Update README.md

README.md

@@ -25,7 +25,7 @@ LS-Micro is 3x smaller than LS-TIny (11M vs 31M), and has 3x less active paramet
 
 Pushing the limits of size to quality, LS-Micro-Base is a sparse 11.49M MoE model (A5.52M) pretrained on 5.7B tokens.
 Training at a speed of 255.6k tokens/s on a 5060ti 16GB, it offers an incredible training efficiency at ~2.9x faster tokens seen compared to LS2.5's 108M-A17M model.
-Fully trained in ~6 hours.
+Fully pretrained in ~6 hours.
 
 | **Model specs**      |        |
 |----------------------|--------|
@@ -35,7 +35,7 @@ Fully trained in ~6 hours.
 | Ngrams:              | 4.21M  |
 | Context length:      | 2048   |
 | **Pretrain details** |        |
-| Tokens seen:         | ~5.7M  |
+| Tokens seen:         | ~5.7B  |
 | GPU time (5060ti):   | 22310s |
 
 *Note that it was trained with a 16k vocab, so 3.15M of the 5.52M active parameters are embedding.