---
license: mit
language:
- en
metrics:
- accuracy
library_name: transformers
pipeline_tag: text-classification
tags:
- agriculture



widget:
- text: "paddy pest"
  example_title: "Example- pest"
- text: "how do I apply for PM-Kisan"
  example_title: "Example- scheme"
- text: "Will it rain today"
  example_title: "Example- weather"
---

# Agri-flow Classification Model

This model classifies grievances into five distinct buckets:

- **Label 0**: agricultural_scheme
- **Label 1**: agriculture
- **Label 2**: pest
- **Label 3**: seed
- **Label 4**: weather
- **Label 5**: price
- **Label 6**: non_agri

## Description of the Buckets

1. **agricultural_scheme**: 
   The farmer query is about schemes in Odisha

2. **agriculture**: 
   General agri queries

3. **pest**: 
   The farmer query is about pests
   
4. **seed**:
   The farmer query is about seed varieties

5. **weather** :
  The farmer query is asking about the weather for a district /place
  e.g. :  'What's the weather forecast for Sundargarh?'

6. **price** :
   The farmer query is asking about the price of some crop 
   e.g.  'Price for paddy'

6. **non_agri** :
   The farmer query is just some salutation or unrelated to agri


## Training Metrics

The following training metrics were observed over 10 epochs:
Epoch 1/1000 - Loss: 0.8210 - Accuracy: 0.7443 - F1 Score: 0.7360
Validation Accuracy: 0.9037
Validation F1 Score: 0.9022
Epoch 2/1000 - Loss: 0.2868 - Accuracy: 0.9199 - F1 Score: 0.9197
Validation Accuracy: 0.9241
Validation F1 Score: 0.9236
Epoch 3/1000 - Loss: 0.1620 - Accuracy: 0.9536 - F1 Score: 0.9534
Validation Accuracy: 0.9408
Validation F1 Score: 0.9407
Epoch 4/1000 - Loss: 0.0975 - Accuracy: 0.9698 - F1 Score: 0.9698
Validation Accuracy: 0.9457
Validation F1 Score: 0.9461
Epoch 5/1000 - Loss: 0.0722 - Accuracy: 0.9777 - F1 Score: 0.9777
Validation Accuracy: 0.9518
Validation F1 Score: 0.9520
Epoch 6/1000 - Loss: 0.0570 - Accuracy: 0.9801 - F1 Score: 0.9801
Validation Accuracy: 0.9574
Validation F1 Score: 0.9573
Epoch 7/1000 - Loss: 0.0426 - Accuracy: 0.9838 - F1 Score: 0.9838
Validation Accuracy: 0.9601
Validation F1 Score: 0.9601
Epoch 8/1000 - Loss: 0.0403 - Accuracy: 0.9850 - F1 Score: 0.9850
Validation Accuracy: 0.9646
Validation F1 Score: 0.9646
Epoch 9/1000 - Loss: 0.0340 - Accuracy: 0.9853 - F1 Score: 0.9853
Validation Accuracy: 0.9623
Validation F1 Score: 0.9624
Epoch 10/1000 - Loss: 0.0307 - Accuracy: 0.9857 - F1 Score: 0.9857
Validation Accuracy: 0.9640
Validation F1 Score: 0.9640
Epoch 11/1000 - Loss: 0.0297 - Accuracy: 0.9873 - F1 Score: 0.9873
Validation Accuracy: 0.9618
Validation F1 Score: 0.9618
Epoch 12/1000 - Loss: 0.0279 - Accuracy: 0.9867 - F1 Score: 0.9867
Validation Accuracy: 0.9607
Validation F1 Score: 0.9607