description: <p><strong><span style="color:rgb(255, 255, 255)">Beatrice Egli</span></strong><span style="color:rgb(255, 255, 255)"> (born 21 June 1988) is a Swiss </span><a target="_blank" rel="ugc" href="https://en.wikipedia.org/wiki/Pop_music"><span style="color:rgb(255, 255, 255)">pop</span></a><span style="color:rgb(255, 255, 255)"> and </span><a target="_blank" rel="ugc" href="https://en.wikipedia.org/wiki/Schlager_music"><span style="color:rgb(255, 255, 255)">Schlager</span></a><span style="color:rgb(255, 255, 255)"> singer. She is the winner of </span><a target="_blank" rel="ugc" href="https://en.wikipedia.org/wiki/Deutschland_sucht_den_Superstar_(season_10)"><span style="color:rgb(255, 255, 255)">season 10</span></a><span style="color:rgb(255, 255, 255)"> of the German music competition "</span><a target="_blank" rel="ugc" href="https://en.wikipedia.org/wiki/Deutschland_sucht_den_Superstar"><em><span style="color:rgb(255, 255, 255)">Deutschland sucht den Superstar"</span></em></a><span style="color:rgb(255, 255, 255)">.</span></p><p></p><p></p><p>ADetailer recommended in most situations</p><p></p><p>The LORA was trained in 1 epoch, and then resuming the training with the network weights of the previous versions 7 times. I don't know if that's the same as 7 epochs.</p><p></p><p>The dataset were 84 HQ images mostly from the past 4 years, auto-tagged with WD14 captioning and additional manual tagging.</p><p></p><p>Base Model: sd_xl_base_1.0.safetensors</p><p></p><p>Some more training parameters I changed from their standards:</p><p>resolution = "1024,1024"</p><p>save_precision = "bf16"</p><p>mixed_precision = "bf16"</p><p>min_snr_gamma = 5</p><p>network_dim = 64</p><p>network_alpha = 32</p><p>bucket_reso_steps = 32</p><p>lr_scheduler = "cosine_with_restarts"</p><p>lr_scheduler_num_cycles = 3</p><p>noise_offset = 0.1</p><p>optimizer_type = "Adafactor"</p>
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