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 0.38 0.22 0.28 102
company 0.69 0.72 0.70 205
delivery_cap 0.00 0.00 0.00 11
delivery_location 0.81 0.33 0.46 40
delivery_port 0.78 0.87 0.82 623
delivery_state 0.86 0.46 0.60 109
incoterms 0.89 0.92 0.90 276
measures 0.92 0.94 0.93 834
package_type 0.88 0.87 0.88 377
pickup_cap 0.79 0.92 0.85 149
pickup_location 0.67 0.74 0.71 513
pickup_port 0.00 0.00 0.00 5
pickup_state 0.75 0.85 0.80 114
quantity 0.90 0.82 0.86 201
stackable 0.79 0.60 0.69 81
volume 0.71 0.72 0.71 88
weight 0.76 0.81 0.79 324
-------------------- ----------- -------- ---------- ---------
micro avg 0.81 0.81 0.81 4052
macro avg 0.68 0.63 0.65 4052
weighted avg 0.80 0.81 0.80 4052