
# 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)  


## Checkout Our Awesome 3D GrabCAD Models:
- [AutoCut : Automatic Wire Cutter Machine](https://grabcad.com/library/automatic-wire-cutter-machine-1)
- [ESP Matrix Display 5mm Acrylic Box](https://grabcad.com/library/esp-matrix-display-5mm-acrylic-box-1)
- [Arcylic Bending Machine w/ Hot Air Gun](https://grabcad.com/library/arcylic-bending-machine-w-hot-air-gun-1)
- [Automatic Wire Cutter/Stripper](https://grabcad.com/library/automatic-wire-cutter-stripper-1)

## 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)

## We sell Gigs on Fiverr : 
- [code android and ios app for you using flutter firebase software stack](https://business.fiverr.com/share/3v14pr)
- [code custom algotrading software for zerodha or angel broking](https://business.fiverr.com/share/kzkvEy)

## Awesome Fiverr. Gigs:
- [develop machine learning ner model as in nlp using python](https://www.fiverr.com/share/9YNabx)
- [train custom chatgpt question answering model](https://www.fiverr.com/share/rwx6r7)
- [build algotrading, backtesting and stock monitoring tools using python](https://www.fiverr.com/share/A7Y14q)
- [tutor you in your science problems](https://www.fiverr.com/share/zPzmlz)
- [make apps for you crossplatform	](https://www.fiverr.com/share/BGw12l)

{"language": ["en"], "tags": ["autotrain", "token-classification"], "datasets": ["hemangjoshi37a/autotrain-data-ratnakar_1000_sample_curated"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": {"emissions": 2.1802563684907916}}
transformers pytorch autotrain token-classification en dataset:hemangjoshi37a/autotrain-data-ratnakar_1000_sample_curated co2_eq_emissions endpoints_compatible region:us
TAGS
#transformers #pytorch #autotrain #token-classification #en #dataset-hemangjoshi37a/autotrain-data-ratnakar_1000_sample_curated #co2_eq_emissions #endpoints_compatible #region-us 


# 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:



Or Python API:




# GitHub Link to this project : Telegram Trade Msg Backtest ML

# Need custom model for your application? : Place a order on URL : 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 convert to  !Screenshot from 2022-09-30 18-59-14

2. Convert LabelStudio CSV or JSON to HuggingFace-autoTrain dataset conversion script
!Screenshot from 2022-10-01 10-36-03

3. Train NER model on Hugginface-autoTrain.
 !Screenshot from 2022-10-01 10-38-24

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
 !Screenshot from 2022-10-01 10-42-36
 !Screenshot from 2022-10-01 10-44-56

5. Define python function to predict labels using Hugginface-autoTrain model.
 !Screenshot from 2022-10-01 10-47-08
!Screenshot from 2022-10-01 10-47-25

6. Only label new data from newly predicted-labels-dataset that has falsified labels.
 !Screenshot from 2022-09-30 22-47-23

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

8. Evaluate total gained percentage since inception summation-wise and compounded and plot.
 !Screenshot from 2022-10-01 00-06-59

9. Listen to telegram channel for new LIVE messages using telegram API for algotrading.
 !Screenshot from 2022-10-01 00-09-29

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

11. Outperforming or underperforming results of the telegram channel tips against exchange index by percentage.
 !Screenshot from 2022-10-01 11-16-27



Place a custom order on URL : URL


----------------------------------------------------------------------

### Social Media :
* WhatsApp/917016525813
* telegram/hjlabs 
* Gmail/hemangjoshi37a@URL
* Facebook/hemangjoshi37
* Twitter/HemangJ81509525
* LinkedIn/hemang-joshi-046746aa
* Tumblr/hemangjoshi37a-blog
* Pinterest/hemangjoshi37a
* Blogger/hemangjoshi
* Instagram/hemangjoshi37
  
### Checkout Our Other Repositories

- pyPortMan
- transformers_stock_prediction
- TrendMaster
- hjAlgos_notebooks
- AutoCut
- My_Projects
- Cool Arduino and ESP8266 or NodeMCU Projects
- Telegram Trade Msg Backtest ML

