Qwen2.5-1.5B-Nemotron-Math-52B-Mid-Train-8

Qwen2.5-1.5B-Nemotron-Math-52B-Mid-Train-8

This model is a mid-trained version of Qwen/Qwen2.5-1.5B on the NVIDIA Nemotron-CC-Math-v1 dataset (52B tokens, 4plus subset).

Training Details

• Base Model: Qwen/Qwen2.5-1.5B
• Training Data: Nemotron-CC-Math-v1 (4plus subset, ~52B tokens)
• Training Type: Continued pre-training (causal language modeling)
• Training Stage: Train 8 (final checkpoint of multi-stage mid-training)

Training Hyperparameters

• Learning rate: 2e-05
• Train batch size: 8 per device
• Gradient accumulation steps: 4
• Total train batch size: 128
• Distributed: 4 GPUs
• Optimizer: AdamW
• LR scheduler: Cosine with 5% warmup
• Epochs: 1.0
• Precision: bf16

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "salmannyu/Qwen2.5-1.5B-Nemotron-Math-52B-Mid-Train-8"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

Framework Versions

• Transformers: 4.57.1
• PyTorch: 2.6.0+cu124
• Datasets: 4.0.0
• LLaMA-Factory