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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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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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--- |
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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 [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1592 |
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- Precision: 0.7852 |
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- Recall: 0.8012 |
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- F1: 0.7931 |
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- Accuracy: 0.9701 |
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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: 8e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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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: 8 |
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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 | 131 | 0.1607 | 0.6254 | 0.6801 | 0.6516 | 0.9538 | |
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| No log | 2.0 | 262 | 0.1188 | 0.7437 | 0.7695 | 0.7564 | 0.9670 | |
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| No log | 3.0 | 393 | 0.1264 | 0.7556 | 0.7750 | 0.7652 | 0.9675 | |
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| 0.0923 | 4.0 | 524 | 0.1344 | 0.7622 | 0.7858 | 0.7738 | 0.9680 | |
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| 0.0923 | 5.0 | 655 | 0.1442 | 0.7741 | 0.7835 | 0.7788 | 0.9694 | |
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| 0.0923 | 6.0 | 786 | 0.1501 | 0.7892 | 0.8104 | 0.7997 | 0.9703 | |
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| 0.0923 | 7.0 | 917 | 0.1584 | 0.7750 | 0.7964 | 0.7856 | 0.9694 | |
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| 0.0133 | 8.0 | 1048 | 0.1592 | 0.7852 | 0.8012 | 0.7931 | 0.9701 | |
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### Framework versions |
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- Transformers 4.30.1 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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