amos1088/gpt-oss-20b-relevance-ft-20250811_213108

gpt-oss-20b Document Relevance Classifier

This model was trained using standard fine-tuning for document relevance classification.

Training Configuration

• Base Model: openai/gpt-oss-20b
• Training Type: Standard Fine-tuning
• Learning Rate: 5e-06
• Batch Size: 32
• Epochs: 5
• Training Samples: 2000
• Validation Samples: 400

Performance Metrics

• Accuracy: 57.50%
• Yes Predictions: 47.5%
• No Predictions: 52.5%

Usage

from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel

# Load base model
model = AutoModelForCausalLM.from_pretrained("openai/gpt-oss-20b")
tokenizer = AutoTokenizer.from_pretrained("openai/gpt-oss-20b")

# Load adapter
model = PeftModel.from_pretrained(model, "amos1088/gpt-oss-20b-relevance-ft-20250811_213108")

Training Date

2025-08-11 21:31:08 UTC