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--- |
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license: apache-2.0 |
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base_model: bert-base-cased |
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tags: |
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- generated_from_trainer |
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datasets: |
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- wnut_17 |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: bert-finetuned-ner |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: wnut_17 |
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type: wnut_17 |
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config: wnut_17 |
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split: test |
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args: wnut_17 |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.5091743119266054 |
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- name: Recall |
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type: recall |
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value: 0.3086190917516219 |
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- name: F1 |
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type: f1 |
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value: 0.38430467397576457 |
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- name: Accuracy |
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type: accuracy |
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value: 0.935251256281407 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# bert-finetuned-ner |
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the wnut_17 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4256 |
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- Precision: 0.5092 |
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- Recall: 0.3086 |
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- F1: 0.3843 |
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- Accuracy: 0.9353 |
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- Corporation Precision: 0.2188 |
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- Corporation Recall: 0.2121 |
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- Corporation F1: 0.2154 |
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- Creative-work Precision: 0.3768 |
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- Creative-work Recall: 0.1831 |
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- Creative-work F1: 0.2464 |
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- Group Precision: 0.3594 |
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- Group Recall: 0.1394 |
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- Group F1: 0.2009 |
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- Location Precision: 0.5439 |
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- Location Recall: 0.4133 |
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- Location F1: 0.4697 |
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- Person Precision: 0.7538 |
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- Person Recall: 0.4569 |
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- Person F1: 0.5689 |
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- Product Precision: 0.1446 |
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- Product Recall: 0.0945 |
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- Product F1: 0.1143 |
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- B-corporation Precision: 0.3333 |
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- B-corporation Recall: 0.2424 |
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- B-corporation F1: 0.2807 |
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- B-creative-work Precision: 0.8158 |
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- B-creative-work Recall: 0.2183 |
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- B-creative-work F1: 0.3444 |
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- B-group Precision: 0.4906 |
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- B-group Recall: 0.1576 |
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- B-group F1: 0.2385 |
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- B-location Precision: 0.6606 |
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- B-location Recall: 0.48 |
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- B-location F1: 0.5560 |
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- B-person Precision: 0.8423 |
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- B-person Recall: 0.4732 |
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- B-person F1: 0.6060 |
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- B-product Precision: 0.4792 |
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- B-product Recall: 0.1811 |
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- B-product F1: 0.2629 |
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- I-corporation Precision: 0.3404 |
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- I-corporation Recall: 0.2909 |
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- I-corporation F1: 0.3137 |
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- I-creative-work Precision: 0.4559 |
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- I-creative-work Recall: 0.2403 |
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- I-creative-work F1: 0.3147 |
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- I-group Precision: 0.3333 |
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- I-group Recall: 0.1150 |
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- I-group F1: 0.1711 |
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- I-location Precision: 0.5849 |
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- I-location Recall: 0.3263 |
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- I-location F1: 0.4189 |
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- I-person Precision: 0.7375 |
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- I-person Recall: 0.3512 |
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- I-person F1: 0.4758 |
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- I-product Precision: 0.2206 |
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- I-product Recall: 0.1240 |
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- I-product F1: 0.1587 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3 |
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### Training results |
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| 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 | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:---------------------:|:------------------:|:--------------:|:-----------------------:|:--------------------:|:----------------:|:---------------:|:------------:|:--------:|:------------------:|:---------------:|:-----------:|:----------------:|:-------------:|:---------:|:-----------------:|:--------------:|:----------:|:-----------------------:|:--------------------:|:----------------:|:-------------------------:|:----------------------:|:------------------:|:-----------------:|:--------------:|:----------:|:--------------------:|:-----------------:|:-------------:|:------------------:|:---------------:|:-----------:|:-------------------:|:----------------:|:------------:|:-----------------------:|:--------------------:|:----------------:|:-------------------------:|:----------------------:|:------------------:|:-----------------:|:--------------:|:----------:|:--------------------:|:-----------------:|:-------------:|:------------------:|:---------------:|:-----------:|:-------------------:|:----------------:|:------------:| |
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| No log | 1.0 | 425 | 0.3964 | 0.4911 | 0.2558 | 0.3364 | 0.9301 | 0.1579 | 0.1364 | 0.1463 | 0.0 | 0.0 | 0.0 | 0.2157 | 0.0667 | 0.1019 | 0.4490 | 0.44 | 0.4444 | 0.7412 | 0.4406 | 0.5526 | 0.0233 | 0.0079 | 0.0118 | 0.2558 | 0.1667 | 0.2018 | 0.0 | 0.0 | 0.0 | 0.52 | 0.0788 | 0.1368 | 0.5703 | 0.4867 | 0.5252 | 0.9019 | 0.4499 | 0.6003 | 0.25 | 0.0079 | 0.0153 | 0.3571 | 0.1818 | 0.2410 | 0.5556 | 0.0388 | 0.0725 | 0.1471 | 0.0442 | 0.0680 | 0.4198 | 0.3579 | 0.3864 | 0.7152 | 0.3512 | 0.4711 | 0.2143 | 0.0744 | 0.1104 | |
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| 0.2016 | 2.0 | 850 | 0.4337 | 0.5407 | 0.2706 | 0.3607 | 0.9327 | 0.1897 | 0.1667 | 0.1774 | 0.3488 | 0.1056 | 0.1622 | 0.3077 | 0.0727 | 0.1176 | 0.5327 | 0.38 | 0.4436 | 0.7837 | 0.4476 | 0.5697 | 0.1042 | 0.0394 | 0.0571 | 0.2979 | 0.2121 | 0.2478 | 0.9048 | 0.1338 | 0.2331 | 0.48 | 0.0727 | 0.1263 | 0.6915 | 0.4333 | 0.5328 | 0.8855 | 0.4685 | 0.6128 | 0.6875 | 0.0866 | 0.1538 | 0.3243 | 0.2182 | 0.2609 | 0.5 | 0.1628 | 0.2456 | 0.25 | 0.0619 | 0.0993 | 0.5660 | 0.3158 | 0.4054 | 0.76 | 0.3393 | 0.4691 | 0.2093 | 0.0744 | 0.1098 | |
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| 0.0823 | 3.0 | 1275 | 0.4256 | 0.5092 | 0.3086 | 0.3843 | 0.9353 | 0.2188 | 0.2121 | 0.2154 | 0.3768 | 0.1831 | 0.2464 | 0.3594 | 0.1394 | 0.2009 | 0.5439 | 0.4133 | 0.4697 | 0.7538 | 0.4569 | 0.5689 | 0.1446 | 0.0945 | 0.1143 | 0.3333 | 0.2424 | 0.2807 | 0.8158 | 0.2183 | 0.3444 | 0.4906 | 0.1576 | 0.2385 | 0.6606 | 0.48 | 0.5560 | 0.8423 | 0.4732 | 0.6060 | 0.4792 | 0.1811 | 0.2629 | 0.3404 | 0.2909 | 0.3137 | 0.4559 | 0.2403 | 0.3147 | 0.3333 | 0.1150 | 0.1711 | 0.5849 | 0.3263 | 0.4189 | 0.7375 | 0.3512 | 0.4758 | 0.2206 | 0.1240 | 0.1587 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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