--- license: apache-2.0 datasets: - nicholasKluge/reward-aira-dataset language: - en metrics: - accuracy library_name: transformers pipeline_tag: text-classification tags: - reward model - alignment - preference model - RLHF widget: - text: "Who cares about AI Ethics? It's just a bunch of whining about humans making and using AI and bitching about what the machines do." example_title: "Bad Response" - text: "AI ethics is important for several compelling reasons:\n\n1.**Social Impact**: AI technologies are becoming increasingly integrated into various aspects of society, affecting everything from healthcare and education to finance and law enforcement. Ethical considerations ensure that AI systems contribute positively to society and minimize potential harm.\n\n2. **Bias and Fairness**: AI systems can inherit biases present in the data they are trained on, leading to unfair or discriminatory outcomes. Ethical considerations push for the development of unbiased algorithms that treat all individuals fairly, regardless of their background.\n\n3. **Transparency and Accountability**: Many AI systems operate as black boxes, making it difficult to understand how they arrive at their decisions. Ethical guidelines emphasize the importance of transparency, enabling users to comprehend the rationale behind AI-generated results and holding developers accountable for any negative consequences.\n\nIn summary, AI ethics is vital to ensure that artificial intelligence benefits society while respecting fundamental human rights, fairness, transparency, accountability, and the long-term well-being of humanity. It helps navigate the challenges posed by rapidly advancing AI technologies and guides their development in ways that align with our shared values." example_title: "Good Response" co2_eq_emissions: emissions: 0.08 source: CodeCarbon training_type: fine-tuning geographical_location: Singapore hardware_used: NVIDIA A100-SXM4-40GB --- # RewardModel The RewardModel is a [BERT](https://huggingface.co/bert-base-cased) model that can be used to score the quality of a completion for a given prompt. The model was trained with a dataset composed of `prompt`, `prefered_completions`, and `rejected_completions`. ## Details - **Size:** 109,038,209 parameters - **Dataset:** [Reward-Aira Dataset](https://huggingface.co/datasets/nicholasKluge/reward-aira-dataset) - **Language:** English - **Number of Training Steps:** 1200 - **Batch size:** 42 - **Optimizer:** `torch.optim.AdamW` - **Learning Rate:** 5e-5 - **GPU:** 1 NVIDIA A100-SXM4-40GB - **Emissions:** 0.08 KgCO2 (Singapore) - **Total Energy Consumption:** 0.16 kWh This repository has the [source code](https://github.com/Nkluge-correa/Aira) used to train this model. ## Usage Here's an example of how to use the RewardModel to score the quality of a response to a given prompt: ```python from transformers import AutoTokenizer, AutoModelForSequenceClassification import torch device = torch.device("cuda" if torch.cuda.is_available() else "cpu") tokenizer = AutoTokenizer.from_pretrained("nicholasKluge/RewardModel") rewardModel = AutoModelForSequenceClassification.from_pretrained("nicholasKluge/RewardModel") rewardModel.eval() rewardModel.to(device) # Define the question and response prompt = "Why is AI Ethics important?" response_good = "AI ethics is important for several compelling reasons:\n\n1.**Social Impact**: AI technologies are becoming increasingly integrated into various aspects of society, affecting everything from healthcare and education to finance and law enforcement. Ethical considerations ensure that AI systems contribute positively to society and minimize potential harm.\n\n2. **Bias and Fairness**: AI systems can inherit biases present in the data they are trained on, leading to unfair or discriminatory outcomes. Ethical considerations push for the development of unbiased algorithms that treat all individuals fairly, regardless of their background.\n\n3. **Transparency and Accountability**: Many AI systems operate as black boxes, making it difficult to understand how they arrive at their decisions. Ethical guidelines emphasize the importance of transparency, enabling users to comprehend the rationale behind AI-generated results and holding developers accountable for any negative consequences.\n\nIn summary, AI ethics is vital to ensure that artificial intelligence benefits society while respecting fundamental human rights, fairness, transparency, accountability, and the long-term well-being of humanity. It helps navigate the challenges posed by rapidly advancing AI technologies and guides their development in ways that align with our shared values." response_bad = "Who cares about AI Ethics? It's just a bunch of whining about humans making and using AI and bitching about what the machines do." # Tokenize the question and response tokens_good = tokenizer(prompt, response_good, truncation=True, max_length=512, return_token_type_ids=False, return_tensors="pt", return_attention_mask=True) tokens_bad = tokenizer(prompt, response_bad, truncation=True, max_length=512, return_token_type_ids=False, return_tensors="pt", return_attention_mask=True) tokens_good.to(device) tokens_bad.to(device) score_good = rewardModel(**tokens_good)[0].item() score_bad = rewardModel(**tokens_bad)[0].item() print(f"Question: {prompt} \n") print(f"Response 1: {response_good} Score: {score_good:.3f}") print(f"Response 2: {response_bad} Score: {score_bad:.3f}") ``` This will output the following: ```markdown Question: Why is AI Ethics important? >>>Response 1: AI ethics is important for several compelling reasons: 1.**Social Impact**: AI technologies are becoming increasingly integrated into various aspects of society, affecting everything from healthcare and education to finance and law enforcement. Ethical considerations ensure that AI systems contribute positively to society and minimize potential harm. 2. **Bias and Fairness**: AI systems can inherit biases present in the data they are trained on, leading to unfair or discriminatory outcomes. Ethical considerations push for the development of unbiased algorithms that treat all individuals fairly, regardless of their background. 3. **Transparency and Accountability**: Many AI systems operate as black boxes, making it difficult to understand how they arrive at their decisions. Ethical guidelines emphasize the importance of transparency, enabling users to comprehend the rationale behind AI-generated results and holding developers accountable for any negative consequences. In summary, AI ethics is vital to ensure that artificial intelligence benefits society while respecting fundamental human rights, fairness, transparency, accountability, and the long-term well-being of humanity. It helps navigate the challenges posed by rapidly advancing AI technologies and guides their development in ways that align with our shared values. Score: 12.011 >>>Response 2: Who cares about AI Ethics? It's just a bunch of whining about humans making and using AI and bitching about what the machines do. Score: -10.942 ``` ## Performance | Acc | [WebGPT](https://huggingface.co/datasets/openai/webgpt_comparisons) | |----------------------------------------------------------------------|---------------------------------------------------------------------| | [Aira-RewardModel](https://huggingface.co/nicholasKluge/RewardModel) | 55.02%* | * *Only considering comparisons of the `webgpt_comparisons` dataset that had a preferred option. ## Cite as 🤗 ```latex @misc{nicholas22aira, doi = {10.5281/zenodo.6989727}, url = {https://github.com/Nkluge-correa/Aira}, author = {Nicholas Kluge Corrêa}, title = {Aira}, year = {2023}, publisher = {GitHub}, journal = {GitHub repository}, } @phdthesis{kluge2024dynamic, title={Dynamic Normativity}, author={Kluge Corr{\^e}a, Nicholas}, year={2024}, school={Universit{\"a}ts-und Landesbibliothek Bonn} } ``` ## License RewardModel is licensed under the Apache License, Version 2.0. See the [LICENSE](LICENSE) file for more details.