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README.md

@@ -0,0 +1,204 @@
+---
+library_name: peft
+base_model: baichuan-inc/Baichuan2-7B-Base
+---
+
+# 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. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+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.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- 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. -->
+
+[More Information Needed]
+
+### Training Procedure 
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## 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).
+
+- **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]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## 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. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+
+
+### Framework versions
+
+- PEFT 0.7.2.dev0

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "baichuan-inc/Baichuan2-7B-Base",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "gate_proj",
+    "up_proj",
+    "down_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_rslora": true
+}

adapter_model.safetensors

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checkpoint-2000/README.md

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+---
+library_name: peft
+base_model: baichuan-inc/Baichuan2-7B-Base
+---
+
+# 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. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+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.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- 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. -->
+
+[More Information Needed]
+
+### Training Procedure 
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## 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).
+
+- **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]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## 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. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+
+
+### Framework versions
+
+- PEFT 0.7.2.dev0

checkpoint-2000/adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "baichuan-inc/Baichuan2-7B-Base",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
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+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "down_proj",
+    "gate_proj",
+    "up_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_rslora": true
+}

checkpoint-2000/adapter_model.bin

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checkpoint-3000/README.md

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+---
+library_name: peft
+base_model: baichuan-inc/Baichuan2-7B-Base
+---
+
+# 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. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+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.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- 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. -->
+
+[More Information Needed]
+
+### Training Procedure 
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## 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).
+
+- **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]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## 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. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+
+
+### Framework versions
+
+- PEFT 0.7.2.dev0

checkpoint-3000/adapter_config.json

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+    "gate_proj",
+    "up_proj"
+  ],
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+}

