File size: 1,166 Bytes
a9f81e5 7ab934c c113a01 7ab934c 908c247 7ab934c c113a01 1fece1b c113a01 7ab934c c113a01 7ab934c c113a01 7ab934c c113a01 7ab934c c113a01 908c247 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 |
---
license: afl-3.0
datasets:
- WillHeld/hinglish_top
language:
- en
metrics:
- accuracy
library_name: transformers
pipeline_tag: fill-mask
---
### SRDberta
This is a BERT model trained for Masked Language Modeling for English Data.
### Dataset
Hinglish-Top [Dataset](https://huggingface.co/datasets/WillHeld/hinglish_top) columns
- en_query
- cs_query
- en_parse
- cs_parse
- domain
### Training
|Epoch|Loss|
|:--:|:--:|
|1 |0.0485|
|2 |0.00837|
|3 |0.00812|
|4 |0.0029|
|5 |0.014|
|6 |0.00748|
|7 |0.0041|
|8 |0.00543|
|9 |0.00304|
|10 |0.000574|
### Inference
```python
from transformers import AutoTokenizer, AutoModelForMaskedLM, pipeline
tokenizer = AutoTokenizer.from_pretrained("SRDdev/SRDBerta")
model = AutoModelForMaskedLM.from_pretrained("SRDdev/SRDBerta")
fill = pipeline('fill-mask', model='SRDberta', tokenizer='SRDberta')
```
```python
fill_mask = fill.tokenizer.mask_token
fill(f'Aap {fill_mask} ho?')
```
### Citation
Author: @[SRDdev](https://huggingface.co/SRDdev)
```
Name : Shreyas Dixit
framework : Pytorch
Year: Jan 2023
Pipeline : fill-mask
Github : https://github.com/SRDdev
LinkedIn : https://www.linkedin.com/in/srddev/
``` |