Update README.md

README.md

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   <h3 style="font-size:24px; font-family: Arial, Helvetica, sans-serif; font-weight: bold; margin:20px 0; color: #222;">Technical Details</h3>
   <h4 style="font-size:20px; font-family: Arial, Helvetica, sans-serif; font-weight: bold; margin:20px 0; color: #222;">Model Training</h4>
   <p style="font-size: 18px; color: #666;">
-    MyneFactoryBase was trained using 23,088 samples from Yande.re. File captions were generated using 3 iterations of WD1.4 tagger to ensure maximum identification of objects within the training data. A second captioning run was done using one tagger with a reduced threshold to produce shorter captions for later use. The model was trained using the NAI model as the base, and the Adam optimizer was used with a manually set maximum learning rate and cosine decay. Training was done on an RTX 4090 with a batch size of 4, utilizing DDIM sample scheduler and DDPM noise scheduler with mix precision.
+    MyneFactoryBase was trained using ~18000 high scored samples from Yande.re and ~5000 high scored samples from Konachan. File captions were generated using 3 iterations of WD1.4 tagger to ensure maximum identification of objects within the training data. A second captioning run was done using one tagger with a reduced threshold to produce shorter captions for later use. The model was trained using the NAI model as the base, and the Adam optimizer was used with a manually set maximum learning rate and cosine decay. Training was done on an RTX 4090 with a batch size of 4, utilizing DDIM sample scheduler and DDPM noise scheduler with mix precision.
   </p>
   <h4 style="font-size:20px; font-family: Arial, Helvetica, sans-serif; font-weight: bold; margin:20px 0; color: #222;">Text Encoder Training</h4>
   <p style="font-size: 18px; color: #666;">