This model is trained on bert-base-multilingual-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 |
---|---|---|---|---|
client_reference | 0.44 | 0.68 | 0.54 | 22 |
contact_email | 0.72 | 0.65 | 0.68 | 43 |
contact_phone | 0.79 | 0.77 | 0.78 | 165 |
delivery_address | 0.59 | 0.60 | 0.59 | 85 |
delivery_city | 0.78 | 0.80 | 0.79 | 223 |
delivery_date | 0.59 | 0.67 | 0.63 | 33 |
delivery_name | 0.72 | 0.83 | 0.77 | 281 |
delivery_province | 0.77 | 0.79 | 0.78 | 34 |
delivery_state | 0.87 | 0.86 | 0.86 | 114 |
delivery_zipcode | 0.81 | 0.89 | 0.85 | 210 |
goods_value | 0.50 | 0.33 | 0.40 | 15 |
incoterms | 0.73 | 0.87 | 0.80 | 38 |
item_measures_body | 0.94 | 0.93 | 0.93 | 617 |
item_numpack_body | 0.77 | 0.84 | 0.80 | 163 |
item_pack_type | 0.83 | 0.90 | 0.86 | 220 |
item_stackable | 0.93 | 0.79 | 0.85 | 52 |
item_volume_body | 0.89 | 0.85 | 0.87 | 47 |
item_weight_body | 0.90 | 0.76 | 0.83 | 72 |
item_weight_body_measure_unit | 0.87 | 0.88 | 0.87 | 83 |
numpack_tot | 0.81 | 0.81 | 0.81 | 108 |
pick_up_date | 0.84 | 0.93 | 0.88 | 132 |
pickup_address | 0.66 | 0.74 | 0.70 | 98 |
pickup_city | 0.85 | 0.82 | 0.83 | 234 |
pickup_name | 0.84 | 0.80 | 0.82 | 215 |
pickup_province | 0.92 | 0.93 | 0.92 | 70 |
pickup_state | 0.94 | 0.58 | 0.71 | 26 |
pickup_zipcode | 0.88 | 0.85 | 0.86 | 205 |
tot_pack_dimension | 0.76 | 0.83 | 0.80 | 290 |
tot_pack_type | 0.84 | 0.84 | 0.84 | 195 |
volumes_tot | 0.88 | 0.94 | 0.91 | 31 |
weight_measure_unit | 0.91 | 0.94 | 0.92 | 143 |
weight_tot | 0.90 | 0.91 | 0.91 | 176 |
--------------------------- | ----------- | -------- | ---------- | --------- |
micro avg | 0.82 | 0.85 | 0.83 | 4440 |
macro avg | 0.80 | 0.80 | 0.79 | 4440 |
weighted avg | 0.83 | 0.85 | 0.83 | 4440 |