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Model-DMS_AsCas12f-35M

PEFT

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FarmerTao commited on Jul 27

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@@ -6,197 +6,49 @@ library_name: peft
 # Model Card for Model ID
 <!-- Provide a quick summary of what the model is/does. -->
-## Model Details
-### Model Description
-<!-- Provide a longer summary of what this model is. -->
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-## Uses
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-### Direct Use
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-## Bias, Risks, and Limitations
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-### Recommendations
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-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-## How to Get Started with the Model
-Use the code below to get started with the model.
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-## Training Details
-### Training Data
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-### Training Procedure
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-#### Preprocessing [optional]
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-#### Training Hyperparameters
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-#### Speeds, Sizes, Times [optional]
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-## Evaluation
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-### Testing Data, Factors & Metrics
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-### Results
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-#### Summary
-## Model Examination [optional]
-<!-- Relevant interpretability work for the model goes here -->
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-## Environmental Impact
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-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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-## Technical Specifications [optional]
-### Model Architecture and Objective
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-### Compute Infrastructure
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-#### Hardware
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-## Citation [optional]
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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-## Glossary [optional]
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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-## More Information [optional]
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-## Model Card Authors [optional]
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-## Model Card Contact
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-### Framework versions
-- PEFT 0.10.0

 # Model Card for Model ID
 <!-- Provide a quick summary of what the model is/does. -->
+This model is trained on a sigle site deep mutation scanning dataset and
+can be used to predict fitness score of mutant amino acid sequence of protein AsCas12f.
+## Protein Function
+AsCas12a is widely utilized as genome-editing tools in human cells.
+### Task type
+protein level regression
+### Dataset description
+The dataset is from [An AsCas12f-based compact genome-editing tool derived by deep mutational scanning and structural analysis](https://doi.org/10.1016/j.cell.2023.08.031).
+Label means fitness score of each mutant amino acid sequence.
+Ranging from negative infinity to positive infinity. The wildtype sequence has fitness 1.
+If the effect larger than 1 represents high fitness, smaller than 1 represents low fitness.
+### Model input type
+Amino acid sequence
+### Performance
+ 0.60 Spearman's ρ
+### LoRA config
+lora_dropout: 0.0
+lora_alpha: 16
+target_modules: ["query", "key", "value", "intermediate.dense", "output.dense"]
+modules_to_save: ["classifier"]
+### Training config
+class: AdamW
+betas: (0.9, 0.98)
+weight_decay: 0.01
+learning rate: 1e-4
+epoch: 50
+batch size: 36
+precision: 16-mixed