--- 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 --- # 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