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+  "results": {
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+      "acc,none": 0.4811992593647629,
+      "acc_stderr,none": 0.11827476804960772,
+      "alias": "mmlu"
+    },
+    "mmlu_humanities": {
+      "alias": " - humanities",
+      "acc,none": 0.45504782146652495,
+      "acc_stderr,none": 0.12864316445574026
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+      "alias": "  - formal_logic",
+      "acc,none": 0.31746031746031744,
+      "acc_stderr,none": 0.04163453031302859
+    },
+    "mmlu_high_school_european_history": {
+      "alias": "  - high_school_european_history",
+      "acc,none": 0.6424242424242425,
+      "acc_stderr,none": 0.037425970438065864
+    },
+    "mmlu_high_school_us_history": {
+      "alias": "  - high_school_us_history",
+      "acc,none": 0.6372549019607843,
+      "acc_stderr,none": 0.03374499356319355
+    },
+    "mmlu_high_school_world_history": {
+      "alias": "  - high_school_world_history",
+      "acc,none": 0.679324894514768,
+      "acc_stderr,none": 0.030381931949990417
+    },
+    "mmlu_international_law": {
+      "alias": "  - international_law",
+      "acc,none": 0.6694214876033058,
+      "acc_stderr,none": 0.04294340845212094
+    },
+    "mmlu_jurisprudence": {
+      "alias": "  - jurisprudence",
+      "acc,none": 0.6018518518518519,
+      "acc_stderr,none": 0.04732332615978814
+    },
+    "mmlu_logical_fallacies": {
+      "alias": "  - logical_fallacies",
+      "acc,none": 0.558282208588957,
+      "acc_stderr,none": 0.03901591825836184
+    },
+    "mmlu_moral_disputes": {
+      "alias": "  - moral_disputes",
+      "acc,none": 0.5491329479768786,
+      "acc_stderr,none": 0.026788811931562753
+    },
+    "mmlu_moral_scenarios": {
+      "alias": "  - moral_scenarios",
+      "acc,none": 0.2424581005586592,
+      "acc_stderr,none": 0.014333522059217887
+    },
+    "mmlu_philosophy": {
+      "alias": "  - philosophy",
+      "acc,none": 0.5337620578778135,
+      "acc_stderr,none": 0.028333277109562786
+    },
+    "mmlu_prehistory": {
+      "alias": "  - prehistory",
+      "acc,none": 0.558641975308642,
+      "acc_stderr,none": 0.027628737155668777
+    },
+    "mmlu_professional_law": {
+      "alias": "  - professional_law",
+      "acc,none": 0.39048239895697523,
+      "acc_stderr,none": 0.012460135913945073
+    },
+    "mmlu_world_religions": {
+      "alias": "  - world_religions",
+      "acc,none": 0.6666666666666666,
+      "acc_stderr,none": 0.036155076303109344
+    },
+    "mmlu_other": {
+      "alias": " - other",
+      "acc,none": 0.5526231091084648,
+      "acc_stderr,none": 0.09630130905093312
+    },
+    "mmlu_business_ethics": {
+      "alias": "  - business_ethics",
+      "acc,none": 0.57,
+      "acc_stderr,none": 0.04975698519562427
+    },
+    "mmlu_clinical_knowledge": {
+      "alias": "  - clinical_knowledge",
+      "acc,none": 0.5207547169811321,
+      "acc_stderr,none": 0.030746349975723463
+    },
+    "mmlu_college_medicine": {
+      "alias": "  - college_medicine",
+      "acc,none": 0.4624277456647399,
+      "acc_stderr,none": 0.0380168510452446
+    },
+    "mmlu_global_facts": {
+      "alias": "  - global_facts",
+      "acc,none": 0.36,
+      "acc_stderr,none": 0.04824181513244218
+    },
+    "mmlu_human_aging": {
+      "alias": "  - human_aging",
+      "acc,none": 0.5919282511210763,
+      "acc_stderr,none": 0.03298574607842822
+    },
+    "mmlu_management": {
+      "alias": "  - management",
+      "acc,none": 0.6699029126213593,
+      "acc_stderr,none": 0.0465614711001235
+    },
+    "mmlu_marketing": {
+      "alias": "  - marketing",
+      "acc,none": 0.7008547008547008,
+      "acc_stderr,none": 0.029996951858349486
+    },
+    "mmlu_medical_genetics": {
+      "alias": "  - medical_genetics",
+      "acc,none": 0.52,
+      "acc_stderr,none": 0.05021167315686779
+    },
+    "mmlu_miscellaneous": {
+      "alias": "  - miscellaneous",
+      "acc,none": 0.6807151979565773,
+      "acc_stderr,none": 0.016671261749538722
+    },
+    "mmlu_nutrition": {
+      "alias": "  - nutrition",
+      "acc,none": 0.5261437908496732,
+      "acc_stderr,none": 0.028590752958852394
+    },
+    "mmlu_professional_accounting": {
+      "alias": "  - professional_accounting",
+      "acc,none": 0.36879432624113473,
+      "acc_stderr,none": 0.028782227561347247
+    },
+    "mmlu_professional_medicine": {
+      "alias": "  - professional_medicine",
+      "acc,none": 0.4411764705882353,
+      "acc_stderr,none": 0.030161911930767105
+    },
+    "mmlu_virology": {
+      "alias": "  - virology",
+      "acc,none": 0.42771084337349397,
+      "acc_stderr,none": 0.038515976837185335
+    },
+    "mmlu_social_sciences": {
+      "alias": " - social_sciences",
+      "acc,none": 0.5407864803379916,
+      "acc_stderr,none": 0.09279588633835714
+    },
+    "mmlu_econometrics": {
+      "alias": "  - econometrics",
+      "acc,none": 0.2894736842105263,
+      "acc_stderr,none": 0.04266339443159394
+    },
+    "mmlu_high_school_geography": {
+      "alias": "  - high_school_geography",
+      "acc,none": 0.5909090909090909,
+      "acc_stderr,none": 0.035029757994130065
+    },
+    "mmlu_high_school_government_and_politics": {
+      "alias": "  - high_school_government_and_politics",
+      "acc,none": 0.6787564766839378,
+      "acc_stderr,none": 0.033699508685490674
+    },
+    "mmlu_high_school_macroeconomics": {
+      "alias": "  - high_school_macroeconomics",
+      "acc,none": 0.4282051282051282,
+      "acc_stderr,none": 0.02508830145469483
+    },
+    "mmlu_high_school_microeconomics": {
+      "alias": "  - high_school_microeconomics",
