From fa265230a200f037592377987c6d963d2601e6d0 Mon Sep 17 00:00:00 2001
From: Suraj Parmar <parmarsuraj99@gmail.com>
Date: Fri, 10 Jul 2020 21:04:23 +0530
Subject: [PATCH] Create Model card for RoBERTa-hindi-guj-san (#5661)

---
 .../surajp/RoBERTa-hindi-guj-san/README.md    | 108 ++++++++++++++++++
 1 file changed, 108 insertions(+)
 create mode 100644 model_cards/surajp/RoBERTa-hindi-guj-san/README.md

diff --git a/model_cards/surajp/RoBERTa-hindi-guj-san/README.md b/model_cards/surajp/RoBERTa-hindi-guj-san/README.md
new file mode 100644
index 0000000000..2a8f45eefc
--- /dev/null
+++ b/model_cards/surajp/RoBERTa-hindi-guj-san/README.md
@@ -0,0 +1,108 @@
+---
+language: "multilingual"
+tags:
+- Hindi
+- Sanskrit
+- Gujarati
+- Indic
+- roberta
+license: "MIT"
+datasets:
+- Wikipedia (Hindi, Sanskrit, Gujarati)
+metrics:
+- perplexity
+---
+
+# RoBERTa-hindi-guj-san
+
+## Model description
+
+Multillingual RoBERTa like model trained on Wikipedia articles of Hindi, Sanskrit, Gujarati languages. The tokenizer was trained on combined text. 
+However, Hindi text was used to pre-train the model and then it was fine-tuned on Sanskrit and Gujarati Text combined hoping that pre-training with Hindi 
+will help the model learn similar languages.
+
+### Configuration
+
+| Parameter | Value |
+|---|---|
+| `hidden_size` | 768 |
+| `num_attention_heads` | 12 |
+| `num_hidden_layers` | 6 |
+| `vocab_size` | 30522 |
+|`model_type`|`roberta`|
+
+## Intended uses & limitations
+
+#### How to use
+
+```python
+# Example usage
+from transformers import AutoTokenizer, AutoModelWithLMHead, pipeline
+
+tokenizer = AutoTokenizer.from_pretrained("surajp/RoBERTa-hindi-guj-san")
+model = AutoModelWithLMHead.from_pretrained("surajp/RoBERTa-hindi-guj-san")
+
+fill_mask = pipeline(
+    "fill-mask",
+    model=model,
+    tokenizer=tokenizer
+)
+
+# Sanskrit: इयं भाषा न केवलं भारतस्य अपि तु विश्वस्य प्राचीनतमा भाषा इति मन्यते।
+# Hindi:  अगर आप अब अभ्यास नहीं करते हो तो आप अपने परीक्षा में मूर्खतापूर्ण गलतियाँ करोगे।
+# Gujarati: ગુજરાતમાં ૧૯મી માર્ચ સુધી કોઈ સકારાત્મક (પોઝીટીવ) રીપોર્ટ આવ્યો <mask> હતો.
+fill_mask("ગુજરાતમાં ૧૯મી માર્ચ સુધી કોઈ સકારાત્મક (પોઝીટીવ) રીપોર્ટ આવ્યો <mask> હતો.")
+
+'''
+Output:
+--------
+[
+{'score': 0.07849744707345963, 'sequence': '<s> ગુજરાતમાં ૧૯મી માર્ચ સુધી કોઈ સકારાત્મક (પોઝીટીવ) રીપોર્ટ આવ્યો જ હતો.</s>', 'token': 390},
+{'score': 0.06273336708545685, 'sequence': '<s> ગુજરાતમાં ૧૯મી માર્ચ સુધી કોઈ સકારાત્મક (પોઝીટીવ) રીપોર્ટ આવ્યો ન હતો.</s>', 'token': 478},
+{'score': 0.05160355195403099, 'sequence': '<s> ગુજરાતમાં ૧૯મી માર્ચ સુધી કોઈ સકારાત્મક (પોઝીટીવ) રીપોર્ટ આવ્યો થઇ હતો.</s>', 'token': 2075},
+{'score': 0.04751499369740486, 'sequence': '<s> ગુજરાતમાં ૧૯મી માર્ચ સુધી કોઈ સકારાત્મક (પોઝીટીવ) રીપોર્ટ આવ્યો એક હતો.</s>', 'token': 600},
+{'score': 0.03788900747895241, 'sequence': '<s> ગુજરાતમાં ૧૯મી માર્ચ સુધી કોઈ સકારાત્મક (પોઝીટીવ) રીપોર્ટ આવ્યો પણ હતો.</s>', 'token': 840}
+]
+
+```
+
+## Training data
+
+Cleaned wikipedia articles in Hindi, Sanskrit and Gujarati on Kaggle. It contains training as well as evaluation text. 
+Used in [iNLTK](https://github.com/goru001/inltk)
+
+- [Hindi](https://www.kaggle.com/disisbig/hindi-wikipedia-articles-172k)
+- [Gujarati](https://www.kaggle.com/disisbig/gujarati-wikipedia-articles)
+- [Sanskrit](https://www.kaggle.com/disisbig/sanskrit-wikipedia-articles)
+
+## Training procedure
+
+- On TPU (using `xla_spawn.py`)
+- For language modelling
+- Iteratively increasing `--block_size` from 128 to 256 over epochs
+- Tokenizer trained on combined text
+- Pre-training with Hindi and fine-tuning on Sanskrit and Gujarati texts
+
+```
+--model_type distillroberta-base \
+--model_name_or_path "/content/SanHiGujBERTa" \
+--mlm_probability 0.20 \
+--line_by_line \
+--save_total_limit 2 \
+--per_device_train_batch_size 128 \
+--per_device_eval_batch_size 128 \
+--num_train_epochs 5 \
+--block_size 256 \
+--seed 108 \
+--overwrite_output_dir \
+```
+
+## Eval results
+
+perplexity = 2.920005983224673
+
+
+
+> Created by [Suraj Parmar/@parmarsuraj99](https://twitter.com/parmarsuraj99) | [LinkedIn](https://www.linkedin.com/in/parmarsuraj99/)
+
+> Made with <span style="color: #e25555;">&hearts;</span> in India