This repo contains the global combined model at the final 10k-step checkpoint for the metadata localization project. It was trained from scratch on the project corpus, using the Llama 3.2 tokenizer and vocabulary.

Variant Metadata

Stage: pretrain
Family: global
Size: 500m
Metadata condition: without_metadata
Base model lineage: Trained from scratch; tokenizer/vocabulary from meta-llama/Llama-3.2-1B

Weights & Biases Provenance

Run name: 11/11/2025_13:18:50_combined_without_metadata_500m
Internal run URL: https://wandb.ai/iamshnoo/nanotron/runs/lqtre9sh
Note: the Weights & Biases workspace is private; public readers should use the summarized metrics and configuration below.
State: finished
Runtime: 75h 32m 59s

Run Summary

KPI/train_lm_loss: 2.3613
KPI/train_perplexity: 10.6047
KPI/val_loss: 2.404
KPI/val_perplexity: 11.0673
KPI/consumed_tokens/train: 41,943,040,000
_step: 10,000

Training Configuration

train_steps: 10,000
sequence_length: 2,048
micro_batch_size: 8
batch_accumulation_per_replica: 64
learning_rate: 0.003
min_decay_lr: 0.0003
checkpoint_interval: 1,000

Training Curves

Static plots below were exported from the private Weights & Biases run and embedded here for public access.

Train Loss

Validation Perplexity

Throughput

Project Context

This model is part of the metadata localization release. Related checkpoints and variants are grouped in the public Hugging Face collection Metadata Conditioned LLMs.

Training data source: News on the Web (NOW) Corpus
Project repository: https://github.com/iamshnoo/metadata_localization
Paper: https://arxiv.org/abs/2601.15236

Last synced: 2026-04-02 14:39:14 UTC

iamshnoo/combined_without_metadata_500m

combined_without_metadata_500m

Summary