Update README.md

README.md

@@ -1,37 +1,41 @@
 ---
-title: cha
-emoji: 🤖 
-colorFrom: yellow
-colorTo: red
-sdk: gradio
-app_file: app.py
-pinned: false
+library_name: keras
 ---
-# Configuration
-`title`: _string_
-Display title for the Space
-`emoji`: _string_
-Space emoji (emoji-only character allowed)
-`colorFrom`: _string_
-Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
-`colorTo`: _string_
-Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
-`sdk`: _string_
-Can be either `gradio`, `streamlit`, or `static`
-`sdk_version` : _string_
-Only applicable for `streamlit` SDK.  
-See [doc](https://hf.co/docs/hub/spaces) for more info on supported versions.
-
-`app_file`: _string_
-Path to your main application file (which contains either `gradio` or `streamlit` Python code, or `static` html code).
-Path is relative to the root of the repository.
-
-`models`: _List[string]_
-HF model IDs (like "gpt2" or "deepset/roberta-base-squad2") used in the Space.
-Will be parsed automatically from your code if not specified here.
-
-`datasets`: _List[string]_
-HF dataset IDs (like "common_voice" or "oscar-corpus/OSCAR-2109") used in the Space.
-Will be parsed automatically from your code if not specified here.
-`pinned`: _boolean_
-Whether the Space stays on top of your list.
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+
+| Hyperparameters | Value |
+| :-- | :-- |
+| name | Adam |
+| weight_decay | None |
+| clipnorm | None |
+| global_clipnorm | None |
+| clipvalue | None |
+| use_ema | False |
+| ema_momentum | 0.99 |
+| ema_overwrite_frequency | None |
+| jit_compile | False |
+| is_legacy_optimizer | False |
+| learning_rate | 0.0010000000474974513 |
+| beta_1 | 0.9 |
+| beta_2 | 0.999 |
+| epsilon | 1e-07 |
+| amsgrad | False |
+| training_precision | float32 |
+