Update README.md

README.md

@@ -57,40 +57,35 @@ The *SpeechT5 TTS Technical Train2* is built on the *SpeechT5* architecture and
 
 The model was fine-tuned on a *custom dataset*, curated for enhancing TTS outputs. This dataset consists of various types of text that help the model generate more natural speech, making it suitable for TTS applications.
 
----
-
-## ⚙ Training Procedure
-
-### ⚙ *Hyperparameters*:
+### ⚙ *Hyperparameters:*
 
 The model was trained with the following hyperparameters:
-```yaml
-learning_rate: 1e-05
-train_batch_size: 16
-eval_batch_size: 8
-seed: 42
-gradient_accumulation_steps: 2
-total_train_batch_size: 32
-optimizer: adamw_torch (betas=(0.9, 0.999), epsilon=1e-08)
-lr_scheduler_type: linear
-lr_scheduler_warmup_steps: 50
-training_steps: 500
-mixed_precision_training: Native AMP
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss |
-|:-------------:|:-----:|:----:|:---------------:|
-| 1.1921        | 100.0 | 100  | 0.4136          |
-| 0.8435        | 200.0 | 200  | 0.3791          |
-| 0.8294        | 300.0 | 300  | 0.3766          |
-| 0.7959        | 400.0 | 400  | 0.3744          |
-| 0.7918        | 500.0 | 500  | 0.3763          |
-
-
-### Framework versions
-
-- Transformers 4.46.0.dev0
-- Pytorch 2.4.1+cu121
-- Datasets 3.0.2
-- Tokenizers 0.20.1
+
+- *Learning Rate*: 1e-05
+- *Train Batch Size*: 16
+- *Eval Batch Size*: 8
+- *Seed*: 42
+- *Gradient Accumulation Steps*: 2
+- *Total Train Batch Size*: 32
+- *Optimizer*: AdamW (betas=(0.9, 0.999), epsilon=1e-08)
+- *LR Scheduler Type*: Linear
+- *Warmup Steps*: 50
+- *Training Steps*: 500
+- *Mixed Precision Training*: Native AMP
+
+### ⚙ *📊 Training Results:*:
+| 🏋‍♂ Training Loss | 🕑 Epoch | 🛤 Step | 📉 Validation Loss |
+|:-------------------:|:-------:|:-------:|:-----------------:|
+|        1.1921       | 100.0   | 100     |      0.4136       |
+|        0.8435       | 200.0   | 200     |      0.3791       |
+|        0.8294       | 300.0   | 300     |      0.3766       |
+|        0.7959       | 400.0   | 400     |      0.3744       |
+|        0.7918       | 500.0   | 500     |      0.3763       |
+
+
+### 📦 Framework Versions
+
+- *Transformers*: 4.46.0.dev0
+- *PyTorch*: 2.4.1+cu121
+- *Datasets*: 3.0.2
+- *Tokenizers*: 0.20.1