Detail	Value
Model Architecture	LlamaForCausalLM (Decoder-Only Transformer)
Parameter Count	~500M
Training Type	Trained from Scratch (Random Initialization)
Tokenizer	Custom BPE, Vocab Size 32,000
Sequence Length	4096 tokens
Attention Type	Grouped Query Attention (GQA)

Configuration Details

This model is a custom size and configuration based on Llama:

Parameter	Value
Number of Layers	24
Hidden Size (d)	1280
Intermediate Size ($\text{d}_{\text{ff}}$)	3456
Attention Heads	20 (Query) / 5 (Key/Value)
Activation Function	SiLU (`silu`)
Normalization	RMS Norm (`rms_norm_eps`: 1e-06)
Position Embeddings	Rotary Positional Embeddings (RoPE, `theta`: 10000)

Training data

Corpus: english-historical-corpus-1800-1875-15GB-sample (sample_5b_tokens)
863,087 documents, ~5.71B tokens, packed into 1,393,977 sequences of length 4096

Training

From scratch, 13,000 steps (~0.9 epoch), effective batch 96, LR 3e-4 (500 warmup, linear decay), AdamW fused, bf16+tf32, FlashAttention-2
1x H100 SXM 80GB, ~21h, final train loss ~2.9

Evaluation notes

Strong, consistent period style across registers (newspaper, sermon, diary, parliamentary, scientific).
No date leakage surfaced; date-seeded prompts stayed within 1800–1875.
OCR residue is the main corpus cleanup item: end-of-line hyphenation (ap-\npear) and character-confusion errors (deatli, lie for "he").
Weak on procedural/recipe text; topic drift over long generations (expected at this scale).

Usage

Model weights and tokenizer are in the final/ subfolder.

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
REPO = "haykgrigorian/TimeCapsuleLLM-English-1800-1875-v3-mini-eval"
tok = AutoTokenizer.from_pretrained(REPO, subfolder="final")
model = AutoModelForCausalLM.from_pretrained(REPO, subfolder="final", dtype=torch.bfloat16).eval()

Cost

This model was trained on an H100 SXM from RunPod

Total: $85

haykgrigorian/TimeCapsuleLLM-English-1800-1875-v3mini-eval1-500M

TimeCapsuleLLM — English 1800–1875 (v3 mini eval, 500M)

Model Overview

Configuration Details

Training data

Training

Evaluation notes

Usage

Cost

haykgrigorian/
TimeCapsuleLLM-English-1800-1875-v3mini-eval1-500M