| | --- |
| | license: apache-2.0 |
| | base_model: bert-base-cased |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - wnut_17 |
| | metrics: |
| | - precision |
| | - recall |
| | - f1 |
| | - accuracy |
| | model-index: |
| | - name: bert-finetuned-ner |
| | results: |
| | - task: |
| | name: Token Classification |
| | type: token-classification |
| | dataset: |
| | name: wnut_17 |
| | type: wnut_17 |
| | config: wnut_17 |
| | split: test |
| | args: wnut_17 |
| | metrics: |
| | - name: Precision |
| | type: precision |
| | value: 0.5254237288135594 |
| | - name: Recall |
| | type: recall |
| | value: 0.3160333642261353 |
| | - name: F1 |
| | type: f1 |
| | value: 0.3946759259259259 |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.9350753768844221 |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # bert-finetuned-ner |
| |
|
| | This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the wnut_17 dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.4362 |
| | - Precision: 0.5254 |
| | - Recall: 0.3160 |
| | - F1: 0.3947 |
| | - Accuracy: 0.9351 |
| | - Corporation Precision: 0.1833 |
| | - Corporation Recall: 0.1667 |
| | - Corporation F1: 0.1746 |
| | - Creative-work Precision: 0.4308 |
| | - Creative-work Recall: 0.1972 |
| | - Creative-work F1: 0.2705 |
| | - Group Precision: 0.3467 |
| | - Group Recall: 0.1576 |
| | - Group F1: 0.2167 |
| | - Location Precision: 0.55 |
| | - Location Recall: 0.44 |
| | - Location F1: 0.4889 |
| | - Person Precision: 0.8008 |
| | - Person Recall: 0.4592 |
| | - Person F1: 0.5837 |
| | - Product Precision: 0.1566 |
| | - Product Recall: 0.1024 |
| | - Product F1: 0.1238 |
| | - B-corporation Precision: 0.3256 |
| | - B-corporation Recall: 0.2121 |
| | - B-corporation F1: 0.2569 |
| | - B-creative-work Precision: 0.76 |
| | - B-creative-work Recall: 0.2676 |
| | - B-creative-work F1: 0.3958 |
| | - B-group Precision: 0.5179 |
| | - B-group Recall: 0.1758 |
| | - B-group F1: 0.2624 |
| | - B-location Precision: 0.6792 |
| | - B-location Recall: 0.48 |
| | - B-location F1: 0.5625 |
| | - B-person Precision: 0.8615 |
| | - B-person Recall: 0.4639 |
| | - B-person F1: 0.6030 |
| | - B-product Precision: 0.4468 |
| | - B-product Recall: 0.1654 |
| | - B-product F1: 0.2414 |
| | - I-corporation Precision: 0.2889 |
| | - I-corporation Recall: 0.2364 |
| | - I-corporation F1: 0.26 |
| | - I-creative-work Precision: 0.45 |
| | - I-creative-work Recall: 0.2093 |
| | - I-creative-work F1: 0.2857 |
| | - I-group Precision: 0.2549 |
| | - I-group Recall: 0.1150 |
| | - I-group F1: 0.1585 |
| | - I-location Precision: 0.5606 |
| | - I-location Recall: 0.3895 |
| | - I-location F1: 0.4596 |
| | - I-person Precision: 0.7564 |
| | - I-person Recall: 0.3512 |
| | - I-person F1: 0.4797 |
| | - I-product Precision: 0.1972 |
| | - I-product Recall: 0.1157 |
| | - I-product F1: 0.1458 |
| | |
| | ## Model description |
| | |
| | More information needed |
| | |
| | ## Intended uses & limitations |
| | |
| | More information needed |
| | |
| | ## Training and evaluation data |
| | |
| | More information needed |
| | |
| | ## Training procedure |
| | |
| | ### Training hyperparameters |
| | |
| | The following hyperparameters were used during training: |
