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---
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
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