Update README.md

README.md

@@ -8,8 +8,8 @@ base_model:
 - sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
 library_name: transformers
 ---
-Model Description
-This model is a fine-tuned version of sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 for sentence similarity tasks. It was trained on the mteb/stsbenchmark-sts dataset to evaluate the similarity between sentence pairs.
+# Model Description
+  This model is a fine-tuned version of sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 for sentence similarity tasks. It was trained on the mteb/stsbenchmark-sts dataset to evaluate the similarity between sentence pairs.
 
 Model Type: Sequence Classification (Regression)
 Pre-trained Model: sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
@@ -26,10 +26,11 @@ Weight Decay: 0.01
 Evaluation
 The model was evaluated using Pearson correlation on the validation set of the mteb/stsbenchmark-sts dataset. Results indicate how well the model predicts similarity scores between sentence pairs.
 
-Usage
+# Usage
 To use this model for sentence similarity, follow these steps:
 
-from transformers import AutoTokenizer, AutoModelForSequenceClassification
+```python
+  from transformers import AutoTokenizer, AutoModelForSequenceClassification
 
 # Load the fine-tuned model
 
@@ -67,7 +68,7 @@ If using the model for generating sentence embeddings, you can use the following
 Domain Specificity: The model is fine-tuned on the mteb/stsbenchmark-sts dataset and may perform differently on other types of text or datasets.
 Biases: As with any model trained on human language data, it may inherit and reflect biases present in the training data.
 
-Future Work
+# Future Work
 Potential improvements include fine-tuning on additional datasets, experimenting with different architectures or hyperparameters, and incorporating additional training techniques to improve performance and robustness.
 
 Citation
@@ -80,5 +81,5 @@ If you use this model in your research, please cite it as follows:
 }
 
 
-License
+# License
 This model is licensed under the MIT License. See the LICENSE file for more information.