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--- |
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license: apache-2.0 |
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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-small-finetuned-xglue-ner-longer50 |
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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: train |
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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: 0.6182136602451839 |
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- name: Recall |
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type: recall |
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value: 0.4222488038277512 |
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- name: F1 |
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type: f1 |
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value: 0.5017768301350392 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9252207821997935 |
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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-small-finetuned-xglue-ner-longer50 |
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This model is a fine-tuned version of [muhtasham/bert-small-finetuned-xglue-ner-longer20](https://huggingface.co/muhtasham/bert-small-finetuned-xglue-ner-longer20) on the wnut_17 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7236 |
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- Precision: 0.6182 |
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- Recall: 0.4222 |
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- F1: 0.5018 |
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- Accuracy: 0.9252 |
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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: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 425 | 0.5693 | 0.5232 | 0.4581 | 0.4885 | 0.9268 | |
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| 0.0032 | 2.0 | 850 | 0.6191 | 0.5281 | 0.4498 | 0.4858 | 0.9260 | |
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| 0.0035 | 3.0 | 1275 | 0.7045 | 0.6011 | 0.4055 | 0.4843 | 0.9241 | |
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| 0.0056 | 4.0 | 1700 | 0.6715 | 0.5571 | 0.4438 | 0.4940 | 0.9261 | |
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| 0.004 | 5.0 | 2125 | 0.6537 | 0.5645 | 0.4294 | 0.4878 | 0.9256 | |
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| 0.0063 | 6.0 | 2550 | 0.6646 | 0.5659 | 0.4211 | 0.4829 | 0.9255 | |
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| 0.0063 | 7.0 | 2975 | 0.6269 | 0.5306 | 0.4354 | 0.4783 | 0.9238 | |
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| 0.003 | 8.0 | 3400 | 0.7235 | 0.5921 | 0.3959 | 0.4746 | 0.9238 | |
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| 0.0051 | 9.0 | 3825 | 0.6334 | 0.5330 | 0.4450 | 0.4850 | 0.9237 | |
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| 0.0047 | 10.0 | 4250 | 0.6408 | 0.5893 | 0.4462 | 0.5078 | 0.9271 | |
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| 0.004 | 11.0 | 4675 | 0.6721 | 0.5840 | 0.4282 | 0.4941 | 0.9255 | |
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| 0.0051 | 12.0 | 5100 | 0.6853 | 0.5795 | 0.4318 | 0.4949 | 0.9258 | |
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| 0.0038 | 13.0 | 5525 | 0.6870 | 0.5789 | 0.4211 | 0.4875 | 0.9249 | |
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| 0.0038 | 14.0 | 5950 | 0.6931 | 0.6032 | 0.4091 | 0.4875 | 0.9241 | |
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| 0.0033 | 15.0 | 6375 | 0.6502 | 0.5965 | 0.4510 | 0.5136 | 0.9266 | |
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| 0.0032 | 16.0 | 6800 | 0.6941 | 0.6126 | 0.4426 | 0.5139 | 0.9267 | |
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| 0.0042 | 17.0 | 7225 | 0.6603 | 0.5856 | 0.4462 | 0.5064 | 0.9266 | |
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| 0.0016 | 18.0 | 7650 | 0.6870 | 0.6121 | 0.4474 | 0.5169 | 0.9273 | |
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| 0.0028 | 19.0 | 8075 | 0.6922 | 0.5906 | 0.4366 | 0.5021 | 0.9250 | |
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| 0.0023 | 20.0 | 8500 | 0.7096 | 0.6089 | 0.4246 | 0.5004 | 0.9250 | |
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| 0.0023 | 21.0 | 8925 | 0.6763 | 0.5772 | 0.4426 | 0.5010 | 0.9261 | |
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| 0.0025 | 22.0 | 9350 | 0.6880 | 0.5696 | 0.4258 | 0.4873 | 0.9241 | |
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| 0.0018 | 23.0 | 9775 | 0.6759 | 0.5836 | 0.4426 | 0.5034 | 0.9259 | |
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| 0.0017 | 24.0 | 10200 | 0.7044 | 0.6198 | 0.4270 | 0.5057 | 0.9262 | |
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| 0.0018 | 25.0 | 10625 | 0.6948 | 0.6040 | 0.4306 | 0.5028 | 0.9245 | |
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| 0.0018 | 26.0 | 11050 | 0.6930 | 0.5948 | 0.4354 | 0.5028 | 0.9255 | |
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| 0.0018 | 27.0 | 11475 | 0.7077 | 0.6048 | 0.4246 | 0.4989 | 0.9250 | |
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| 0.0023 | 28.0 | 11900 | 0.7127 | 0.6103 | 0.4270 | 0.5025 | 0.9252 | |
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| 0.0013 | 29.0 | 12325 | 0.7253 | 0.6243 | 0.4234 | 0.5046 | 0.9254 | |
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| 0.0015 | 30.0 | 12750 | 0.7236 | 0.6182 | 0.4222 | 0.5018 | 0.9252 | |
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### Framework versions |
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- Transformers 4.21.1 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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