Update README.md

README.md

@@ -297,6 +297,116 @@ Every config also has a test set (for validation) of 1% the total size of the da
 
 Wikipedia and CulturaX were suffled before merging and the teset set creation was also shuffled. Priority is given to Wikipedia to prioritize knowledge-content, so the smaller configs will consist exclusively of Wikipedia and for the larger configs we augment with CulturaX. Every config builds further on the previous, so this means that every config contains the same data as the smaller ones and more HOWEVER their train/test splits are not the same, so test set of one config may overlap with samples for another training set. This is usually not a problem but just be aware that you do not train on one config's training set and test with another config's test set.
 
+## Configs
+
+### 10k -- 79 samples -- 10,087 tokens
+- ratio_wikipedia: 100.00%
+- total_num_tokens: 10,087
+- train_num_tokens: 9,205
+- test_num_tokens: 882
+- total_num_samples: 79
+- train_num_samples: 78
+- test_num_samples: 1
+
+### 100k -- 1,057 samples -- 100,075 tokens
+- ratio_wikipedia: 100.00%
+- total_num_tokens: 100,075
+- train_num_tokens: 98,044
+- test_num_tokens: 2,031
+- total_num_samples: 1,057
+- train_num_samples: 1,047
+- test_num_samples: 10
+
+### 1M -- 10,802 samples -- 1,000,239 tokens
+- ratio_wikipedia: 100.00%
+- total_num_tokens: 1,000,239
+- train_num_tokens: 991,119
+- test_num_tokens: 9,120
+- total_num_samples: 10,802
+- train_num_samples: 10,694
+- test_num_samples: 108
+
+### 10M -- 141,263 samples -- 10,000,022 tokens
+- ratio_wikipedia: 100.00%
+- total_num_tokens: 10,000,022
+- train_num_tokens: 9,874,772
+- test_num_tokens: 125,250
+- total_num_samples: 141,263
+- train_num_samples: 139,851
+- test_num_samples: 1,412
+
+### 100M -- 1,028,484 samples -- 100,000,047 tokens
+- ratio_wikipedia: 100.00%
+- total_num_tokens: 100,000,047
+- train_num_tokens: 99,013,372
+- test_num_tokens: 986,675
+- total_num_samples: 1,028,484
+- train_num_samples: 1,018,200
+- test_num_samples: 10,284
+
+### 1B -- 5,153,898 samples -- 1,000,000,187 tokens
+- ratio_wikipedia: 61.21%
+- total_num_tokens: 1,000,000,187
+- train_num_tokens: 989,990,190
+- test_num_tokens: 10,009,997
+- total_num_samples: 5,153,898
+- train_num_samples: 5,102,360
+- test_num_samples: 51,538
+
+### 5B -- 20,833,009 samples -- 5,000,000,076 tokens
+- ratio_wikipedia: 25.35%
+- total_num_tokens: 5,000,000,076
+- train_num_tokens: 4,984,493,654
+- test_num_tokens: 15,506,422
+- total_num_samples: 20,833,009
+- train_num_samples: 20,769,009
+- test_num_samples: 64,000
+
+### 10B -- 40,240,566 samples -- 10,000,000,115 tokens
+- ratio_wikipedia: 18.41%
+- total_num_tokens: 10,000,000,115
+- train_num_tokens: 9,984,156,828
+- test_num_tokens: 15,843,287
+- total_num_samples: 40,240,566
+- train_num_samples: 40,176,566
+- test_num_samples: 64,000
+
+### 15B -- 59,648,123 samples -- 15,000,000,154 tokens
+- ratio_wikipedia: 15.98%
+- total_num_tokens: 15,000,000,154
+- train_num_tokens: 14,983,970,518
+- test_num_tokens: 16,029,636
+- total_num_samples: 59,648,123
+- train_num_samples: 59,584,123
+- test_num_samples: 64,000
+
+### 20B -- 79,055,679 samples -- 20,000,000,009 tokens
+- ratio_wikipedia: 14.75%
+- total_num_tokens: 20,000,000,009
+- train_num_tokens: 19,983,799,357
+- test_num_tokens: 16,200,652
+- total_num_samples: 79,055,679
+- train_num_samples: 78,991,679
+- test_num_samples: 64,000
+
+### 25B -- 98,463,236 samples -- 25,000,000,048 tokens
+- ratio_wikipedia: 14.00%
+- total_num_tokens: 25,000,000,048
+- train_num_tokens: 24,983,765,326
+- test_num_tokens: 16,234,722
+- total_num_samples: 98,463,236
+- train_num_samples: 98,399,236
+- test_num_samples: 64,000
+
+### 30B -- 117,870,793 samples -- 30,000,000,087 tokens
+- ratio_wikipedia: 13.50%
+- total_num_tokens: 30,000,000,087
+- train_num_tokens: 29,983,707,932
+- test_num_tokens: 16,292,155
+- total_num_samples: 117,870,793
+- train_num_samples: 117,806,793
+- test_num_samples: 64,000
+
 
 ## Filtering