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Model: LLM-Research/digital-socrates-7b
Source: Original Platform

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README.md

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+---
+language: en
+license: apache-2.0
+library_name: transformers
+model-index:
+- name: digital-socrates-7b
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: AI2 Reasoning Challenge (25-Shot)
+      type: ai2_arc
+      config: ARC-Challenge
+      split: test
+      args:
+        num_few_shot: 25
+    metrics:
+    - type: acc_norm
+      value: 54.44
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=allenai/digital-socrates-7b
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: HellaSwag (10-Shot)
+      type: hellaswag
+      split: validation
+      args:
+        num_few_shot: 10
+    metrics:
+    - type: acc_norm
+      value: 75.99
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=allenai/digital-socrates-7b
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU (5-Shot)
+      type: cais/mmlu
+      config: all
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 51.41
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=allenai/digital-socrates-7b
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: TruthfulQA (0-shot)
+      type: truthful_qa
+      config: multiple_choice
+      split: validation
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: mc2
+      value: 44.88
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=allenai/digital-socrates-7b
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: Winogrande (5-shot)
+      type: winogrande
+      config: winogrande_xl
+      split: validation
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 73.09
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=allenai/digital-socrates-7b
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GSM8k (5-shot)
+      type: gsm8k
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 17.89
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=allenai/digital-socrates-7b
+      name: Open LLM Leaderboard
+---
+
+This is the Digital Socrates 7B (DS-7B) model described in our paper: <b>Digital Socrates: Evaluating LLMs through explanation critiques</b> (ACL Anthology link: https://aclanthology.org/2024.acl-long.302, arXiv link: https://arxiv.org/abs/2311.09613). 
+
+The recommended, better performing 13B model can be found at https://huggingface.co/allenai/digital-socrates-13b
+
+The DS-7B model is a fine-tuned version of [Llama-2-7b-Chat](https://huggingface.co/meta-llama/Llama-2-7b-chat), please 
+review its [guidelines](https://huggingface.co/meta-llama/Llama-2-7b-chat/blob/main/USE_POLICY.md) and 
+[licensing](https://huggingface.co/meta-llama/Llama-2-7b-chat#model-details) before use.
+  
+  
+  
+# What is Digital Socrates?
+Digital Socrates is an open-source, automatic explanation-critiquing model. It is useful for revealing insights about student 
+models by examining their reasoning chains. The use of Digital Socrates allows for nuanced, interpretable automatic 
+evaluation of explanations without expensive API calls or human annotations.
+
+While LLMs can provide reasoned explanations along with their answers, the nature and
+quality of those explanations are still poorly understood. In response, our goal is to define a detailed way of characterizing the 
+explanation capabilities of modern models and to create a nuanced, interpretable explanation
+evaluation tool that can generate such characterizations automatically.
+
+Given a **question** (together with the multiple-choice options and gold answer),
+```commandline
+When Dennis operates his lawnmower, he notices the engine makes a lot of noise. He also notices that the engine gets very hot. Which best describes the heat and noise generated from the lawnmower? 
+(A) a change in phase 
+(B) thermal expansion 
+(C) an increase in entropy 
+(D) mechanical advantage 
+
+Answer sheet: (C)
+```
+ as well as a student model explanation and answer,
+```
+1) The question states that the lawnmower engine makes a lot of noise.
+2) The question states that the lawnmower engine gets very hot.
+3) Noise and heat are both forms of energy.
+4) The noise and heat generated from the lawnmower are a result of the conversion of energy from the fuel to mechanical energy.
+
+Answer: (D)
+```
+
+Digital Socrates gives a **critique of the model-generated explanation** that provides localized feedback on the 
+most significant flaw (if any) in the explanation, suggestions to address the identified flaw, as well as a numeric rating indicating the explanation quality:
+```
+The explanation states or suggests the following:
+* Main flaw (standalone statement): "The noise and heat generated from the lawnmower are a result of the conversion of energy from the fuel to mechanical energy."
+* Dimension: incorrect_information
+
+Consider these points for revising the explanation:
+* General: Remember that noise and heat are not forms of energy. They are byproducts of energy conversion.
+* Specific: In this case, the noise and heat generated by the lawnmower are not a result of the conversion of energy from the fuel to mechanical energy. They are byproducts of the combustion process.
+
+Explanation score: 2
+```
+
+
+Remarkably, despite being orders of magnitude smaller than GPT-4, our Digital Socrates models are 
+capable of generating critiques close to GPT-4 critiques in terms of human rating and other 
+quantitative measures (correlation of explanation scores given and error category matches). 
