Update README.md

README.md

@@ -17,8 +17,7 @@ probably proofread and complete it, then remove this comment. -->
 
 **roberta-large-finetuned-ner** is a fine-tuned Roberta model that is ready to use for **Named Entity Recognition**. It has been trained to recognize eight types of entities:
 Geographical, Organization, Person, Geopolitical Entity, Time indicator, Artifact, Event, Natural Phenomenon.
-This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on an [Named Entity Recognition (NER) Corpus dataset]
-(https://www.kaggle.com/datasets/naseralqaydeh/named-entity-recognition-ner-corpus).
+This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on an [Named Entity Recognition (NER) Corpus dataset](https://www.kaggle.com/datasets/naseralqaydeh/named-entity-recognition-ner-corpus).
 
 It achieves the following results on the evaluation set:
 - Train Loss: 0.1164
@@ -86,7 +85,29 @@ This model was trained on a single T4 GPU.
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 4795, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
+- optimizer:
+  {
+    "name": "AdamWeightDecay",
+    "learning_rate": {
+        "module": "keras.optimizers.schedules",
+        "class_name": "PolynomialDecay",
+        "config": {
+            "initial_learning_rate": 2e-05,
+            "decay_steps": 4795,
+            "end_learning_rate": 0.0,
+            "power": 1.0,
+            "cycle": False,
+            "name": None,
+        },
+        "registered_name": None,
+    },
+    "decay": 0.0,
+    "beta_1": 0.9,
+    "beta_2": 0.999,
+    "epsilon": 1e-08,
+    "amsgrad": False,
+    "weight_decay_rate": 0.01,
+}          - 
 - training_precision: float32
 
 ### Training results