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--- |
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license: mit |
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language: |
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- en |
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metrics: |
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- accuracy |
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library_name: transformers |
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pipeline_tag: text-classification |
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tags: |
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- agriculture |
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widget: |
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- text: "paddy pest" |
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example_title: "Example- pest" |
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- text: "how do I apply for PM-Kisan" |
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example_title: "Example- scheme" |
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- text: "Will it rain today" |
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example_title: "Example- weather" |
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--- |
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# Agri-flow Classification Model |
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This model classifies grievances into five distinct buckets: |
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- **Label 0**: agricultural_scheme |
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- **Label 1**: agriculture |
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- **Label 2**: pest |
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- **Label 3**: seed |
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- **Label 4**: weather |
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- **Label 5**: price |
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- **Label 6**: non_agri |
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## Description of the Buckets |
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1. **agricultural_scheme**: |
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The farmer query is about schemes in Odisha |
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2. **agriculture**: |
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General agri queries |
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3. **pest**: |
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The farmer query is about pests |
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4. **seed**: |
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The farmer query is about seed varieties |
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5. **weather** : |
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The farmer query is asking about the weather for a district /place |
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e.g. : 'What's the weather forecast for Sundargarh?' |
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6. **price** : |
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The farmer query is asking about the price of some crop |
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e.g. 'Price for paddy' |
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6. **non_agri** : |
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The farmer query is just some salutation or unrelated to agri |
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## Training Metrics |
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The following training metrics were observed over 10 epochs: |
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Epoch 1/1000 - Loss: 0.8210 - Accuracy: 0.7443 - F1 Score: 0.7360 |
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Validation Accuracy: 0.9037 |
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Validation F1 Score: 0.9022 |
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Epoch 2/1000 - Loss: 0.2868 - Accuracy: 0.9199 - F1 Score: 0.9197 |
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Validation Accuracy: 0.9241 |
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Validation F1 Score: 0.9236 |
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Epoch 3/1000 - Loss: 0.1620 - Accuracy: 0.9536 - F1 Score: 0.9534 |
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Validation Accuracy: 0.9408 |
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Validation F1 Score: 0.9407 |
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Epoch 4/1000 - Loss: 0.0975 - Accuracy: 0.9698 - F1 Score: 0.9698 |
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Validation Accuracy: 0.9457 |
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Validation F1 Score: 0.9461 |
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Epoch 5/1000 - Loss: 0.0722 - Accuracy: 0.9777 - F1 Score: 0.9777 |
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Validation Accuracy: 0.9518 |
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Validation F1 Score: 0.9520 |
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Epoch 6/1000 - Loss: 0.0570 - Accuracy: 0.9801 - F1 Score: 0.9801 |
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Validation Accuracy: 0.9574 |
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Validation F1 Score: 0.9573 |
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Epoch 7/1000 - Loss: 0.0426 - Accuracy: 0.9838 - F1 Score: 0.9838 |
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Validation Accuracy: 0.9601 |
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Validation F1 Score: 0.9601 |
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Epoch 8/1000 - Loss: 0.0403 - Accuracy: 0.9850 - F1 Score: 0.9850 |
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Validation Accuracy: 0.9646 |
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Validation F1 Score: 0.9646 |
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Epoch 9/1000 - Loss: 0.0340 - Accuracy: 0.9853 - F1 Score: 0.9853 |
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Validation Accuracy: 0.9623 |
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Validation F1 Score: 0.9624 |
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Epoch 10/1000 - Loss: 0.0307 - Accuracy: 0.9857 - F1 Score: 0.9857 |
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Validation Accuracy: 0.9640 |
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Validation F1 Score: 0.9640 |
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Epoch 11/1000 - Loss: 0.0297 - Accuracy: 0.9873 - F1 Score: 0.9873 |
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Validation Accuracy: 0.9618 |
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Validation F1 Score: 0.9618 |
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Epoch 12/1000 - Loss: 0.0279 - Accuracy: 0.9867 - F1 Score: 0.9867 |
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Validation Accuracy: 0.9607 |
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Validation F1 Score: 0.9607 |
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