Update README.md

README.md

@@ -25,6 +25,7 @@ augmetations = {'class': 'ITIL or Ontology, one word {ITIL} or {Ontology}',
                 'nearest ontology': 'find nearest analogy, process, class or entity from DOLCE ontology domain. 1 words, short sentence to explain, max 20 words',
                 'nearest ITIL': 'find nearest analogy, process, class or entity from enterprise IT service domain. 1 words, short sentence to explain, max 20 words',
                 'summary': 'text esscence in 20 words, no intro, just meaning'}
+```
 
 - **Total Samples before augmentation**: 5779
 - **Total Samples after augmentation**: 17337
@@ -45,6 +46,7 @@ training_args = TrainingArguments(
     logging_steps=500,
     fp16=True
 )
+```
 
 ## Intended Use
 
@@ -54,6 +56,7 @@ This model is optimized for class representation tasks in the context of ontolog
 
 Trained for ontology-based semantic representation and classification tasks.
 
+```
 Trained on raw data
 Evaluation results: {'eval_loss': 3.6031947135925293, 'eval_runtime': 26.6242, 'eval_samples_per_second': 21.71, 'eval_steps_per_second': 10.855, 'epoch': 100.0}
 Perplexity: 36.7153422841205
@@ -61,6 +64,7 @@ Perplexity: 36.7153422841205
 Trained on augmented data
 Evaluation results: {'eval_loss': 1.4712743759155273, 'eval_model_preparation_time': 0.0065, 'eval_runtime': 76.2792, 'eval_samples_per_second': 22.732, 'eval_steps_per_second': 2.845}
 Perplexity: 4.3547812347309875
+```
 
 ---