This model is trained on roberta-base - https://huggingface.co/roberta-base
Dataset - https://drive.google.com/file/d/1hyXTTubD9CRjL1MBSIU_iVxFCdtGXqgB/view?usp=sharing
Notebook - https://colab.research.google.com/drive/1zHrs3hosTXBPiy0P1O-x6Z2EQ9RZGUsQ?usp=sharing
Label | Precision | Recall | F1-Score | Support |
---|---|---|---|---|
commodity | 0.41 | 0.27 | 0.32 | 89 |
company | 0.57 | 0.66 | 0.61 | 192 |
delivery_cap | 0.00 | 0.00 | 0.00 | 10 |
delivery_location | 0.57 | 0.17 | 0.27 | 46 |
delivery_port | 0.66 | 0.85 | 0.74 | 608 |
delivery_state | 0.85 | 0.48 | 0.62 | 120 |
incoterms | 0.82 | 0.94 | 0.88 | 212 |
measures | 0.75 | 0.77 | 0.76 | 682 |
package_type | 0.84 | 0.90 | 0.87 | 338 |
pickup_cap | 0.86 | 0.88 | 0.87 | 133 |
pickup_location | 0.65 | 0.68 | 0.67 | 505 |
pickup_port | 0.00 | 0.00 | 0.00 | 6 |
pickup_state | 0.79 | 0.88 | 0.83 | 92 |
quantity | 0.87 | 0.86 | 0.87 | 195 |
stackable | 0.47 | 0.38 | 0.42 | 73 |
volume | 0.36 | 0.31 | 0.33 | 71 |
weight | 0.41 | 0.52 | 0.45 | 283 |
micro avg | 0.69 | 0.73 | 0.71 | 3655 |
macro avg | 0.58 | 0.56 | 0.56 | 3655 |
weighted avg | 0.69 | 0.73 | 0.70 | 3655 |