This model is trained on distilbert-base-multilingual-cased & 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 0.27 0.24 0.26 99
company 0.67 0.70 0.68 180
delivery_cap 0.00 0.00 0.00 10
delivery_location 0.50 0.11 0.17 38
delivery_port 0.72 0.86 0.79 590
delivery_state 0.74 0.29 0.42 95
incoterms 0.74 0.92 0.82 234
measures 0.88 0.94 0.91 811
package_type 0.78 0.92 0.84 318
pickup_cap 0.69 0.96 0.80 141
pickup_location 0.59 0.83 0.69 442
pickup_port 0.00 0.00 0.00 3
pickup_state 0.73 0.85 0.79 115
quantity 0.85 0.88 0.86 199
stackable 0.60 0.36 0.45 78
volume 0.46 0.53 0.49 79
weight 0.64 0.68 0.66 266
micro avg 0.72 0.81 0.76 3698
macro avg 0.58 0.59 0.57 3698
weighted avg 0.72 0.81 0.75 3698