+      "acc,none": 0.42436974789915966,
+      "acc_stderr,none": 0.032104790510157764
+    },
+    "mmlu_high_school_psychology": {
+      "alias": "  - high_school_psychology",
+      "acc,none": 0.6330275229357798,
+      "acc_stderr,none": 0.020664675659520532
+    },
+    "mmlu_human_sexuality": {
+      "alias": "  - human_sexuality",
+      "acc,none": 0.6259541984732825,
+      "acc_stderr,none": 0.04243869242230523
+    },
+    "mmlu_professional_psychology": {
+      "alias": "  - professional_psychology",
+      "acc,none": 0.49019607843137253,
+      "acc_stderr,none": 0.0202239460050743
+    },
+    "mmlu_public_relations": {
+      "alias": "  - public_relations",
+      "acc,none": 0.5636363636363636,
+      "acc_stderr,none": 0.04750185058907296
+    },
+    "mmlu_security_studies": {
+      "alias": "  - security_studies",
+      "acc,none": 0.4816326530612245,
+      "acc_stderr,none": 0.03198761546763127
+    },
+    "mmlu_sociology": {
+      "alias": "  - sociology",
+      "acc,none": 0.681592039800995,
+      "acc_stderr,none": 0.03294118479054095
+    },
+    "mmlu_us_foreign_policy": {
+      "alias": "  - us_foreign_policy",
+      "acc,none": 0.71,
+      "acc_stderr,none": 0.04560480215720684
+    },
+    "mmlu_stem": {
+      "alias": " - stem",
+      "acc,none": 0.3916904535363146,
+      "acc_stderr,none": 0.10496079468282744
+    },
+    "mmlu_abstract_algebra": {
+      "alias": "  - abstract_algebra",
+      "acc,none": 0.29,
+      "acc_stderr,none": 0.04560480215720683
+    },
+    "mmlu_anatomy": {
+      "alias": "  - anatomy",
+      "acc,none": 0.4666666666666667,
+      "acc_stderr,none": 0.043097329010363554
+    },
+    "mmlu_astronomy": {
+      "alias": "  - astronomy",
+      "acc,none": 0.48026315789473684,
+      "acc_stderr,none": 0.04065771002562605
+    },
+    "mmlu_college_biology": {
+      "alias": "  - college_biology",
+      "acc,none": 0.4722222222222222,
+      "acc_stderr,none": 0.04174752578923185
+    },
+    "mmlu_college_chemistry": {
+      "alias": "  - college_chemistry",
+      "acc,none": 0.3,
+      "acc_stderr,none": 0.046056618647183814
+    },
+    "mmlu_college_computer_science": {
+      "alias": "  - college_computer_science",
+      "acc,none": 0.42,
+      "acc_stderr,none": 0.049604496374885836
+    },
+    "mmlu_college_mathematics": {
+      "alias": "  - college_mathematics",
+      "acc,none": 0.32,
+      "acc_stderr,none": 0.046882617226215034
+    },
+    "mmlu_college_physics": {
+      "alias": "  - college_physics",
+      "acc,none": 0.22549019607843138,
+      "acc_stderr,none": 0.04158307533083286
+    },
+    "mmlu_computer_security": {
+      "alias": "  - computer_security",
+      "acc,none": 0.59,
+      "acc_stderr,none": 0.04943110704237102
+    },
+    "mmlu_conceptual_physics": {
+      "alias": "  - conceptual_physics",
+      "acc,none": 0.40425531914893614,
+      "acc_stderr,none": 0.032081157507886836
+    },
+    "mmlu_electrical_engineering": {
+      "alias": "  - electrical_engineering",
+      "acc,none": 0.5655172413793104,
+      "acc_stderr,none": 0.04130740879555497
+    },
+    "mmlu_elementary_mathematics": {
+      "alias": "  - elementary_mathematics",
+      "acc,none": 0.2857142857142857,
+      "acc_stderr,none": 0.023266512213730564
+    },
+    "mmlu_high_school_biology": {
+      "alias": "  - high_school_biology",
+      "acc,none": 0.5387096774193548,
+      "acc_stderr,none": 0.028358634859836935
+    },
+    "mmlu_high_school_chemistry": {
+      "alias": "  - high_school_chemistry",
+      "acc,none": 0.4187192118226601,
+      "acc_stderr,none": 0.03471192860518468
+    },
+    "mmlu_high_school_computer_science": {
+      "alias": "  - high_school_computer_science",
+      "acc,none": 0.51,
+      "acc_stderr,none": 0.05024183937956913
+    },
+    "mmlu_high_school_mathematics": {
+      "alias": "  - high_school_mathematics",
+      "acc,none": 0.24814814814814815,
+      "acc_stderr,none": 0.026335739404055803
+    },
+    "mmlu_high_school_physics": {
+      "alias": "  - high_school_physics",
+      "acc,none": 0.31125827814569534,
+      "acc_stderr,none": 0.03780445850526732
+    },
+    "mmlu_high_school_statistics": {
+      "alias": "  - high_school_statistics",
+      "acc,none": 0.30092592592592593,
+      "acc_stderr,none": 0.03128039084329882
+    },
+    "mmlu_machine_learning": {
+      "alias": "  - machine_learning",
+      "acc,none": 0.4375,
+      "acc_stderr,none": 0.04708567521880525
+    }
+  },
+  "groups": {
+    "mmlu": {
+      "acc,none": 0.4811992593647629,
+      "acc_stderr,none": 0.11827476804960772,
+      "alias": "mmlu"
+    },
+    "mmlu_humanities": {
+      "alias": " - humanities",
+      "acc,none": 0.45504782146652495,
+      "acc_stderr,none": 0.12864316445574026
+    },
+    "mmlu_other": {
+      "alias": " - other",
+      "acc,none": 0.5526231091084648,
+      "acc_stderr,none": 0.09630130905093312
+    },
+    "mmlu_social_sciences": {
+      "alias": " - social_sciences",
+      "acc,none": 0.5407864803379916,
+      "acc_stderr,none": 0.09279588633835714
+    },
+    "mmlu_stem": {
+      "alias": " - stem",
+      "acc,none": 0.3916904535363146,
+      "acc_stderr,none": 0.10496079468282744
+    }
+  },
+  "configs": {
+    "mmlu_abstract_algebra": {
+      "task": "mmlu_abstract_algebra",
+      "task_alias": "abstract_algebra",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "abstract_algebra",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about abstract algebra.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_anatomy": {
+      "task": "mmlu_anatomy",
