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+ "Task&Skill","tot","prefetch","hit","prefetch_rate","acc"
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+ "Overall","1000","581","341","58.099999999999994","34.1"
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+ "scientific reasoning","122","96","51","78.68852459016394","41.80327868852459"
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+ "textbook question answering","158","107","67","67.72151898734177","42.405063291139236"
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+ "numeric commonsense","144","46","45","31.944444444444443","31.25"
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+ "arithmetic reasoning","353","108","113","30.59490084985836","32.01133144475921"
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+ "visual question answering","179","99","61","55.3072625698324","34.07821229050279"
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+ "geometry reasoning","239","212","66","88.70292887029288","27.615062761506277"
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+ "algebraic reasoning","281","239","75","85.05338078291815","26.690391459074732"
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+ "geometry problem solving","208","203","50","97.59615384615384","24.03846153846154"
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+ "math word problem","186","23","72","12.365591397849462","38.70967741935484"
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+ "logical reasoning","37","24","6","64.86486486486487","16.216216216216218"
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+ "figure question answering","269","149","91","55.39033457249071","33.82899628252788"
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+ "statistical reasoning","301","140","103","46.51162790697674","34.21926910299003"
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+ "split","Overall","acc","precision","recall"
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+ "Overall","83.74662410999264","85.28888888888889","93.5545803620406","75.8"
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+ "popular","84.4097995545657","86.0","95.22613065326632","75.8"
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+ "adversarial","82.06423673763983","83.43333333333334","89.45712037765539","75.8"
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+ "random","84.81909735173443","86.43333333333332","96.27434377646063","75.8"
README.md ADDED
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+ ---
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+ base_model: TIGER-Lab/Mantis-8B-siglip-llama3-pretraind
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+ library_name: peft
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+ ---
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+
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+ # Model Card for Model ID
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+
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+ <!-- Provide a quick summary of what the model is/does. -->
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+ ## Model Details
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+ ### Model Description
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+ <!-- Provide a longer summary of what this model is. -->
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+ ## Bias, Risks, and Limitations
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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.
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+
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+ ## How to Get Started with the Model
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+ Use the code below to get started with the model.
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+ [More Information Needed]
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+ ## Training Details
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+ ### Training Data
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+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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+ ### Training Procedure
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+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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+ #### Preprocessing [optional]
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+ [More Information Needed]
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+ #### Training Hyperparameters
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+
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+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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+ #### Speeds, Sizes, Times [optional]
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+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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+ ## Evaluation
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+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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+ [More Information Needed]
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+ #### Metrics
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+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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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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+ ## Model Card Contact
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+ [More Information Needed]
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+ ### Framework versions
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+
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+ - PEFT 0.12.0