This model is trained on bert-base-uncased & 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 0.50 0.50 0.50 66
company 0.79 0.87 0.83 164
delivery_cap 0.00 0.00 0.00 10
delivery_location 0.58 0.27 0.37 26
delivery_port 0.88 0.90 0.89 332
delivery_state 0.80 0.82 0.81 45
incoterms 0.88 0.97 0.92 187
measures 0.91 0.96 0.94 802
package_type 0.89 0.96 0.92 292
pickup_cap 0.83 0.97 0.90 139
pickup_location 0.77 0.92 0.84 356
pickup_port 0.00 0.00 0.00 3
pickup_state 0.83 0.82 0.83 67
quantity 0.93 0.90 0.92 199
stackable 0.91 0.84 0.87 57
volume 0.46 0.67 0.55 69
weight 0.81 0.83 0.82 247
-------------------- ----------- -------- ---------- ---------
micro avg 0.84 0.90 0.87 3061
macro avg 0.69 0.72 0.70 3061
weighted avg 0.84 0.90 0.87 3061