+      "task_alias": "anatomy",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "anatomy",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about anatomy.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_astronomy": {
+      "task": "mmlu_astronomy",
+      "task_alias": "astronomy",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "astronomy",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about astronomy.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_business_ethics": {
+      "task": "mmlu_business_ethics",
+      "task_alias": "business_ethics",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "business_ethics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about business ethics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_clinical_knowledge": {
+      "task": "mmlu_clinical_knowledge",
+      "task_alias": "clinical_knowledge",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "clinical_knowledge",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about clinical knowledge.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_college_biology": {
+      "task": "mmlu_college_biology",
+      "task_alias": "college_biology",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "college_biology",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about college biology.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_college_chemistry": {
+      "task": "mmlu_college_chemistry",
+      "task_alias": "college_chemistry",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "college_chemistry",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about college chemistry.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_college_computer_science": {
+      "task": "mmlu_college_computer_science",
+      "task_alias": "college_computer_science",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "college_computer_science",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about college computer science.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_college_mathematics": {
+      "task": "mmlu_college_mathematics",
+      "task_alias": "college_mathematics",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "college_mathematics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about college mathematics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_college_medicine": {
+      "task": "mmlu_college_medicine",
+      "task_alias": "college_medicine",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "college_medicine",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about college medicine.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_college_physics": {
+      "task": "mmlu_college_physics",
+      "task_alias": "college_physics",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "college_physics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about college physics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_computer_security": {
+      "task": "mmlu_computer_security",
+      "task_alias": "computer_security",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "computer_security",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about computer security.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_conceptual_physics": {
+      "task": "mmlu_conceptual_physics",
+      "task_alias": "conceptual_physics",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "conceptual_physics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about conceptual physics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_econometrics": {
+      "task": "mmlu_econometrics",
+      "task_alias": "econometrics",
+      "group": "mmlu_social_sciences",
+      "group_alias": "social_sciences",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "econometrics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about econometrics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_electrical_engineering": {
+      "task": "mmlu_electrical_engineering",
+      "task_alias": "electrical_engineering",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "electrical_engineering",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about electrical engineering.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_elementary_mathematics": {
+      "task": "mmlu_elementary_mathematics",
+      "task_alias": "elementary_mathematics",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "elementary_mathematics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about elementary mathematics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_formal_logic": {
+      "task": "mmlu_formal_logic",
+      "task_alias": "formal_logic",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "formal_logic",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about formal logic.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_global_facts": {
+      "task": "mmlu_global_facts",
+      "task_alias": "global_facts",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "global_facts",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about global facts.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_biology": {
+      "task": "mmlu_high_school_biology",
+      "task_alias": "high_school_biology",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_biology",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school biology.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_chemistry": {
+      "task": "mmlu_high_school_chemistry",
+      "task_alias": "high_school_chemistry",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_chemistry",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school chemistry.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_computer_science": {
+      "task": "mmlu_high_school_computer_science",
