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--- |
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language: |
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- en |
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--- |
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# AutoTrain Dataset for project: ratnakar_1000_sample_curated |
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## Dataset Description |
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This dataset has been automatically processed by AutoTrain for project ratnakar_1000_sample_curated. |
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### Languages |
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The BCP-47 code for the dataset's language is en. |
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## Dataset Structure |
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### Data Instances |
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A sample from this dataset looks as follows: |
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```json |
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[ |
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{ |
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"tokens": [ |
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"INTRADAY", |
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"NAHARINDUS", |
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" ABOVE ", |
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"128", |
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" - 129 SL ", |
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"126", |
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" TARGET ", |
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"140", |
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" " |
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], |
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"tags": [ |
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8, |
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10, |
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0, |
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3, |
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0, |
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9, |
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0, |
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5, |
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0 |
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] |
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}, |
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{ |
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"tokens": [ |
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"INTRADAY", |
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"ASTRON", |
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" ABV ", |
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"39", |
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" SL ", |
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"37.50", |
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" TARGET ", |
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"45", |
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" " |
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], |
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"tags": [ |
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8, |
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10, |
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0, |
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3, |
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0, |
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9, |
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0, |
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5, |
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0 |
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] |
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} |
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] |
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``` |
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### Dataset Fields |
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The dataset has the following fields (also called "features"): |
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```json |
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{ |
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"tokens": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)", |
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"tags": "Sequence(feature=ClassLabel(num_classes=12, names=['NANA', 'btst', 'delivery', 'enter', 'entry_momentum', 'exit', 'exit2', 'exit3', 'intraday', 'sl', 'symbol', 'touched'], id=None), length=-1, id=None)" |
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} |
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``` |
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### Dataset Splits |
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This dataset is split into a train and validation split. The split sizes are as follow: |
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| Split name | Num samples | |
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| ------------ | ------------------- | |
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| train | 726 | |
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| valid | 259 | |
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# GitHub Link to this project : [Telegram Trade Msg Backtest ML](https://github.com/hemangjoshi37a/TelegramTradeMsgBacktestML) |
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# Need custom model for your application? : Place a order on hjLabs.in : [Custom Token Classification or Named Entity Recognition (NER) model as in Natural Language Processing (NLP) Machine Learning](https://hjlabs.in/product/custom-token-classification-or-named-entity-recognition-ner-model-as-in-natural-language-processing-nlp-machine-learning/) |
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## What this repository contains? : |
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1. Label data using LabelStudio NER(Named Entity Recognition or Token Classification) tool. |
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 convert to  |
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2. Convert LabelStudio CSV or JSON to HuggingFace-autoTrain dataset conversion script |
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3. Train NER model on Hugginface-autoTrain. |
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4. Use Hugginface-autoTrain model to predict labels on new data in LabelStudio using LabelStudio-ML-Backend. |
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5. Define python function to predict labels using Hugginface-autoTrain model. |
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6. Only label new data from newly predicted-labels-dataset that has falsified labels. |
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7. Backtest Truely labelled dataset against real historical data of the stock using zerodha kiteconnect and jugaad_trader. |
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8. Evaluate total gained percentage since inception summation-wise and compounded and plot. |
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9. Listen to telegram channel for new LIVE messages using telegram API for algotrading. |
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10. Serve the app as flask web API for web request and respond to it as labelled tokens. |
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11. Outperforming or underperforming results of the telegram channel tips against exchange index by percentage. |
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Place a custom order on hjLabs.in : [https://hjLabs.in](https://hjlabs.in/?product=custom-algotrading-software-for-zerodha-and-angel-w-source-code) |
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---------------------------------------------------------------------- |
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### Contact us |
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Mobile : [+917016525813](tel:+917016525813) |
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Whatsapp & Telegram : [+919409077371](tel:+919409077371) |
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Email : [hemangjoshi37a@gmail.com](mailto:hemangjoshi37a@gmail.com) |
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Place a custom order on hjLabs.in : [https://hjLabs.in](https://hjlabs.in/) |
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Please contribute your suggestions and corections to support our efforts. |
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Thank you. |
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## Our HuggingFace Models : |
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- [hemangjoshi37a/autotrain-ratnakar_1000_sample_curated-1474454086 : Stock tip message NER(Named Entity Recognition or Token Classification) using HUggingFace-AutoTrain and LabelStudio and Ratnakar Securities Pvt. Ltd.](https://huggingface.co/hemangjoshi37a/autotrain-ratnakar_1000_sample_curated-1474454086) |
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## Our HuggingFace Datasets : |
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- [hemangjoshi37a/autotrain-data-ratnakar_1000_sample_curated : Stock tip message NER(Named Entity Recognition or Token Classification) using HUggingFace-AutoTrain and LabelStudio and Ratnakar Securities Pvt. Ltd.](https://huggingface.co/datasets/hemangjoshi37a/autotrain-data-ratnakar_1000_sample_curated) |
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