eriksalt/reddit-rpg-rules-questions-classifier-lora

reddit-rpg-rules-questions-classifier (lora)

Binary text classifier fine-tuned with LoRA on a custom dataset. This model was trained to distinguish rules questions from other kinds of posts in rpg-related subreddits.

Model Details

• Base model: unsloth/Qwen2.5-7B-Instruct-bnb-4bit
• LoRA rank: 16

Dataset

• Dataset: eriksalt/reddit-rpg-rules-question-classification
• Training split: train
• Test split: test
• Validation split: validation
• Positive class: Question

Training Configuration

• Epochs: 1.0
• Batch size (per device): 32
• Gradient accumulation steps: 2
• Learning rate: 0.00055
• Max sequence length: 1536

Pre-Training Metrics

Metric	Value
accuracy	0.794392523364486
precision	0.5
recall	0.8409090909090909
f1	0.6271186440677967
total_seen	214

Post-Training Metrics

Metric	Value
accuracy	0.9065420560747663
precision	0.9285714285714286
recall	0.5909090909090909
f1	0.7222222222222223
total_seen	214

Usage

LoRA with Python (PEFT)

from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer

base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-7B-Instruct-bnb-4bit")
model = PeftModel.from_pretrained(base_model, "eriksalt/reddit-rpg-rules-questions-classifier-lora")
tokenizer = AutoTokenizer.from_pretrained("eriksalt/reddit-rpg-rules-questions-classifier-lora")