Update README.md

README.md

@@ -21,36 +21,29 @@ It achieves the following results on the evaluation set:
 - Train Accuracy: 0.7976
 - Validation Loss: 0.5521
 - Validation Accuracy: 0.7456
-- Epoch: 4
+- Epoch: 5
+- Batch size: 32
 
 ## Model description
-This model is fine-tuned by Bùi Nguyên Nghĩa - 19120600@student.hcmus.edu.vn in [Kaggle](https://www.kaggle.com/code/nguynnghabi/training-electra)
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
+This model is fine-tuned by 19120600@student.hcmus.edu.vn in [Kaggle](https://www.kaggle.com/code/nguynnghabi/training-electra)
 
 ## Training procedure
 
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- optimizer: {'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': True, 'is_legacy_optimizer': False, 'learning_rate': 5e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
+- optimizer: {'name': 'Adam', 'learning_rate': 5e-05, 'epsilon': 1e-08}
 - training_precision: float32
 
 ### Training results
 
 | Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
 |:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
-| 0.5951     | 0.6936         | 0.5818          | 0.6966              | 0     |
-| 0.5484     | 0.7291         | 0.5681          | 0.7054              | 1     |
-| 0.5119     | 0.7543         | 0.5284          | 0.7423              | 2     |
-| 0.4769     | 0.7800         | 0.5306          | 0.7432              | 3     |
-| 0.4494     | 0.7976         | 0.5521          | 0.7456              | 4     |
+| 0.5951     | 0.6936         | 0.5818          | 0.6966              | 1     |
+| 0.5484     | 0.7291         | 0.5681          | 0.7054              | 2     |
+| 0.5119     | 0.7543         | 0.5284          | 0.7423              | 3     |
+| 0.4769     | 0.7800         | 0.5306          | 0.7432              | 4     |
+| 0.4494     | 0.7976         | 0.5521          | 0.7456              | 5     |
 
 
 ### Framework versions