fix trainSD21.json and advanced tweaking ema param names

doc/ADVANCED_TWEAKING.md

@@ -230,7 +230,7 @@ In this mode, the EMA model will be saved alongside the regular checkpoint from
 For more information, consult the [research paper](https://arxiv.org/abs/2101.08482) or continue reading the tuning notes below. 
 **Parameters:**  
 - `--ema_decay_rate`: Determines the EMA decay rate. It defines how much the EMA model is updated from training at each update. Values should be close to 1 but not exceed it. Activating this parameter triggers the EMA decay feature.
-- `--ema_decay_target`: Set the EMA decay target value within the (0,1) range. The `ema_decay_rate` is computed based on the relation: decay_rate to the power of (total_steps/decay_interval) equals decay_target. Enabling this parameter will override `ema_decay_rate` and will enable EMA feature.
+- `--ema_strength_target`: Set the EMA decay target value within the (0,1) range. The `ema_decay_rate` is computed based on the relation: decay_rate to the power of (total_steps/decay_interval) equals decay_target. Enabling this parameter will override `ema_decay_rate` and will enable EMA feature.
 - `--ema_update_interval`: Set the interval in steps between EMA updates. The update occurs at each optimizer step.  If you use grad_accum, actual update interval will be multipled by your grad_accum value.
 - `--ema_device`: Choose between `cpu` and `cuda` for EMA. Opting for 'cpu' takes around 4 seconds per update and uses approximately 3.2GB RAM, while 'cuda' is much faster but requires a similar amount of VRAM.
 - `--ema_sample_raw_training`: Activate to display samples from the trained model, mirroring conventional training. They will not be presented by default with EMA decay enabled.

trainSD21.json

@@ -44,7 +44,7 @@
   "load_settings_every_epoch": false,
   "min_snr_gamma": null,
   "ema_decay_rate": null,
-  "ema_decay_target": null,
+  "ema_strength_target": null,
   "ema_update_interval": null,
   "ema_device": null,
   "ema_sample_raw_training": false,