+      "task_alias": "high_school_computer_science",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_computer_science",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school computer science.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_european_history": {
+      "task": "mmlu_high_school_european_history",
+      "task_alias": "high_school_european_history",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_european_history",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school european history.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_geography": {
+      "task": "mmlu_high_school_geography",
+      "task_alias": "high_school_geography",
+      "group": "mmlu_social_sciences",
+      "group_alias": "social_sciences",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_geography",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school geography.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_government_and_politics": {
+      "task": "mmlu_high_school_government_and_politics",
+      "task_alias": "high_school_government_and_politics",
+      "group": "mmlu_social_sciences",
+      "group_alias": "social_sciences",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_government_and_politics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school government and politics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_macroeconomics": {
+      "task": "mmlu_high_school_macroeconomics",
+      "task_alias": "high_school_macroeconomics",
+      "group": "mmlu_social_sciences",
+      "group_alias": "social_sciences",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_macroeconomics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school macroeconomics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_mathematics": {
+      "task": "mmlu_high_school_mathematics",
+      "task_alias": "high_school_mathematics",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_mathematics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school mathematics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_microeconomics": {
+      "task": "mmlu_high_school_microeconomics",
+      "task_alias": "high_school_microeconomics",
+      "group": "mmlu_social_sciences",
+      "group_alias": "social_sciences",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_microeconomics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school microeconomics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_physics": {
+      "task": "mmlu_high_school_physics",
+      "task_alias": "high_school_physics",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_physics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school physics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_psychology": {
+      "task": "mmlu_high_school_psychology",
+      "task_alias": "high_school_psychology",
+      "group": "mmlu_social_sciences",
+      "group_alias": "social_sciences",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_psychology",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school psychology.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_statistics": {
+      "task": "mmlu_high_school_statistics",
+      "task_alias": "high_school_statistics",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_statistics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school statistics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_us_history": {
+      "task": "mmlu_high_school_us_history",
+      "task_alias": "high_school_us_history",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_us_history",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school us history.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_high_school_world_history": {
+      "task": "mmlu_high_school_world_history",
+      "task_alias": "high_school_world_history",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "high_school_world_history",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about high school world history.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_human_aging": {
+      "task": "mmlu_human_aging",
+      "task_alias": "human_aging",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "human_aging",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about human aging.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_human_sexuality": {
+      "task": "mmlu_human_sexuality",
+      "task_alias": "human_sexuality",
+      "group": "mmlu_social_sciences",
+      "group_alias": "social_sciences",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "human_sexuality",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about human sexuality.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_international_law": {
+      "task": "mmlu_international_law",
+      "task_alias": "international_law",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "international_law",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about international law.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_jurisprudence": {
+      "task": "mmlu_jurisprudence",
+      "task_alias": "jurisprudence",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "jurisprudence",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about jurisprudence.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_logical_fallacies": {
+      "task": "mmlu_logical_fallacies",
+      "task_alias": "logical_fallacies",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "logical_fallacies",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about logical fallacies.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_machine_learning": {
+      "task": "mmlu_machine_learning",
+      "task_alias": "machine_learning",