### Checkout Our Other Products

- WiFi IoT LED Matrix Display
- SWiBoard WiFi Switch Board IoT Device
- Electric Bicycle
- Product 3D Design Service with Solidworks
- AutoCut : Automatic Wire Cutter Machine
- Custom AlgoTrading Software Coding Services
- SWiBoard :Tasmota MQTT Control App
- 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
- ESP8266_NodeMCU_BasicOTA : Simple OTA (Over The Air) upload code from Arduino IDE using WiFi to NodeMCU or ESP8266  
- IoT_CSV_SD : Read analog value of Voltage and Current and write it to SD Card in CSV format for Arduino, ESP8266, NodeMCU etc  
- Honeywell_I2C_Datalogger : Log data in A SD Card from a Honeywell I2C HIH8000 or HIH6000 series sensor having external I2C RTC clock
- 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
- 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  


## Checkout Our Awesome 3D GrabCAD Models:
- AutoCut : Automatic Wire Cutter Machine
- ESP Matrix Display 5mm Acrylic Box
- Arcylic Bending Machine w/ Hot Air Gun
- Automatic Wire Cutter/Stripper

## 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.

## 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.

## We sell Gigs on Fiverr : 
- code android and ios app for you using flutter firebase software stack
- code custom algotrading software for zerodha or angel broking

## Awesome Fiverr. Gigs:
- develop machine learning ner model as in nlp using python
- train custom chatgpt question answering model
- build algotrading, backtesting and stock monitoring tools using python
- tutor you in your science problems
- make apps for you crossplatform	

# 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:



Or Python API: # GitHub Link to this project : Telegram Trade Msg Backtest ML # Need custom model for your application? : Place a order on URL : 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 convert to  !Screenshot from 2022-09-30 18-59-14

2. Convert LabelStudio CSV or JSON to HuggingFace-autoTrain dataset conversion script
!Screenshot from 2022-10-01 10-36-03

3. Train NER model on Hugginface-autoTrain.
 !Screenshot from 2022-10-01 10-38-24

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
 !Screenshot from 2022-10-01 10-42-36
 !Screenshot from 2022-10-01 10-44-56

5. Define python function to predict labels using Hugginface-autoTrain model.
 !Screenshot from 2022-10-01 10-47-08
!Screenshot from 2022-10-01 10-47-25

6. Only label new data from newly predicted-labels-dataset that has falsified labels.
 !Screenshot from 2022-09-30 22-47-23

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

8. Evaluate total gained percentage since inception summation-wise and compounded and plot.
 !Screenshot from 2022-10-01 00-06-59

9. Listen to telegram channel for new LIVE messages using telegram API for algotrading.
 !Screenshot from 2022-10-01 00-09-29

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

11. Outperforming or underperforming results of the telegram channel tips against exchange index by percentage.
 !Screenshot from 2022-10-01 11-16-27



Place a custom order on URL : URL


---------------------------------------------------------------------- ### Social Media :
* WhatsApp/917016525813
* telegram/hjlabs 
* Gmail/hemangjoshi37a@URL
* Facebook/hemangjoshi37
* Twitter/HemangJ81509525
* LinkedIn/hemang-joshi-046746aa
* Tumblr/hemangjoshi37a-blog
* Pinterest/hemangjoshi37a
* Blogger/hemangjoshi
* Instagram/hemangjoshi37 ### Checkout Our Other Repositories

- pyPortMan
- transformers_stock_prediction
- TrendMaster
- hjAlgos_notebooks
- AutoCut
- My_Projects
- Cool Arduino and ESP8266 or NodeMCU Projects
- Telegram Trade Msg Backtest ML ### Checkout Our Other Products

