RoBERTa trained on Sanskrit (SanBERTa)
Mode size (after training): 340MB
Dataset:
Wikipedia articles (used in iNLTK). It contains evaluation set.
Configuration
Parameter | Value |
---|---|
num_attention_heads |
12 |
num_hidden_layers |
6 |
hidden_size |
768 |
vocab_size |
29407 |
Training :
- On TPU
- For language modelling
- Iteratively increasing
--block_size
from 128 to 256 over epochs
Evaluation
Metric | # Value |
---|---|
Perplexity (block_size=256 ) |
4.04 |
Example of usage:
For Embeddings
tokenizer = AutoTokenizer.from_pretrained("surajp/SanBERTa")
model = RobertaModel.from_pretrained("surajp/SanBERTa")
op = tokenizer.encode("इयं भाषा न केवलं भारतस्य अपि तु विश्वस्य प्राचीनतमा भाषा इति मन्यते।", return_tensors="pt")
ps = model(op)
ps[0].shape
'''
Output:
--------
torch.Size([1, 47, 768])
For <mask> Prediction
from transformers import pipeline
fill_mask = pipeline(
"fill-mask",
model="surajp/SanBERTa",
tokenizer="surajp/SanBERTa"
)
## इयं भाषा न केवलं भारतस्य अपि तु विश्वस्य प्राचीनतमा भाषा इति मन्यते।
fill_mask("इयं भाषा न केवल<mask> भारतस्य अपि तु विश्वस्य प्राचीनतमा भाषा इति मन्यते।")
ps = model(torch.tensor(enc).unsqueeze(1))
print(ps[0].shape)
'''
Output:
--------
[{'score': 0.7516744136810303,
'sequence': '<s> इयं भाषा न केवलं भारतस्य अपि तु विश्वस्य प्राचीनतमा भाषा इति मन्यते।</s>',
'token': 280,
'token_str': 'à¤Ĥ'},
{'score': 0.06230105459690094,
'sequence': '<s> इयं भाषा न केवली भारतस्य अपि तु विश्वस्य प्राचीनतमा भाषा इति मन्यते।</s>',
'token': 289,
'token_str': 'à¥Ģ'},
{'score': 0.055410224944353104,
'sequence': '<s> इयं भाषा न केवला भारतस्य अपि तु विश्वस्य प्राचीनतमा भाषा इति मन्यते।</s>',
'token': 265,
'token_str': 'ा'},
...]
@misc{Parmar2020Sanberta,
author = {Parmar, Suraj},
title = {SanBERTa - a RoBERTa trained on Sanskrit},
year = {2020},
month = {Jun},
publisher = {Hugging Face Model Hub},
url = {https://huggingface.co/surajp/SanBERTa}
}
It works!! 🎉 🎉 🎉
Created by Suraj Parmar/@parmarsuraj99 | LinkedIn
Made with ♥ in India
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