medium v2
- preset: medium
- training corpus: data/medium (see corpus_index.md / corpus_stats.txt)
- trained: 2026-07-03 16:04 (checkpoint mtime)
- training wall-clock: unknown
- final val loss: 1.2278 (iter 7999)
- parameters: 25.44M | vocab 97
Training hyperparameters
| param | value |
|---|---|
| block_size | 256 |
| n_embd | 512 |
| n_head | 8 |
| n_layer | 8 |
| dropout | 0.0 |
| batch_size | 40 |
| max_iters | 8000 |
| eval_interval | 500 |
| eval_iters | 80 |
| learning_rate | 0.0003 |
| vocab_size | 97 |
Validation curve
| step | train | val |
|---|
Reproducing the corpus
corpus_index.md lists every author and work in the training set; re-run python -m corpus add-author / add-topic per that index and make finalize to rebuild an equivalent corpus.