From fd869eba7a3956bc2a74f62f06c6d81964b42915 Mon Sep 17 00:00:00 2001
From: kalomazing <155201551+kalomazing@users.noreply.github.com>
Date: Thu, 7 Mar 2024 01:59:52 +0000
Subject: [PATCH] easygui update
---
assets/RVC/Cloud/EasyGUI.md | 26 +++++++++++++++---
assets/RVC/Cloud/easygui-img/dataset.png | Bin 0 -> 11457 bytes
assets/RVC/Cloud/easygui-img/ui-t-cache.png | Bin 0 -> 14635 bytes
assets/RVC/Cloud/easygui-img/ui-t-gpu.png | Bin 0 -> 4698 bytes
.../RVC/Cloud/easygui-img/ui-t-saverate.png | Bin 0 -> 7719 bytes
5 files changed, 22 insertions(+), 4 deletions(-)
create mode 100644 assets/RVC/Cloud/easygui-img/dataset.png
create mode 100644 assets/RVC/Cloud/easygui-img/ui-t-cache.png
create mode 100644 assets/RVC/Cloud/easygui-img/ui-t-gpu.png
create mode 100644 assets/RVC/Cloud/easygui-img/ui-t-saverate.png
diff --git a/assets/RVC/Cloud/EasyGUI.md b/assets/RVC/Cloud/EasyGUI.md
index e170b377..8d825c3a 100644
--- a/assets/RVC/Cloud/EasyGUI.md
+++ b/assets/RVC/Cloud/EasyGUI.md
@@ -38,7 +38,7 @@ visibility: private
#### 1. Prepare dataset (optional)
- If you're going to train models, go to Google Drive, make a new folder & place your dataset in it.
-
+
***
######
@@ -149,9 +149,9 @@ a. Press the upload box & select your dataset. Or simply drag & drop.
-b. Once it's done uploading, press **Process Data**. It'll finish when the logs say ``Process data``.
+b. Once it's done uploading, press **Process Data**. It'll finish when the logs say ``end preprocess``.
-
+
***
#### 4. Feature extraction
@@ -163,7 +163,25 @@ b. Once it's done uploading, press **Process Data**. It'll finish when the logs
- But since we'll use [TensorBoard](https://aihubdocs.github.io/en/rvc/resources/epochs-overtraining--tensorboard/#tensorboard), use an arbitrarily large value like `1000`
-
+
+
+***
+#### 6. Save frequency
+- Rate at which the model will be saved, based on the [epochs](https://aihubdocs.github.io/en/rvc/resources/epochs-overtraining--tensorboard/). The saved models are known as the "checkpoints".
+
+- If you are a newbie, leave it at `15`.
+
+- E.g: with a value of ``10``, it will be saved after the epoch 10, 20, 30, etc.
+***
+#### 7. Batch size
+- If you are a newbie, use `8`. But in case your dataset is short (around 2 minutes or less), use `4`.
+***
+#### 8. Cache
+- For a faster training, set **Cache all training sets to GPU memory** as yes, if your dataset is less 10 minutes.
+
+***
+#### 9. Train INDEX
+- Press ´Train feature index´ to get the model's [.INDEX]() file.
***
## Without UI
diff --git a/assets/RVC/Cloud/easygui-img/dataset.png b/assets/RVC/Cloud/easygui-img/dataset.png
new file mode 100644
index 0000000000000000000000000000000000000000..ecacd60c048eb9e1875752ff7cf09f8ddd5dd0c3
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