+Through quantitative and qualitative analysis, we demonstrate how Digital Socrates is useful for 
+revealing insights about student models by examining their reasoning chains.
+
+We invite you to try out Digital Socrates for your own application!
+    
+    
+    
+# How to use Digital Socrates?
+We provide a quick example of how you can try out Digital Socrates with just a few lines of code:
+
+'DSCritiqueBank-V1' used below can be downloaded from our [dataset page](https://allenai.org/data/digital-socrates).
+```
+import json
+from transformers import AutoTokenizer, AutoModelForCausalLM
+# Load model and tokenizer
+model_path = "allenai/digital-socrates-7b"
+model = AutoModelForCausalLM.from_pretrained(model_path).to("cuda:0")
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+
+# Define input data
+question = "When Dennis operates his lawnmower, he notices the engine makes a lot of noise. He also notices that the engine gets very hot. Which best describes the heat and noise generated from the lawnmower? (A) a change in phase (B) thermal expansion (C) an increase in entropy (D) mechanical advantage"
+explanation = "1) The question states that the lawnmower engine makes a lot of noise.\n2) The question states that the lawnmower engine gets very hot.\n3) Noise and heat are both forms of energy.\n4) The noise and heat generated from the lawnmower are a result of the conversion of energy from the fuel to mechanical energy."
+answerkey = "C"
+predictedanswer = "D"
+
+# construct prompt (Llama conventions)
+with open("../DSCritiqueBank-V1/DSCB-prompts.json") as file:
+    prompts = json.load(file)
+
+system_prompt = prompts['digital_socrates_v1']['system']
+user_prompt = prompts['digital_socrates_v1']['main'].replace("[[QUESTION]]", question).replace("[[EXPLANATION]]", explanation).replace("[[PREDICTEDANSWER]]", predictedanswer).replace("[[ANSWERKEY]]", answerkey)
+
+full_prompt = f"[INST] <<SYS>>\n{system_prompt}\n<</SYS>{user_prompt} [/INST]\n\n"
+
+# Run model
+input_ids = tokenizer.encode(full_prompt, return_tensors="pt").to("cuda:0")
+output = model.generate(input_ids, max_new_tokens=512, temperature=0)
+res = tokenizer.batch_decode(output, skip_special_tokens=True)
+```
+Print the output:
+```
+>>> print(res[0].split("[/INST]")[-1])
+
+The explanation states or suggests the following:
+* Main flaw (standalone statement): "The noise and heat generated from the lawnmower are a result of the conversion of energy from the fuel to mechanical energy."
+* Dimension: incorrect_information
+
+Consider these points for revising the explanation:
+* General: Remember that noise and heat are not forms of energy. They are byproducts of energy conversion.
+* Specific: In this case, the noise and heat generated by the lawnmower are not a result of the conversion of energy from the fuel to mechanical energy. They are byproducts of the combustion process.
+
+Explanation score: 2
+```
+
+
+    
+# More details about Digital Socrates ...
+For more details about Digital Socrates, please refer to our:
+* 📄Paper: https://arxiv.org/abs/2311.09613
+* 💻Dataset: https://allenai.org/data/digital-socrates
+
+
+# Citation
+
+```
+@inproceedings{gu-etal-2024-digital,
+    title = "Digital Socrates: Evaluating {LLM}s through Explanation Critiques",
+    author = "Gu, Yuling  and
+      Tafjord, Oyvind  and
+      Clark, Peter",
+    editor = "Ku, Lun-Wei  and
+      Martins, Andre  and
+      Srikumar, Vivek",
+    booktitle = "Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
+    month = aug,
+    year = "2024",
+    address = "Bangkok, Thailand",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2024.acl-long.302",
+    pages = "5559--5586",
+}
+```
+
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_allenai__digital-socrates-7b)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |52.95|
+|AI2 Reasoning Challenge (25-Shot)|54.44|
+|HellaSwag (10-Shot)              |75.99|
+|MMLU (5-Shot)                    |51.41|
+|TruthfulQA (0-shot)              |44.88|
+|Winogrande (5-shot)              |73.09|
+|GSM8k (5-shot)                   |17.89|
+

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+  "vocab_size": 32001
+}

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+    "model.layers.9.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
+    "model.layers.9.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
+    "model.layers.9.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
+    "model.layers.9.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
+    "model.layers.9.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
+    "model.layers.9.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
+    "model.layers.9.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
+    "model.norm.weight": "pytorch_model-00003-of-00003.bin"
+  }
+}

special_tokens_map.json

@@ -0,0 +1,12 @@
+{
+  "additional_special_tokens": [
+    "<unk>",
+    "<s>",
+    "</s>",
+    "<pad>"
+  ],
+  "bos_token": "<s>",
+  "eos_token": "</s>",
+  "pad_token": "<pad>",
+  "unk_token": "<unk>"
+}

tokenizer_config.json

@@ -0,0 +1,57 @@
+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32000": {
+      "content": "<pad>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [
+    "<unk>",
+    "<s>",
+    "</s>",
+    "<pad>"
+  ],
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "legacy": false,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<pad>",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "tokenizer_file": null,
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false,
+  "use_fast": false
+}