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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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- wikiann |
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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: wikiann |
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type: wikiann |
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config: ace |
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split: validation |
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args: ace |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.34523809523809523 |
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- name: Recall |
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type: recall |
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value: 0.5420560747663551 |
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- name: F1 |
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type: f1 |
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value: 0.4218181818181818 |
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- name: Accuracy |
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type: accuracy |
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value: 0.8688172043010752 |
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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 wikiann dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5677 |
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- Precision: 0.3452 |
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- Recall: 0.5421 |
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- F1: 0.4218 |
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- Accuracy: 0.8688 |
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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: 10 |
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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 | 13 | 0.5728 | 0.2077 | 0.3551 | 0.2621 | 0.8199 | |
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| No log | 2.0 | 26 | 0.5687 | 0.2889 | 0.3645 | 0.3223 | 0.8312 | |
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| No log | 3.0 | 39 | 0.5447 | 0.2857 | 0.4486 | 0.3491 | 0.8425 | |
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| No log | 4.0 | 52 | 0.5509 | 0.2881 | 0.4766 | 0.3592 | 0.8489 | |
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| No log | 5.0 | 65 | 0.5751 | 0.3121 | 0.4579 | 0.3712 | 0.8511 | |
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| No log | 6.0 | 78 | 0.5358 | 0.3851 | 0.5794 | 0.4627 | 0.8667 | |
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| No log | 7.0 | 91 | 0.5484 | 0.3491 | 0.5514 | 0.4275 | 0.8645 | |
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| No log | 8.0 | 104 | 0.5671 | 0.3580 | 0.5421 | 0.4312 | 0.8672 | |
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| No log | 9.0 | 117 | 0.5666 | 0.3494 | 0.5421 | 0.4249 | 0.8688 | |
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| No log | 10.0 | 130 | 0.5677 | 0.3452 | 0.5421 | 0.4218 | 0.8688 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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