+      "group": "mmlu_stem",
+      "group_alias": "stem",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "machine_learning",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about machine learning.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_management": {
+      "task": "mmlu_management",
+      "task_alias": "management",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "management",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about management.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_marketing": {
+      "task": "mmlu_marketing",
+      "task_alias": "marketing",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "marketing",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about marketing.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_medical_genetics": {
+      "task": "mmlu_medical_genetics",
+      "task_alias": "medical_genetics",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "medical_genetics",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about medical genetics.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_miscellaneous": {
+      "task": "mmlu_miscellaneous",
+      "task_alias": "miscellaneous",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "miscellaneous",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about miscellaneous.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_moral_disputes": {
+      "task": "mmlu_moral_disputes",
+      "task_alias": "moral_disputes",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "moral_disputes",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about moral disputes.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_moral_scenarios": {
+      "task": "mmlu_moral_scenarios",
+      "task_alias": "moral_scenarios",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "moral_scenarios",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about moral scenarios.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_nutrition": {
+      "task": "mmlu_nutrition",
+      "task_alias": "nutrition",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "nutrition",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about nutrition.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_philosophy": {
+      "task": "mmlu_philosophy",
+      "task_alias": "philosophy",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "philosophy",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about philosophy.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_prehistory": {
+      "task": "mmlu_prehistory",
+      "task_alias": "prehistory",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "prehistory",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about prehistory.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_professional_accounting": {
+      "task": "mmlu_professional_accounting",
+      "task_alias": "professional_accounting",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "professional_accounting",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about professional accounting.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_professional_law": {
+      "task": "mmlu_professional_law",
+      "task_alias": "professional_law",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "professional_law",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about professional law.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_professional_medicine": {
+      "task": "mmlu_professional_medicine",
+      "task_alias": "professional_medicine",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "professional_medicine",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about professional medicine.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_professional_psychology": {
+      "task": "mmlu_professional_psychology",
+      "task_alias": "professional_psychology",
+      "group": "mmlu_social_sciences",
+      "group_alias": "social_sciences",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "professional_psychology",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about professional psychology.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_public_relations": {
+      "task": "mmlu_public_relations",
+      "task_alias": "public_relations",
+      "group": "mmlu_social_sciences",
+      "group_alias": "social_sciences",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "public_relations",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about public relations.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_security_studies": {
+      "task": "mmlu_security_studies",
+      "task_alias": "security_studies",
+      "group": "mmlu_social_sciences",
+      "group_alias": "social_sciences",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "security_studies",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about security studies.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_sociology": {
+      "task": "mmlu_sociology",
+      "task_alias": "sociology",
+      "group": "mmlu_social_sciences",
+      "group_alias": "social_sciences",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "sociology",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about sociology.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_us_foreign_policy": {
+      "task": "mmlu_us_foreign_policy",
+      "task_alias": "us_foreign_policy",
+      "group": "mmlu_social_sciences",
+      "group_alias": "social_sciences",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "us_foreign_policy",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about us foreign policy.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_virology": {
+      "task": "mmlu_virology",
