--- tags: - autotrain - token-classification language: - en widget: - text: "I love AutoTrain 🤗" datasets: - hemangjoshi37a/autotrain-data-ratnakar_1000_sample_curated co2_eq_emissions: emissions: 2.1802563684907916 --- # Model Trained Using AutoTrain - Problem type: Entity Extraction - Model ID: 1474454086 - CO2 Emissions (in grams): 2.1803 ## Validation Metrics - Loss: 0.177 - Accuracy: 0.957 - Precision: 0.839 - Recall: 0.888 - F1: 0.863 ## Usage You can use cURL to access this model: ``` $ 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 ``` Or Python API: ``` from transformers import AutoModelForTokenClassification, AutoTokenizer model = AutoModelForTokenClassification.from_pretrained("hemangjoshi37a/autotrain-ratnakar_1000_sample_curated-1474454086", use_auth_token=True) tokenizer = AutoTokenizer.from_pretrained("hemangjoshi37a/autotrain-ratnakar_1000_sample_curated-1474454086", use_auth_token=True) inputs = tokenizer("I love AutoTrain", return_tensors="pt") outputs = model(**inputs) ``` # GitHub Link to this project : [Telegram Trade Msg Backtest ML](https://github.com/hemangjoshi37a/TelegramTradeMsgBacktestML) # 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/) ## What this repository contains? : 1. Label data using LabelStudio NER(Named Entity Recognition or Token Classification) tool. ![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) 2. Convert LabelStudio CSV or JSON to HuggingFace-autoTrain dataset conversion script ![Screenshot from 2022-10-01 10-36-03](https://user-images.githubusercontent.com/12392345/193394227-32e293d4-6736-4e71-b687-b0c2fcad732c.png) 3. Train NER model on Hugginface-autoTrain. ![Screenshot from 2022-10-01 10-38-24](https://user-images.githubusercontent.com/12392345/193394247-bf51da86-45bb-41b4-b4da-3de86014e6a5.png) 4. Use Hugginface-autoTrain model to predict labels on new data in LabelStudio using LabelStudio-ML-Backend. ![Screenshot from 2022-10-01 10-41-07](https://user-images.githubusercontent.com/12392345/193394251-bfba07d4-c56b-4fe8-ba7f-08a1c69f0e2c.png) ![Screenshot from 2022-10-01 10-42-36](https://user-images.githubusercontent.com/12392345/193394261-df4bc8f8-9ffd-4819-ba26-04fddbba8e7b.png) ![Screenshot from 2022-10-01 10-44-56](https://user-images.githubusercontent.com/12392345/193394267-c5a111c3-8d00-4d6f-b3c6-0ea82e4ac474.png) 5. Define python function to predict labels using Hugginface-autoTrain model. ![Screenshot from 2022-10-01 10-47-08](https://user-images.githubusercontent.com/12392345/193394278-81389606-f690-454a-bb2b-ef3f1db39571.png) ![Screenshot from 2022-10-01 10-47-25](https://user-images.githubusercontent.com/12392345/193394288-27a0c250-41af-48b1-9c57-c146dc51da1d.png) 6. Only label new data from newly predicted-labels-dataset that has falsified labels. ![Screenshot from 2022-09-30 22-47-23](https://user-images.githubusercontent.com/12392345/193394294-fdfaf40a-c9cd-4c2d-836e-1878b503a668.png) 7. Backtest Truely labelled dataset against real historical data of the stock using zerodha kiteconnect and jugaad_trader. ![Screenshot from 2022-10-01 00-05-55](https://user-images.githubusercontent.com/12392345/193394303-137c2a2a-3341-4be3-8ece-5191669ec53a.png) 8. Evaluate total gained percentage since inception summation-wise and compounded and plot. ![Screenshot from 2022-10-01 00-06-59](https://user-images.githubusercontent.com/12392345/193394308-446eddd9-c5d1-47e3-a231-9edc620284bb.png) 9. Listen to telegram channel for new LIVE messages using telegram API for algotrading. ![Screenshot from 