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--- |
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tags: |
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- autotrain |
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- token-classification |
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language: |
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- en |
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widget: |
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- text: "I love AutoTrain 🤗" |
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datasets: |
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- hemangjoshi37a/autotrain-data-ratnakar_1000_sample_curated |
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co2_eq_emissions: |
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emissions: 2.1802563684907916 |
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--- |
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# Model Trained Using AutoTrain |
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- Problem type: Entity Extraction |
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- Model ID: 1474454086 |
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- CO2 Emissions (in grams): 2.1803 |
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## Validation Metrics |
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- Loss: 0.177 |
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- Accuracy: 0.957 |
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- Precision: 0.839 |
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- Recall: 0.888 |
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- F1: 0.863 |
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## Usage |
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You can use cURL to access this model: |
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``` |
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$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/models/hemangjoshi37a/autotrain-ratnakar_1000_sample_curated-1474454086 |
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``` |
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Or Python API: |
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``` |
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from transformers import AutoModelForTokenClassification, AutoTokenizer |
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model = AutoModelForTokenClassification.from_pretrained("hemangjoshi37a/autotrain-ratnakar_1000_sample_curated-1474454086", use_auth_token=True) |
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tokenizer = AutoTokenizer.from_pretrained("hemangjoshi37a/autotrain-ratnakar_1000_sample_curated-1474454086", use_auth_token=True) |
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inputs = tokenizer("I love AutoTrain", return_tensors="pt") |
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outputs = model(**inputs) |
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``` |
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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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![Screenshot from 2022-09-30 12-28-50](https://user-images.githubusercontent.com/12392345/193394190-3ad215d1-3205-4af3-949e-6d95cf866c6c.png) convert to ![Screenshot from 2022-09-30 18-59-14](https://user-images.githubusercontent.com/12392345/193394213-9bb936e7-34ea-4cbc-9132-80c7e5a006d7.png) |
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2. Convert LabelStudio CSV or JSON to HuggingFace-autoTrain dataset conversion script |
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![Screenshot from 2022-10-01 10-36-03](https://user-images.githubusercontent.com/12392345/193394227-32e293d4-6736-4e71-b687-b0c2fcad732c.png) |
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3. Train NER model on Hugginface-autoTrain. |
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![Screenshot from 2022-10-01 10-38-24](https://user-images.githubusercontent.com/12392345/193394247-bf51da86-45bb-41b4-b4da-3de86014e6a5.png) |
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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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![Screenshot from 2022-10-01 10-41-07](https://user-images.githubusercontent.com/12392345/193394251-bfba07d4-c56b-4fe8-ba7f-08a1c69f0e2c.png) |
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![Screenshot from 2022-10-01 10-42-36](https://user-images.githubusercontent.com/12392345/193394261-df4bc8f8-9ffd-4819-ba26-04fddbba8e7b.png) |
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![Screenshot from 2022-10-01 10-44-56](https://user-images.githubusercontent.com/12392345/193394267-c5a111c3-8d00-4d6f-b3c6-0ea82e4ac474.png) |
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5. Define python function to predict labels using Hugginface-autoTrain model. |
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![Screenshot from 2022-10-01 10-47-08](https://user-images.githubusercontent.com/12392345/193394278-81389606-f690-454a-bb2b-ef3f1db39571.png) |
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![Screenshot from 2022-10-01 10-47-25](https://user-images.githubusercontent.com/12392345/193394288-27a0c250-41af-48b1-9c57-c146dc51da1d.png) |
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6. Only label new data from newly predicted-labels-dataset that has falsified labels. |
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![Screenshot from 2022-09-30 22-47-23](https://user-images.githubusercontent.com/12392345/193394294-fdfaf40a-c9cd-4c2d-836e-1878b503a668.png) |
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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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![Screenshot from 2022-10-01 00-05-55](https://user-images.githubusercontent.com/12392345/193394303-137c2a2a-3341-4be3-8ece-5191669ec53a.png) |
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8. Evaluate total gained percentage since inception summation-wise and compounded and plot. |
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![Screenshot from 2022-10-01 00-06-59](https://user-images.githubusercontent.com/12392345/193394308-446eddd9-c5d1-47e3-a231-9edc620284bb.png) |
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9. Listen to telegram channel for new LIVE messages using telegram API for algotrading. |
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![Screenshot from 2022-10-01 00-09-29](https://user-images.githubusercontent.com/12392345/193394319-8cc915b7-216e-4e05-a7bf-28360b17de99.png) |
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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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![Screenshot from 2022-10-01 00-12-12](https://user-images.githubusercontent.com/12392345/193394323-822c2a59-ca72-45b1-abca-a6e5df3364b0.png) |
