---
datasets:
- Anthropic/hh-rlhf
language:
- en
metrics:
- accuracy
---
- base model: [PY007/TinyLlama-1.1B-intermediate-step-480k-1T](https://huggingface.co/PY007/TinyLlama-1.1B-intermediate-step-480k-1T)
- helpful accuracy: 68.37
- harmless accuracy: 69.71
- total accuracy: 68.74
- 1011-hh-rlhf-1.1b-128-1e-5-epoch-1 (1024 sequence length)

usage:

```
from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("heegyu/1011-hh-rlhf-1.1b-128-1e-5-epoch-1")
model = AutoModelForSequenceClassification.from_pretrained("heegyu/1011-hh-rlhf-1.1b-128-1e-5-epoch-1")

text = """Human: Hi, how are you today?

Assistant: It's so nice!"""

inputs = tokenizer(text, return_tensors="pt")
print(model(**inputs).logits)
# tensor([[0.4552]])

text = """Human: Hi, how are you today?

Assistant: It's so nice!

Human: Really? I'm not so good today

Assistant: Haha!! That's too bad!"""

inputs = tokenizer(text, return_tensors="pt")
print(model(**inputs).logits)
# tensor([[0.0179]])
```