slm-125m-base
125.8M-parameter decoder-only language model trained from scratch for legal, financial, and educational English text.
Training
- Architecture: 12-layer Llama-compatible decoder, hidden size 768, vocabulary 16,384
- Context length: 1,024 tokens
- Training data: 2.034B packed training tokens; 20.6M validation tokens
- Data mix: cleaned and deduplicated US case law, SEC filings, and FineWeb-Edu
- Optimization: AdamW, BF16, cosine learning-rate schedule, one epoch
- Hardware: 8 NVIDIA H100 GPUs
- Final validation loss: 2.3981
- Final validation perplexity: 11.00
- Reported GPU compute cost: approximately $10.60
This is a base model, not an instruction-tuned or safety-tuned assistant. Outputs may be inaccurate and should not be treated as legal or financial advice.