README.md

---
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: "Why is AI Ethics important? [SEP] 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"
---
# 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 [notebook](RewardModel.ipynb) 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 = "The field of AI Ethics delves deeply into the intricate ethical considerations that arise with respect to AI systems. This includes the role of humanity in creating and deploying these systems, as well as the conduct of machines themselves. Broadly speaking, AI Ethics can be divided into two major categories : concerns surrounding the morality of human actions in relation to creating and using AI, and concerns regarding the moral implications of machine behavior."
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: The field of AI Ethics delves deeply into the intricate ethical considerations that arise with respect to AI systems. This includes the role of humanity in creating and deploying these systems, as well as the conduct of machines themselves. Broadly speaking, AI Ethics can be divided into two major categories : concerns surrounding the morality of human actions in relation to creating and using AI, and concerns regarding the moral implications of machine behavior. Score: 4.777
>>>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: -11.582
```

## 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.

## License

The `RewardModel` is licensed under the Apache License, Version 2.0. See the [LICENSE](LICENSE) file for more details.