- WiFi IoT LED Matrix Display
- SWiBoard WiFi Switch Board IoT Device
- Electric Bicycle
- Product 3D Design Service with Solidworks
- AutoCut : Automatic Wire Cutter Machine
- Custom AlgoTrading Software Coding Services
- SWiBoard :Tasmota MQTT Control App
- 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
- ESP8266_NodeMCU_BasicOTA : Simple OTA (Over The Air) upload code from Arduino IDE using WiFi to NodeMCU or ESP8266  
- IoT_CSV_SD : Read analog value of Voltage and Current and write it to SD Card in CSV format for Arduino, ESP8266, NodeMCU etc  
- Honeywell_I2C_Datalogger : Log data in A SD Card from a Honeywell I2C HIH8000 or HIH6000 series sensor having external I2C RTC clock
- 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
- 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 ## Checkout Our Awesome 3D GrabCAD Models:
- AutoCut : Automatic Wire Cutter Machine
- ESP Matrix Display 5mm Acrylic Box
- Arcylic Bending Machine w/ Hot Air Gun
- Automatic Wire Cutter/Stripper ## 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. ## 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. ## We sell Gigs on Fiverr : 
- code android and ios app for you using flutter firebase software stack
- code custom algotrading software for zerodha or angel broking ## Awesome Fiverr. Gigs:
- develop machine learning ner model as in nlp using python
- train custom chatgpt question answering model
- build algotrading, backtesting and stock monitoring tools using python
- tutor you in your science problems
- make apps for you crossplatform
TAGS
#transformers #pytorch #autotrain #token-classification #en #dataset-hemangjoshi37a/autotrain-data-ratnakar_1000_sample_curated #co2_eq_emissions #endpoints_compatible #region-us 
 # 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:



Or Python API: # GitHub Link to this project : Telegram Trade Msg Backtest ML # Need custom model for your application? : Place a order on URL : 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 convert to  !Screenshot from 2022-09-30 18-59-14

2. Convert LabelStudio CSV or JSON to HuggingFace-autoTrain dataset conversion script
!Screenshot from 2022-10-01 10-36-03

3. Train NER model on Hugginface-autoTrain.
 !Screenshot from 2022-10-01 10-38-24

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
 !Screenshot from 2022-10-01 10-42-36
 !Screenshot from 2022-10-01 10-44-56

5. Define python function to predict labels using Hugginface-autoTrain model.
 !Screenshot from 2022-10-01 10-47-08
!Screenshot from 2022-10-01 10-47-25

6. Only label new data from newly predicted-labels-dataset that has falsified labels.
 !Screenshot from 2022-09-30 22-47-23

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

8. Evaluate total gained percentage since inception summation-wise and compounded and plot.
 !Screenshot from 2022-10-01 00-06-59

9. Listen to telegram channel for new LIVE messages using telegram API for algotrading.
 !Screenshot from 2022-10-01 00-09-29

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

11. Outperforming or underperforming results of the telegram channel tips against exchange index by percentage.
 !Screenshot from 2022-10-01 11-16-27



Place a custom order on URL : URL


---------------------------------------------------------------------- ### Social Media :
* WhatsApp/917016525813
* telegram/hjlabs 
* Gmail/hemangjoshi37a@URL
* Facebook/hemangjoshi37
* Twitter/HemangJ81509525
* LinkedIn/hemang-joshi-046746aa
* Tumblr/hemangjoshi37a-blog
* Pinterest/hemangjoshi37a
* Blogger/hemangjoshi
* Instagram/hemangjoshi37 ### Checkout Our Other Repositories

- pyPortMan
- transformers_stock_prediction
- TrendMaster
- hjAlgos_notebooks
- AutoCut
- My_Projects
- Cool Arduino and ESP8266 or NodeMCU Projects
- Telegram Trade Msg Backtest ML ### Checkout Our Other Products