+      "task_alias": "virology",
+      "group": "mmlu_other",
+      "group_alias": "other",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "virology",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about virology.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    },
+    "mmlu_world_religions": {
+      "task": "mmlu_world_religions",
+      "task_alias": "world_religions",
+      "group": "mmlu_humanities",
+      "group_alias": "humanities",
+      "dataset_path": "hails/mmlu_no_train",
+      "dataset_name": "world_religions",
+      "test_split": "test",
+      "fewshot_split": "dev",
+      "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+      "doc_to_target": "answer",
+      "doc_to_choice": [
+        "A",
+        "B",
+        "C",
+        "D"
+      ],
+      "description": "The following are multiple choice questions (with answers) about world religions.\n\n",
+      "target_delimiter": " ",
+      "fewshot_delimiter": "\n\n",
+      "fewshot_config": {
+        "sampler": "first_n"
+      },
+      "metric_list": [
+        {
+          "metric": "acc",
+          "aggregation": "mean",
+          "higher_is_better": true
+        }
+      ],
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "metadata": {
+        "version": 0.0
+      }
+    }
+  },
+  "versions": {
+    "mmlu": "N/A",
+    "mmlu_abstract_algebra": "Yaml",
+    "mmlu_anatomy": "Yaml",
+    "mmlu_astronomy": "Yaml",
+    "mmlu_business_ethics": "Yaml",
+    "mmlu_clinical_knowledge": "Yaml",
+    "mmlu_college_biology": "Yaml",
+    "mmlu_college_chemistry": "Yaml",
+    "mmlu_college_computer_science": "Yaml",
+    "mmlu_college_mathematics": "Yaml",
+    "mmlu_college_medicine": "Yaml",
+    "mmlu_college_physics": "Yaml",
+    "mmlu_computer_security": "Yaml",
+    "mmlu_conceptual_physics": "Yaml",
+    "mmlu_econometrics": "Yaml",
+    "mmlu_electrical_engineering": "Yaml",
+    "mmlu_elementary_mathematics": "Yaml",
+    "mmlu_formal_logic": "Yaml",
+    "mmlu_global_facts": "Yaml",
+    "mmlu_high_school_biology": "Yaml",
+    "mmlu_high_school_chemistry": "Yaml",
+    "mmlu_high_school_computer_science": "Yaml",
+    "mmlu_high_school_european_history": "Yaml",
+    "mmlu_high_school_geography": "Yaml",
+    "mmlu_high_school_government_and_politics": "Yaml",
+    "mmlu_high_school_macroeconomics": "Yaml",
+    "mmlu_high_school_mathematics": "Yaml",
+    "mmlu_high_school_microeconomics": "Yaml",
+    "mmlu_high_school_physics": "Yaml",
+    "mmlu_high_school_psychology": "Yaml",
+    "mmlu_high_school_statistics": "Yaml",
+    "mmlu_high_school_us_history": "Yaml",
+    "mmlu_high_school_world_history": "Yaml",
+    "mmlu_human_aging": "Yaml",
+    "mmlu_human_sexuality": "Yaml",
+    "mmlu_humanities": "N/A",
+    "mmlu_international_law": "Yaml",
+    "mmlu_jurisprudence": "Yaml",
+    "mmlu_logical_fallacies": "Yaml",
+    "mmlu_machine_learning": "Yaml",
+    "mmlu_management": "Yaml",
+    "mmlu_marketing": "Yaml",
+    "mmlu_medical_genetics": "Yaml",
+    "mmlu_miscellaneous": "Yaml",
+    "mmlu_moral_disputes": "Yaml",
+    "mmlu_moral_scenarios": "Yaml",
+    "mmlu_nutrition": "Yaml",
+    "mmlu_other": "N/A",
+    "mmlu_philosophy": "Yaml",
+    "mmlu_prehistory": "Yaml",
+    "mmlu_professional_accounting": "Yaml",
+    "mmlu_professional_law": "Yaml",
+    "mmlu_professional_medicine": "Yaml",
+    "mmlu_professional_psychology": "Yaml",
+    "mmlu_public_relations": "Yaml",
+    "mmlu_security_studies": "Yaml",
+    "mmlu_social_sciences": "N/A",
+    "mmlu_sociology": "Yaml",
+    "mmlu_stem": "N/A",
+    "mmlu_us_foreign_policy": "Yaml",
+    "mmlu_virology": "Yaml",
+    "mmlu_world_religions": "Yaml"
+  },
+  "n-shot": {
+    "mmlu": 0,
+    "mmlu_abstract_algebra": 0,
+    "mmlu_anatomy": 0,
+    "mmlu_astronomy": 0,
+    "mmlu_business_ethics": 0,
+    "mmlu_clinical_knowledge": 0,
+    "mmlu_college_biology": 0,
+    "mmlu_college_chemistry": 0,
+    "mmlu_college_computer_science": 0,
+    "mmlu_college_mathematics": 0,
+    "mmlu_college_medicine": 0,
+    "mmlu_college_physics": 0,
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+}

special_tokens_map.json

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+{
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+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
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+    "single_word": false
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+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.model

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+version https://git-lfs.github.com/spec/v1
+oid sha256:79452955be6b419a65984273a9f08af86042e1c2a75ee3ba989cbf620a133cc2
+size 2001107

tokenizer_config.json

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+{
+  "add_bos_token": false,
+  "add_eos_token": false,
+  "auto_map": {
+    "AutoTokenizer": [
+      "baichuan-inc/Baichuan2-7B-Base--tokenization_baichuan.BaichuanTokenizer",
+      null
+    ]
+  },
+  "bos_token": {
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+    "content": "<s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
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+  "clean_up_tokenization_spaces": false,
+  "eos_token": {
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+    "content": "</s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": true
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+  "model_max_length": 4096,
+  "pad_token": {
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+    "lstrip": false,
+    "normalized": true,
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+    "single_word": true
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+}