Update README.md

README.md

@@ -10,17 +10,14 @@ tags:
 
 This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 200 dimensional dense vector space and can be used for tasks like clustering or semantic search.
 
-<!--- Describe your model here -->
+## Training
 
-## Usage (Sentence-Transformers)
+This model was trained on PapersWithCode dataset on abstracts and READMEs using gensim.
 
-Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed:
+<!--- Describe your model here -->
 
-```
-pip install -U sentence-transformers
-```
+## Usage (Sentence-Transformers)
 
-Then you can use the model like this:
 
 ```python
 from sentence_transformers import SentenceTransformer
@@ -32,15 +29,6 @@ print(embeddings)
 ```
 
 
-
-## Evaluation Results
-
-<!--- Describe how your model was evaluated -->
-
-For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name=lambdaofgod/paperswithcode_word2vec)
-
-
-
 ## Full Model Architecture
 ```
 SentenceTransformer(