Update README.md

README.md

@@ -5,6 +5,10 @@ tags:
 model-index:
 - name: indobert-squad-trained
   results: []
+widget:
+- text: Di daerah mana Ubud berada?
+  context: Ubud adalah sebuah desa adat sekaligus menjadi destinasi wisata di daerah kabupaten Gianyar, pulau Bali, Indonesia. Ubud terutama terkenal diantara para wisatawan mancanegara karena terletak di antara sawah dan hutan yang berjurang-jurang yang membuat pemandangan alam sangat indah. Selain itu, Ubud dikenal karena seni dan budaya yang berkembang sangat pesat dan maju.
+
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,19 +20,30 @@ This model is a fine-tuned version of [indolem/indobert-base-uncased](https://hu
 It achieves the following results on the evaluation set:
 - Loss: 1.8025
 
-## Model description
+## IndoBERT
+
+[IndoBERT](https://huggingface.co/indolem/indobert-base-uncased) is the Indonesian version of BERT model. We train the model using over 220M words, aggregated from three main sources:
+- Indonesian Wikipedia (74M words)
+- news articles from Kompas, Tempo (Tala et al., 2003), and Liputan6 (55M words in total)
+- an Indonesian Web Corpus (Medved and Suchomel, 2017) (90M words).
 
-More information needed
+We trained the model for 2.4M steps (180 epochs) with the final perplexity over the development set being 3.97 (similar to English BERT-base).
 
-## Intended uses & limitations
+This IndoBERT was used to examine IndoLEM - an Indonesian benchmark that comprises of seven tasks for the Indonesian language, spanning morpho-syntax, semantics, and discourse.
 
-More information needed
 
 ## Training and evaluation data
 
-More information needed
+SQuAD2.0 combines the 100,000 questions in SQuAD1.1 with over 50,000 unanswerable questions written adversarially by crowdworkers to look similar to answerable ones. To do well on SQuAD2.0, systems must not only answer questions when possible, but also determine when no answer is supported by the paragraph and abstain from answering.
+
+| Dataset  | Split | # samples |
+| -------- | ----- | --------- |
+| SQuAD2.0 | train | 130k      |
+| SQuAD2.0 | eval  | 12.3k     |
+
 
 ## Training procedure
+The model was trained on a Tesla T4 GPU and 12GB of RAM.
 
 ### Training hyperparameters
 
@@ -49,6 +64,48 @@ The following hyperparameters were used during training:
 | 1.1716        | 2.0   | 16404 | 1.8555          |
 | 1.2909        | 3.0   | 24606 | 1.8025          |
 
+| Metric | # Value   |
+| ------ | --------- |
+| **EM** | **52.17** |
+| **F1** | **69.22** |
+
+
+## Pipeline
+```py
+from transformers import pipeline
+
+qa_pipeline = pipeline(
+    "question-answering",
+    model="esakrissa/indobert-squad-trained",
+    tokenizer="esakrissa/indobert-squad-trained"
+)
+
+qa_pipeline({
+    'context': """Ubud adalah sebuah desa adat sekaligus menjadi destinasi wisata di daerah kabupaten Gianyar, pulau Bali, Indonesia.
+
+Ubud terutama terkenal diantara para wisatawan mancanegara karena terletak di antara sawah dan hutan yang berjurang-jurang yang membuat pemandangan alam sangat indah. Selain itu, Ubud dikenal karena seni dan budaya yang berkembang sangat pesat dan maju. Denyut nadi kehidupan masyarakat Ubud tidak bisa dilepaskan dari kesenian. Di sini banyak pula terdapat galeri-galeri seni, serta arena pertunjukan musik dan tari yang digelar setiap malam secara bergantian di segala penjuru desa.
+
+Sudah sejak tahun 1920-an, Ubud terkenal di antara wisatawan barat. Kala itu pelukis Jerman; Walter Spies dan pelukis Belanda; Rudolf Bonnet menetap di sana. Mereka dibantu oleh Tjokorda Gde Agung Sukawati, dari Puri Agung Ubud. Sekarang karya mereka bisa dilihat di Museum Puri Lukisan, Ubud.""",
+    'question': "Sejak kapan ubud terkenal di antara wisatawan barat?"
+})
+```
+*output:*
+```py
+{
+'answer': '1920-an'
+'start': 644, 
+'end': 651,
+'score': 0.8787403106689453, 
+}
+```
+
+[Github](https://github.com/esakrissa/question-answering)
+
+## Demo
+
+
+### Reference
+<a id="1">[1]</a>Fajri Koto and Afshin Rahimi and Jey Han Lau and Timothy Baldwin. 2020. IndoLEM and IndoBERT: A Benchmark Dataset and Pre-trained Language Model for Indonesian NLP. Proceedings of the 28th COLING.
 
 ### Framework versions