
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Each testing result is derived from the Meta-Llama-3.1-8B-Instruct model that has been fine-tuned using [OPI_full_1.61M.json](https://huggingface.co/datasets/BAAI/OPI/blob/main/OPI_DATA/OPI_full_1.61M_train.json) and subsequently evaluated on the respective testing set for each specific task.
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<table border="1" style="text-align:center; border-collapse:collapse; width: 100%;">
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<thead>
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<tr>
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<th style="text-align:center;">Task Type</th>
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<th style="text-align:center;">Task Name</th>
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<th style="text-align:center;">Testing file</th>
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<th style="text-align:center;">Accuracy</th>
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<th style="text-align:center;">Precision</th>
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<th style="text-align:center;">Recall</th>
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<th style="text-align:center;">F1</th>
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<th style="text-align:center;">Rouge-L</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td rowspan="6">Sequence Understanding</td>
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<td rowspan="2">EC Number Prediction (split100)</td>
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<td>CLEAN_EC_number_new_test</td>
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<td>-</td>
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<td>0.3724</td>
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<td>0.3374</td>
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<td>0.3468</td>
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<td>-</td>
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</tr>
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<tr>
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<td>CLEAN_EC_number_price_test</td>
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<td>-</td>
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<td>0.0738</td>
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<td>0.0738</td>
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<td>0.0738</td>
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<td>-</td>
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</tr>
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<tr>
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<td rowspan="3">Fold Type Prediction</td>
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<td>fold_type_test_Fold_Holdout</td>
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<td>0.1045</td>
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<td>-</td>
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<td>-</td>
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<td>-</td>
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<td>-</td>
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</tr>
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<tr>
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<td>fold_type_test_Superfamily_Holdout</td>
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<td>0.1507</td>
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<td>-</td>
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<td>-</td>
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<td>-</td>
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<td>-</td>
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</tr>
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<tr>
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<td>fold_type_test_Family_Holdout</td>
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<td>0.6145</td>
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<td>-</td>
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<td>-</td>
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<td>-</td>
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<td>-</td>
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</tr>
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<tr>
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<td>Subcellular Localization Prediction</td>
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<td>subcell_loc_test</td>
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<td>0.4214</td>
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<td>-</td>
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<td>-</td>
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<td>-</td>
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<td>-</td>
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</tr>
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<tr>
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<td rowspan="9">Annotation Prediction</td>
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<td rowspan="3">Function Keywords Prediction</td>
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<td>CASPSimilarSeq_keywords_test</td>
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<td>-</td>
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<td>0.4202</td>
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<td>0.5057</td>
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<td>0.4385</td>
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<td>-</td>
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</tr>
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<tr>
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<td>IDFilterSeq_keywords_test</td>
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<td>-</td>
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<td>0.6762</td>
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<td>0.6905</td>
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<td>0.6650</td>
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<td>-</td>
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</tr>
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<tr>
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<td>UniProtSeq_keywords_test</td>
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<td>-</td>
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<td>0.7606</td>
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<td>0.7489</td>
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<td>0.7374</td>
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<td>-</td>
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</tr>
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<tr>
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<td rowspan="3">Gene Ontology(GO) Terms Prediction</td>
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<td>CASPSimilarSeq_go_terms_test</td>
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<td>-</td>
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<td>0.1113</td>
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<td>0.0936</td>
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<td>0.099</td>
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<td>-</td>
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</tr>
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<tr>
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<td>IDFilterSeq_go_terms_test</td>
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<td>-</td>
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<td>0.6686</td>
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<td>0.6287</td>
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<td>0.6304</td>
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<td>-</td>
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</tr>
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<tr>
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<td>UniProtSeq_go_terms_test</td>
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<td>-</td>
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<td>0.7150</td>
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<td>0.6897</td>
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<td>0.6849</td>
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<td>-</td>
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</tr>
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<tr>
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<td rowspan="3">Function Description Prediction</td>
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<td>CASPSimilarSeq_function_test</td>
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<td>-</td>
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<td>-</td>
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<td>-</td>
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<td>-</td>
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<td>0.7524</td>
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</tr>
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<tr>
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<td>IDFilterSeq_function_test</td>
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<td>-</td>
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<td>-</td>
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<td>-</td>
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<td>-</td>
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<td>0.4786</td>
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</tr>
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<tr>
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<td>UniProtSeq_function_test</td>
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<td>-</td>
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<td>-</td>
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<td>-</td>
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<td>-</td>
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<td>0.5144</td>
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</tr>
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<tr>
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<td rowspan="3">Knowledge Mining</td>
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<td>Tissue Location Prediction from Gene Symbol</td>
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<td>gene_symbol_to_tissue_test</td>
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<td>-</td>
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<td>0.4002</td>
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<td>0.9356</td>
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<td>0.5466</td>
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<td>-</td>
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</tr>
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<tr>
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<td>Cancer Prediction from Gene Symbol</td>
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<td>gene_symbol_to_cancer_test</td>
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<td>-</td>
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<td>0.2890</td>
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<td>0.2701</td>
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<td>0.2664</td>
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<td>-</td>
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</tr>
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<tr>
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<td>Cancer Prediction from Gene Name</td>
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<td>gene_name_to_cancer_test</td>
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<td>-</td>
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<td>0.2786</td>
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<td>0.2707</td>
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<td>0.2659</td>
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<td>-</td>
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</tr>
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</tbody>
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</table>
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# Prediction comparison with SOTA mdoels
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