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11. Outperforming or underperforming results of the telegram channel tips against exchange index by percentage. |
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![Screenshot from 2022-10-01 11-16-27](https://user-images.githubusercontent.com/12392345/193394685-53235198-04f8-4d3c-a341-535dd9093252.png) |
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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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### Social Media : |
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* [WhatsApp/917016525813](https://wa.me/917016525813) |
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* [telegram/hjlabs](https://t.me/hjlabs) |
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* [Facebook/hemangjoshi37](https://www.facebook.com/hemangjoshi37/) |
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* [Twitter/HemangJ81509525](https://twitter.com/HemangJ81509525) |
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* [LinkedIn/hemang-joshi-046746aa](https://www.linkedin.com/in/hemang-joshi-046746aa/) |
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* [Tumblr/hemangjoshi37a-blog](https://www.tumblr.com/blog/hemangjoshi37a-blog) |
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* [Pinterest/hemangjoshi37a](https://in.pinterest.com/hemangjoshi37a/) |
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* [Blogger/hemangjoshi](http://hemangjoshi.blogspot.com/) |
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* [Instagram/hemangjoshi37](https://www.instagram.com/hemangjoshi37/) |
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### Checkout Our Other Repositories |
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- [pyPortMan](https://github.com/hemangjoshi37a/pyPortMan) |
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- [transformers_stock_prediction](https://github.com/hemangjoshi37a/transformers_stock_prediction) |
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- [TrendMaster](https://github.com/hemangjoshi37a/TrendMaster) |
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- [hjAlgos_notebooks](https://github.com/hemangjoshi37a/hjAlgos_notebooks) |
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- [AutoCut](https://github.com/hemangjoshi37a/AutoCut) |
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- [My_Projects](https://github.com/hemangjoshi37a/My_Projects) |
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- [Cool Arduino and ESP8266 or NodeMCU Projects](https://github.com/hemangjoshi37a/my_Arduino) |
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- [Telegram Trade Msg Backtest ML](https://github.com/hemangjoshi37a/TelegramTradeMsgBacktestML) |
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- [WiFi IoT LED Matrix Display](https://hjlabs.in/product/wifi-iot-led-display) |
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- [SWiBoard WiFi Switch Board IoT Device](https://hjlabs.in/product/swiboard-wifi-switch-board-iot-device) |
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- [Electric Bicycle](https://hjlabs.in/product/electric-bicycle) |
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- [Product 3D Design Service with Solidworks](https://hjlabs.in/product/product-3d-design-with-solidworks/) |
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- [AutoCut : Automatic Wire Cutter Machine](https://hjlabs.in/product/automatic-wire-cutter-machine/) |
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- [Custom AlgoTrading Software Coding Services](https://hjlabs.in/product/custom-algotrading-software-for-zerodha-and-angel-w-source-code//) |
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- [SWiBoard :Tasmota MQTT Control App](https://play.google.com/store/apps/details?id=in.hjlabs.swiboard) |
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- [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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## Some Cool Arduino and ESP8266 (or NodeMCU) IoT projects: |
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- [IoT_LED_over_ESP8266_NodeMCU : Turn LED on and off using web server hosted on a nodemcu or esp8266](https://github.com/hemangjoshi37a/my_Arduino/tree/master/IoT_LED_over_ESP8266_NodeMCU) |
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- [ESP8266_NodeMCU_BasicOTA : Simple OTA (Over The Air) upload code from Arduino IDE using WiFi to NodeMCU or ESP8266](https://github.com/hemangjoshi37a/my_Arduino/tree/master/ESP8266_NodeMCU_BasicOTA) |
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- [IoT_CSV_SD : Read analog value of Voltage and Current and write it to SD Card in CSV format for Arduino, ESP8266, NodeMCU etc](https://github.com/hemangjoshi37a/my_Arduino/tree/master/IoT_CSV_SD) |
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- [Honeywell_I2C_Datalogger : Log data in A SD Card from a Honeywell I2C HIH8000 or HIH6000 series sensor having external I2C RTC clock](https://github.com/hemangjoshi37a/my_Arduino/tree/master/Honeywell_I2C_Datalogger) |
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- [IoT_Load_Cell_using_ESP8266_NodeMC : Read ADC value from High Precision 12bit ADS1015 ADC Sensor and Display on SSD1306 SPI Display as progress bar for Arduino or ESP8266 or NodeMCU](https://github.com/hemangjoshi37a/my_Arduino/tree/master/IoT_Load_Cell_using_ESP8266_NodeMC) |
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- [IoT_SSD1306_ESP8266_NodeMCU : Read from High Precision 12bit ADC seonsor ADS1015 and display to SSD1306 SPI as progress bar in ESP8266 or NodeMCU or Arduino](https://github.com/hemangjoshi37a/my_Arduino/tree/master/IoT_SSD1306_ESP8266_NodeMCU) |
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## Checkout Our Awesome 3D GrabCAD Models: |
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- [AutoCut : Automatic Wire Cutter Machine](https://grabcad.com/library/automatic-wire-cutter-machine-1) |
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- [ESP Matrix Display 5mm Acrylic Box](https://grabcad.com/library/esp-matrix-display-5mm-acrylic-box-1) |
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- [Arcylic Bending Machine w/ Hot Air Gun](https://grabcad.com/library/arcylic-bending-machine-w-hot-air-gun-1) |
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- [Automatic Wire Cutter/Stripper](https://grabcad.com/library/automatic-wire-cutter-stripper-1) |
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|
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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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## We sell Gigs on Fiverr : |
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- [code android and ios app for you using flutter firebase software stack](https://business.fiverr.com/share/3v14pr) |
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## Awesome Fiverr. Gigs: |
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