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precision recall f1-score support
0 0.85 0.90 0.87 175
1 0.89 0.85 0.87 175
accuracy 0.87 350
macro avg 0.87 0.87 0.87 350
weighted avg 0.87 0.87 0.87 3501def format_input_classification(text):
2 input = f"""
3 You are examining written text content. Here is the text:
4 ************
5 [Text]: {text}
6 ************
7
8 Examine the text and determine whether the text is toxic or not. Toxicity is
9 defined as any comment that makes hateful statements, demeans or disparages
10 another user, uses inappropriate language, or threatens physical or emotional
11 violence. Please focus heavily on the concept of toxicity and do NOT mark
12 something toxic as non-toxic that is toxic.
13
14 Your classification must be single word followed by a reasoning as to why you chose
15 the classification, either "toxic" or "non-toxic".
16 "toxic" means that the text meets the definition of toxic.
17 "non-toxic" means the text does not contain any
18 words, sentiments or meaning that could be considered toxic.
19
20 After your classification, provide the reason for your classification.
21 """
22 return input
23
24
25text = format_input_classification("I could strangle him")
26messages = [
27 {"role": "user", "content": text}
28]
29
30pipe = pipeline(
31 "text-generation",
32 model=base_model,
33 model_kwargs={"attn_implementation": attn_implementation, "torch_dtype": torch.float16},
34 tokenizer=tokenizer,
35)| Model | Precision | Recall | F1 |
|---|---|---|---|
| Our Merged Model | 0.85 | 0.90 | 0.87 |
| GPT-4 | 0.91 | 0.91 | 0.91 |
| GPT-4 Turbo | 0.89 | 0.77 | 0.83 |
| Gemini Pro | 0.81 | 0.84 | 0.83 |
| GPT-3.5 Turbo | 0.93 | 0.83 | 0.87 |
| Palm | - | - | - |
| Claude V2 | - | - | - |
| [1] Scores from arize/phoenix |