- WiFi IoT LED Matrix Display
- SWiBoard WiFi Switch Board IoT Device
- Electric Bicycle
- Product 3D Design Service with Solidworks
- AutoCut : Automatic Wire Cutter Machine
- Custom AlgoTrading Software Coding Services
- SWiBoard :Tasmota MQTT Control App
- 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
- ESP8266_NodeMCU_BasicOTA : Simple OTA (Over The Air) upload code from Arduino IDE using WiFi to NodeMCU or ESP8266  
- IoT_CSV_SD : Read analog value of Voltage and Current and write it to SD Card in CSV format for Arduino, ESP8266, NodeMCU etc  
- Honeywell_I2C_Datalogger : Log data in A SD Card from a Honeywell I2C HIH8000 or HIH6000 series sensor having external I2C RTC clock
- 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
- 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 ## Checkout Our Awesome 3D GrabCAD Models:
- AutoCut : Automatic Wire Cutter Machine
- ESP Matrix Display 5mm Acrylic Box
- Arcylic Bending Machine w/ Hot Air Gun
- Automatic Wire Cutter/Stripper ## 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. ## 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. ## We sell Gigs on Fiverr : 
- code android and ios app for you using flutter firebase software stack
- code custom algotrading software for zerodha or angel broking ## Awesome Fiverr. Gigs:
- develop machine learning ner model as in nlp using python
- train custom chatgpt question answering model
- build algotrading, backtesting and stock monitoring tools using python
- tutor you in your science problems
- make apps for you crossplatform
passage: TAGS
#transformers #pytorch #autotrain #token-classification #en #dataset-hemangjoshi37a/autotrain-data-ratnakar_1000_sample_curated #co2_eq_emissions #endpoints_compatible #region-us 
# 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:



Or Python API:# GitHub Link to this project : Telegram Trade Msg Backtest ML# Need custom model for your application? : Place a order on URL : Custom Token Classification or Named Entity Recognition (NER) model as in Natural Language Processing (NLP) Machine Learning passage: ## 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 convert to  !Screenshot from 2022-09-30 18-59-14

2. Convert LabelStudio CSV or JSON to HuggingFace-autoTrain dataset conversion script
!Screenshot from 2022-10-01 10-36-03

3. Train NER model on Hugginface-autoTrain.
 !Screenshot from 2022-10-01 10-38-24

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
 !Screenshot from 2022-10-01 10-42-36
 !Screenshot from 2022-10-01 10-44-56

5. Define python function to predict labels using Hugginface-autoTrain model.
 !Screenshot from 2022-10-01 10-47-08
!Screenshot from 2022-10-01 10-47-25

6. Only label new data from newly predicted-labels-dataset that has falsified labels.
 !Screenshot from 2022-09-30 22-47-23

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

8. Evaluate total gained percentage since inception summation-wise and compounded and plot.
 !Screenshot from 2022-10-01 00-06-59

9. Listen to telegram channel for new LIVE messages using telegram API for algotrading.
 !Screenshot from 2022-10-01 00-09-29

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

11. Outperforming or underperforming results of the telegram channel tips against exchange index by percentage.
 !Screenshot from 2022-10-01 11-16-27



Place a custom order on URL : URL


----------------------------------------------------------------------### Social Media :
* WhatsApp/917016525813
* telegram/hjlabs 
* Gmail/hemangjoshi37a@URL
* Facebook/hemangjoshi37
* Twitter/HemangJ81509525
* LinkedIn/hemang-joshi-046746aa
* Tumblr/hemangjoshi37a-blog
* Pinterest/hemangjoshi37a
* Blogger/hemangjoshi
* Instagram/hemangjoshi37### Checkout Our Other Repositories

- pyPortMan
- transformers_stock_prediction
- TrendMaster
- hjAlgos_notebooks
- AutoCut
- My_Projects
- Cool Arduino and ESP8266 or NodeMCU Projects
- Telegram Trade Msg Backtest ML### Checkout Our Other Products

- WiFi IoT LED Matrix Display
- SWiBoard WiFi Switch Board IoT Device
- Electric Bicycle
- Product 3D Design Service with Solidworks
- AutoCut : Automatic Wire Cutter Machine
- Custom AlgoTrading Software Coding Services
- SWiBoard :Tasmota MQTT Control App
- Custom Token Classification or Named Entity Recognition (NER) model as in Natural Language Processing (NLP) Machine Learning