2022-10-01 00-09-29](https://user-images.githubusercontent.com/12392345/193394319-8cc915b7-216e-4e05-a7bf-28360b17de99.png) 10. Serve the app as flask web API for web request and respond to it as labelled tokens. ![Screenshot from 2022-10-01 00-12-12](https://user-images.githubusercontent.com/12392345/193394323-822c2a59-ca72-45b1-abca-a6e5df3364b0.png) 11. Outperforming or underperforming results of the telegram channel tips against exchange index by percentage. ![Screenshot from 2022-10-01 11-16-27](https://user-images.githubusercontent.com/12392345/193394685-53235198-04f8-4d3c-a341-535dd9093252.png) Place a custom order on hjLabs.in : [https://hjLabs.in](https://hjlabs.in/?product=custom-algotrading-software-for-zerodha-and-angel-w-source-code) ---------------------------------------------------------------------- ### Social Media : * [WhatsApp/917016525813](https://wa.me/917016525813) * [telegram/hjlabs](https://t.me/hjlabs) * [Gmail/hemangjoshi37a@gmail.com](mailto:hemangjoshi37a@gmail.com) * [Facebook/hemangjoshi37](https://www.facebook.com/hemangjoshi37/) * [Twitter/HemangJ81509525](https://twitter.com/HemangJ81509525) * [LinkedIn/hemang-joshi-046746aa](https://www.linkedin.com/in/hemang-joshi-046746aa/) * [Tumblr/hemangjoshi37a-blog](https://www.tumblr.com/blog/hemangjoshi37a-blog) * [Pinterest/hemangjoshi37a](https://in.pinterest.com/hemangjoshi37a/) * [Blogger/hemangjoshi](http://hemangjoshi.blogspot.com/) * [Instagram/hemangjoshi37](https://www.instagram.com/hemangjoshi37/) ### Checkout Our Other Repositories - [pyPortMan](https://github.com/hemangjoshi37a/pyPortMan) - [transformers_stock_prediction](https://github.com/hemangjoshi37a/transformers_stock_prediction) - [TrendMaster](https://github.com/hemangjoshi37a/TrendMaster) - [hjAlgos_notebooks](https://github.com/hemangjoshi37a/hjAlgos_notebooks) - [AutoCut](https://github.com/hemangjoshi37a/AutoCut) - [My_Projects](https://github.com/hemangjoshi37a/My_Projects) - [Cool Arduino and ESP8266 or NodeMCU Projects](https://github.com/hemangjoshi37a/my_Arduino) - [Telegram Trade Msg Backtest ML](https://github.com/hemangjoshi37a/TelegramTradeMsgBacktestML) ### Checkout Our Other Products - [WiFi IoT LED Matrix Display](https://hjlabs.in/product/wifi-iot-led-display) - [SWiBoard WiFi Switch Board IoT Device](https://hjlabs.in/product/swiboard-wifi-switch-board-iot-device) - [Electric Bicycle](https://hjlabs.in/product/electric-bicycle) - [Product 3D Design Service with Solidworks](https://hjlabs.in/product/product-3d-design-with-solidworks/) - [AutoCut : Automatic Wire Cutter Machine](https://hjlabs.in/product/automatic-wire-cutter-machine/) - [Custom AlgoTrading Software Coding Services](https://hjlabs.in/product/custom-algotrading-software-for-zerodha-and-angel-w-source-code//) - [SWiBoard :Tasmota MQTT Control App](https://play.google.com/store/apps/details?id=in.hjlabs.swiboard) - [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/) ## Some Cool Arduino and ESP8266 (or NodeMCU) IoT projects: - [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) - [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) - [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) - [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) - [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) - [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) ## Our HuggingFace Models : - [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) ## Our HuggingFace Datasets : - [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)