Update README.md

README.md

@@ -1,3 +1,68 @@
 ---
+pipeline_tag: feature-extraction
+tags:
+- feature-extraction
+- transformers
 license: apache-2.0
+language:
+- id
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+datasets:
+- squad_v2
+- natural_questions
 ---
+### indo-dpr-question_encoder-multiset-base
+<p style="font-size:16px">Indonesian Dense Passage Retrieval trained on translated SQuADv2.0 and Natural Question dataset in DPR format.</p>
+
+
+### Evaluation 
+
+| Class | Precision | Recall | F1-Score | Support |
+|-------|-----------|--------|----------|---------|
+| hard_negative | 0.9961 | 0.9961 | 0.9961 | 384778 |
+| positive | 0.8783 | 0.8783 | 0.8783 | 12414 |
+
+| Metric | Value |
+|--------|-------|
+| Loss | 0.0220 |
+| Accuracy | 0.9924 |
+| Macro Average | 0.9372 |
+| Weighted Average | 0.9924 |
+| Accuracy and F1 | 0.9353 |
+| Average Rank | 0.2194 |
+
+
+<p style="font-size:16px">Note: This report is for evaluation on the dev set, after 27288 batches.</p>
+
+### Usage
+
+```python
+from transformers import DPRQuestionEncoder, DPRQuestionEncoderTokenizer
+
+tokenizer = DPRQuestionEncoderTokenizer.from_pretrained('firqaaa/indo-dpr-question_encoder-multiset-base')
+model = DPRQuestionEncoder.from_pretrained('firqaaa/indo-dpr-question_encoder-multiset-base')
+input_ids = tokenizer("Siapa nama pengarang manga Yu-Gi-Oh?", 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-question_encoder-multiset-base",
+                                  passage_embedding_model="firqaaa/indo-dpr-question_encoder-multiset-base",
+                                  max_seq_len_query=64,
+                                  max_seq_len_passage=256,
+                                  batch_size=16,
+                                  use_gpu=True,
+                                  embed_title=True,
+                                  use_fast_tokenizers=True)
+```
+