Update README.md

README.md

@@ -1,4 +1,62 @@
 ---
-license: cc-by-nc-sa-4.0
 pipeline_tag: feature-extraction
----
+tags:
+- feature-extraction
+- transformers
+license: apache-2.0
+language:
+- id
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+datasets:
+- squad_v2
+---
+### indo-dpr-question_encoder-single-squad-base
+<p style="font-size:16px">Indonesian Dense Passage Retrieval trained on translated SQuADv2.0 dataset in DPR format.</p>
+
+
+### Evaluation 
+
+| Class | Precision | Recall | F1-Score | Support |
+|-------|-----------|--------|----------|---------|
+| hard_negative | 0.9963 | 0.9963 | 0.9963 | 183090 |
+| positive | 0.8849 | 0.8849 | 0.8849 | 5910 |
+
+| Metric | Value |
+|--------|-------|
+| Accuracy | 0.9928 |
+| Macro Average | 0.9406 |
+| Weighted Average | 0.9928 |
+
+<p style="font-size:16px">Note: This report is for evaluation on the dev set, after 12000 batches.</p>
+
+### Usage
+
+```python
+from transformers import DPRContextEncoder, DPRContextEncoderTokenizer
+
+tokenizer = DPRContextEncoderTokenizer.from_pretrained('firqaaa/indo-dpr-ctx_encoder-single-squad-base')
+model = DPRContextEncoder.from_pretrained('firqaaa/indo-dpr-ctx_encoder-single-squad-base')
+input_ids = tokenizer("Ibukota Indonesia terletak dimana?", return_tensors='pt')["input_ids"]
+embeddings = model(input_ids).pooler_output
+```
+
+You can use it using `haystack` as follows:
+
+```
+from haystack.nodes import DensePassageRetriever
+from haystack.document_stores import InMemoryDocumentStore
+
+retriever = DensePassageRetriever(document_store=InMemoryDocumentStore(),
+                                  query_embedding_model="firqaaa/indo-dpr-ctx_encoder-single-squad-base",
+                                  passage_embedding_model="firqaaa/indo-dpr-ctx_encoder-single-squad-base",
+                                  max_seq_len_query=64,
+                                  max_seq_len_passage=256,
+                                  batch_size=16,
+                                  use_gpu=True,
+                                  embed_title=True,
+                                  use_fast_tokenizers=True)
+```