Update README.md

README.md

@@ -12,7 +12,6 @@ tags:
 - games
 - elite
 - lichess
-- twic
 - tokenized
 size_categories:
 - 1M<n<10M
@@ -20,29 +19,22 @@ size_categories:
 
 # chess-elite-uci
 
-A transformer-ready dataset of ~8 million elite chess games, pre-tokenized in UCI notation with a deterministic 1977-token vocabulary. Built for training chess language models directly with no preprocessing required.
+A transformer-ready dataset of ~7.8 million elite chess games, pre-tokenized in UCI notation with a deterministic 1977-token vocabulary. Built for training chess language models directly with no preprocessing required.
 
 ## Dataset Summary
 | Field | Value |
 |---|---|
-| Total games | 7,972,071 |
-| Lichess Elite games | 7,805,503 |
-| TWIC OTB games | 166,568 |
-| Average sequence length | 94.3 tokens |
+| Total games | 7,805,503 |
+| Average sequence length | 94.24 tokens |
 | Max sequence length | 255 tokens |
 | Vocabulary size | 1,977 tokens |
-| Mean combined Elo | 5,212 (~2,606 per player) |
+| Mean combined Elo | 5,211 (~2,606 per player) |
 
 ## Sources
 
 **Lichess Elite Database** (June 2020 – November 2025)
 Games where both players are rated 2500+ vs 2300+ (2022 onwards: 2500+ vs 2300+; prior: 2400+ vs 2200+). Source: [database.nikonoel.fr](https://database.nikonoel.fr). Licensed CC0.
 
-**The Week in Chess (TWIC)** (Issues 920–1633, ~2013–2026)
-OTB classical tournament games where both players are FIDE-rated 2500+. Source: [theweekinchess.com](https://theweekinchess.com).
-
-Cross-dataset duplicates (3,173 games appearing in both sources) were removed using SHA1 hashing of move sequences. In these cases, Lichess takes priority on conflicts.
-
 ## Vocabulary
 
 The vocabulary contains **1,977 tokens** and is fully deterministic and enumerated from chess geometry, not derived from data. It will never produce OOV tokens for any legal chess game.
@@ -118,12 +110,11 @@ Games were filtered as follows before inclusion:
 
 | Type | Count | % |
 |---|---|---|
-| White checkmate | 1,702,751 | 21.4% |
-| White resignation | 2,000,000 | 25.1% |
-| Black checkmate | 1,702,752 | 21.4% |
-| Black resignation | 2,000,000 | 25.1% |
-| Forced draw | 400,000 | 5.0% |
-| TWIC (all types) | 166,568 | 2.1% |
+| White checkmate | 1,702,751 | 21.8% |
+| White resignation | 2,000,000 | 25.6% |
+| Black checkmate | 1,702,752 | 21.8% |
+| Black resignation | 2,000,000 | 25.6% |
+| Forced draw | 400,000 | 5.1% |
 
 ## Schema
 ```python
@@ -135,7 +126,7 @@ Games were filtered as follows before inclusion:
     "game_type":    string,       # "checkmate", "resignation", or "forced_draw"
     "pov":          string,       # "<W>" or "<B>"
     "terminal":     string,       # "<CHECKMATE>", "<RESIGN>", "<STALEMATE>", ...
-    "source":       string,       # "lichess" or "twic"
+    "source":       string,       # "lichess"
     "moves_uci":    string,       # space-separated UCI moves, human-readable
     "token_ids":    list[int32],  # encoded sequence, use this for training
     "ntp_mask":     list[int32],  # 1 = apply NTP loss, 0 = skip
@@ -162,10 +153,6 @@ tokens = [id_to_token[i] for i in row["token_ids"]]
 print(" ".join(tokens))
 # → <W> e2e4 e7e5 g1f3 b8c6 f1b5 ... <RESIGN>
 
-# Filter by source
-lichess_only = ds.filter(lambda x: x["source"] == "lichess")
-twic_only    = ds.filter(lambda x: x["source"] == "twic")
-
 # PyTorch DataLoader
 import torch
 from torch.utils.data import DataLoader
@@ -212,6 +199,5 @@ Terminal tokens are never generated during normal play. The game ends when the o
 ## Acknowledgements
 
 - [Lichess Elite Database](https://database.nikonoel.fr) by nikonoel — CC0
-- [The Week in Chess](https://theweekinchess.com) by Mark Crowther
 - [python-chess](https://python-chess.readthedocs.io) for move parsing and board state verification
 - [Modal](https://modal.com) for distributed compute