Model Card for test2-two-strategies

This model is a fine-tuned version of Qwen/Qwen2.5-0.5B-Instruct. It has been trained using TRL.

Model Details

Parameter	Value
Base Model	Qwen/Qwen2.5-0.5B-Instruct
Training Type	qlora
LoRA Rank (r)	N/A
LoRA Alpha	N/A
Strategies	SFT (1ep) → COT (1ep)
Batch Size	4

Training procedure

Training metrics are tracked locally with TensorBoard and MLflow.

Framework versions

• PEFT: 0.18.0
• TRL: 0.25.1
• Transformers: 4.57.3
• PyTorch: 2.9.1
• Datasets: 3.6.0
• Tokenizers: 0.22.1

Training Config

The full training configuration is available in training_config.yaml.

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("Tranium/test2-two-strategies")
tokenizer = AutoTokenizer.from_pretrained("Tranium/test2-two-strategies")

messages = [{"role": "user", "content": "Hello!"}]
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(text, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Training Infrastructure

• Platform: single_node
• GPU: auto-detect