en0_shared32k_d125m_ctx1024

d125m (110.3M parameters) on FineWeb sample (4 files), trained on RTX 3060 12GB (Home GPU). Started 21 Sep 2026, ended 21 Sep 2026.

Hypothesis

Our training pipeline, pointed at English web text (1.33B FineWeb tokens, 125M-class model), lands where a standard GPT-2 124M does at the same budget.

What we learned

Yes: FineWeb validation 1.1517. Measured the way the reference was, 1.1781 vs GPT-2 124M at 1.1755 (+0.2%): on the curve. The pipeline reproduces the field.

Scores

Lower is better on the headline.

FineWeb validation
1.15174
bits per byte · headline
Validation, in training
1.1781
bits per byte
Every published score of EN0
Test setEN0
FineWeb validation headline
About 15,000 FineWeb web documents never used in training, scored with a 1,024-token window.
1.15174
FineWeb validation, clean
The same documents minus any that overlap the training text.
1.16785
Pooled, five sets
All five English test sets pooled.
1.18255
WikiText-103 test
Good and featured Wikipedia articles, a standard language-modelling benchmark.
1.21418
enwik8 test
Raw Wikipedia markup; a character-level compression benchmark.
1.42598
text8 test
Lower-cased Wikipedia text with markup stripped; a character-level benchmark.
1.30127
FineWeb validation, during training
The validation number measured during training, the way the GPT-2 124M reference was measured, so the two can be compared.
1.1781

Bits per byte: how many bits the model needs, on average, to predict each byte of text it never saw in training. Lower is better, and it compares models with different tokenizers fairly, because every model is charged for the same bytes.

Curves

Training loss

Cross-entropy per token, by step. The first few percent of the run, far higher, run off the top; hover or the table has every value.

Held-out bits per byte

The validation split, evaluated during training, by step. Lower is better.

Throughput

Tokens per second, by step.

Model

Preset
d125m
Parameters
110,316,288
Outside embeddings
84,953,856
Layers · heads · width
12 · 12 · 768
Tokenizer
Shared unigram 32k

AdamW, learned positions, GELU, tied head, context 1024

Data

Slice
FineWeb sample (4 files)
Words
—
Training tokens
3,253,318,552
Passes
0.41 passes
Tokens seen
1,332,314,112

Compute

GPU
RTX 3060 12GB
Where
Home GPU
Steps
27,106 / 27,106
GPU hours
13.89
Cost
—
Spot restarts
—

Lineage

homed125m