Update README.md

README.md

@@ -17,32 +17,46 @@ tags:
 - **f** = B (Boolean)  
 - **c** = 3 (third model in the series)
 
+
 It takes two numbers and predicts one of three relations:
 
 - `>` (greater)
+
 - `=` (equal)
+
 - `<` (less)
 
+
 Also supports string input in the format `x?y`.
 
 ## Model Details
 
-| Property              | Value                  |
-|-----------------------|------------------------|
-| Parameters            | ~1731                  |
+| Property              | Value                                  |
+|-----------------------|----------------------------------------|
+| Parameters            | ~1731                                  |
 | Input                 | two floats `(a, b)` or string `"a?b"` |
-| Output                | `<`, `=`, or `>`       |
+| Output                | `<`, `=`, or `>`                       |
 | Architecture          | small MLP (input features: `a, b, a-b`) |
-| Framework             | PyTorch + Safetensors  |
-| License               | CC-BY-SA-4.0           |
+| Framework             | PyTorch + Safetensors                  |
+| License               | CC-BY-SA-4.0                           |
+
+## Training Dynamics
+
+Here is the visualization of the model's training metrics (Loss and Accuracy):
+
+![Training Metrics](training_metrics.png)
 
 ## Intended Use
 
 - Extremely lightweight number comparison
+
 - Edge / constrained environments
+
 - Educational / experimental micro-models
+
 - Fun baseline for boolean tasks
 
+
 **Not intended for** high-precision scientific computing or production systems that require perfect floating-point equality handling.
 
 ## Example inference script
@@ -100,24 +114,26 @@ class PizdecB3(nn.Module):
 model = PizdecB3.from_pretrained("pizdecB3")
 
 # Usage
-print(model.predict(10, 5))       # >
-print(model.predict(3, 3))        # =
-print(model.predict_str("8?2"))   # >
+print(model.predict(10, 5))        # >
+print(model.predict(3, 3))         # =
+print(model.predict_str("8?2"))    # >
+
 ```
 
 ## Known Limitations
 
-- Struggles with very close floating-point numbers (e.g. `100` vs `99.9`, `7.0` vs `7.01`)
-- Exact equality on large floats can be unstable
-- No support for non-numeric input
-- Not suitable for high-precision comparison tasks
-- Performance degrades when numbers differ by less than ~0.01–0.05 depending on magnitude
+* Struggles with very close floating-point numbers (e.g. `100` vs `99.9`, `7.0` vs `7.01`)
+* Exact equality on large floats can be unstable
+* No support for non-numeric input
+* Not suitable for high-precision comparison tasks
+* Performance degrades when numbers differ by less than ~0.01–0.05 depending on magnitude
 
 ## Files
 
-- `model.safetensors` — model weights
-- `config.json` — basic config
+* `model.safetensors` — model weights
+* `config.json` — basic config
+* `training_metrics.png` — training visualization
 
 ---
 
-Part of the experimental **RaspizdAI** micro-model collection.
+Part of the experimental **RaspizdAI** micro-model collection.