Create README.md

README.md

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+---
+language:
+- es
+tags:
+- es
+- Sentence Similarity
+license: "apache-2.0"
+datasets:
+- stsb_multi_mt(es)
+metrics:
+- Cosine-Similarity
+- Manhattan-Distance
+- Euclidean-Distance
+- Dot-Product-Similarity
+---
+# Training
+This model was built using Sentence Transformer.
+## Model description
+Input for the model: Any spanish text
+Output for the model: encoded text
+## Evaluation
+```
+- Cosine-Similarity :	Pearson: 0.8056	Spearman: 0.7993
+- Manhattan-Distance:	Pearson: 0.7986	Spearman: 0.7953
+- Euclidean-Distance:	Pearson: 0.7991	Spearman: 0.7960
+- Dot-Product-Similarity:	Pearson: 0.7658	Spearman: 0.7542
+```
+#### How to use
+Here is how to use this model to get the features of a given text in *PyTorch*:
+```python
+# You can include sample code which will be formatted
+from sentence_transformers import SentenceTransformer
+model = SentenceTransformer()
+sentences = ["mi nombre es Siddhartha","¿viajas a kathmandu?"]
+
+sentence_embeddings = model.encode(sentences)
+print(sentence_embeddings)
+```
+## Training procedure
+I trained on the dataset on the [dccuchile/bert-base-spanish-wwm-cased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased).
+