| | - learning_rate: 2e-05 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 3 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Corporation Precision | Corporation Recall | Corporation F1 | Creative-work Precision | Creative-work Recall | Creative-work F1 | Group Precision | Group Recall | Group F1 | Location Precision | Location Recall | Location F1 | Person Precision | Person Recall | Person F1 | Product Precision | Product Recall | Product F1 | B-corporation Precision | B-corporation Recall | B-corporation F1 | B-creative-work Precision | B-creative-work Recall | B-creative-work F1 | B-group Precision | B-group Recall | B-group F1 | B-location Precision | B-location Recall | B-location F1 | B-person Precision | B-person Recall | B-person F1 | B-product Precision | B-product Recall | B-product F1 | I-corporation Precision | I-corporation Recall | I-corporation F1 | I-creative-work Precision | I-creative-work Recall | I-creative-work F1 | I-group Precision | I-group Recall | I-group F1 | I-location Precision | I-location Recall | I-location F1 | I-person Precision | I-person Recall | I-person F1 | I-product Precision | I-product Recall | I-product F1 | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:---------------------:|:------------------:|:--------------:|:-----------------------:|:--------------------:|:----------------:|:---------------:|:------------:|:--------:|:------------------:|:---------------:|:-----------:|:----------------:|:-------------:|:---------:|:-----------------:|:--------------:|:----------:|:-----------------------:|:--------------------:|:----------------:|:-------------------------:|:----------------------:|:------------------:|:-----------------:|:--------------:|:----------:|:--------------------:|:-----------------:|:-------------:|:------------------:|:---------------:|:-----------:|:-------------------:|:----------------:|:------------:|:-----------------------:|:--------------------:|:----------------:|:-------------------------:|:----------------------:|:------------------:|:-----------------:|:--------------:|:----------:|:--------------------:|:-----------------:|:-------------:|:------------------:|:---------------:|:-----------:|:-------------------:|:----------------:|:------------:| |
| | | No log | 1.0 | 425 | 0.3879 | 0.5038 | 0.2484 | 0.3327 | 0.9296 | 0.0714 | 0.0455 | 0.0556 | 0.1429 | 0.0070 | 0.0134 | 0.1667 | 0.0909 | 0.1176 | 0.4583 | 0.3667 | 0.4074 | 0.7569 | 0.4499 | 0.5643 | 0.0556 | 0.0079 | 0.0138 | 0.3333 | 0.1364 | 0.1935 | 1.0 | 0.0282 | 0.0548 | 0.4722 | 0.1030 | 0.1692 | 0.6162 | 0.4067 | 0.4900 | 0.9037 | 0.4592 | 0.6090 | 0.5 | 0.0157 | 0.0305 | 0.1111 | 0.0545 | 0.0732 | 0.5 | 0.0155 | 0.0301 | 0.12 | 0.0796 | 0.0957 | 0.4595 | 0.3579 | 0.4024 | 0.7108 | 0.3512 | 0.4701 | 0.125 | 0.0165 | 0.0292 | |
| | | 0.196 | 2.0 | 850 | 0.4338 | 0.5712 | 0.2864 | 0.3815 | 0.9328 | 0.2174 | 0.2273 | 0.2222 | 0.4762 | 0.1408 | 0.2174 | 0.35 | 0.0848 | 0.1366 | 0.5727 | 0.42 | 0.4846 | 0.7992 | 0.4452 | 0.5719 | 0.1463 | 0.0472 | 0.0714 | 0.3208 | 0.2576 | 0.2857 | 0.8065 | 0.1761 | 0.2890 | 0.6 | 0.0909 | 0.1579 | 0.7216 | 0.4667 | 0.5668 | 0.8807 | 0.4476 | 0.5935 | 0.6522 | 0.1181 | 0.2 | 0.2917 | 0.2545 | 0.2718 | 0.6 | 0.1860 | 0.2840 | 0.2857 | 0.0708 | 0.1135 | 0.5625 | 0.3789 | 0.4528 | 0.7566 | 0.3423 | 0.4713 | 0.1765 | 0.0496 | 0.0774 | |
| | | 0.0785 | 3.0 | 1275 | 0.4362 | 0.5254 | 0.3160 | 0.3947 | 0.9351 | 0.1833 | 0.1667 | 0.1746 | 0.4308 | 0.1972 | 0.2705 | 0.3467 | 0.1576 | 0.2167 | 0.55 | 0.44 | 0.4889 | 0.8008 | 0.4592 | 0.5837 | 0.1566 | 0.1024 | 0.1238 | 0.3256 | 0.2121 | 0.2569 | 0.76 | 0.2676 | 0.3958 | 0.5179 | 0.1758 | 0.2624 | 0.6792 | 0.48 | 0.5625 | 0.8615 | 0.4639 | 0.6030 | 0.4468 | 0.1654 | 0.2414 | 0.2889 | 0.2364 | 0.26 | 0.45 | 0.2093 | 0.2857 | 0.2549 | 0.1150 | 0.1585 | 0.5606 | 0.3895 | 0.4596 | 0.7564 | 0.3512 | 0.4797 | 0.1972 | 0.1157 | 0.1458 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.35.0 |
| | - Pytorch 2.1.0+cu118 |
| | - Datasets 2.14.6 |
| | - Tokenizers 0.14.1 |
| | |
