This model is trained on xlm-roberta-base - https://huggingface.co/xlm-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 0.17 0.14 0.15 81
company 0.59 0.74 0.66 184
delivery_cap 0.00 0.00 0.00 11
delivery_location 0.00 0.00 0.00 34
delivery_port 0.54 0.83 0.65 488
delivery_state 0.60 0.04 0.08 73
incoterms 0.86 0.76 0.81 194
measures 0.88 0.91 0.90 686
package_type 0.78 0.93 0.85 316
pickup_cap 0.81 0.97 0.88 137
pickup_location 0.61 0.67 0.63 407
pickup_port 0.00 0.00 0.00 4
pickup_state 0.70 0.91 0.79 107
quantity 0.87 0.89 0.88 198
stackable 0.57 0.43 0.49 56
volume 0.53 0.11 0.18 84
weight 0.50 0.72 0.59 279
micro avg 0.68 0.76 0.72 3339
macro avg 0.53 0.53 0.50 3339
weighted avg 0.68 0.76 0.70 3339