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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: bert-base-uncased |
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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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model-index: |
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- name: pii_bert_model |
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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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# pii_bert_model |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1020 |
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- Precision: 0.9748 |
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- Recall: 0.9744 |
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- F1: 0.9745 |
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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: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:| |
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| 0.1362 | 1.0 | 150 | 0.1090 | 0.9663 | 0.9642 | 0.9645 | |
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| 0.0974 | 2.0 | 300 | 0.1192 | 0.9632 | 0.9619 | 0.9620 | |
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| 0.0736 | 3.0 | 450 | 0.0867 | 0.9696 | 0.9693 | 0.9693 | |
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| 0.0605 | 4.0 | 600 | 0.1111 | 0.9696 | 0.9682 | 0.9685 | |
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| 0.0445 | 5.0 | 750 | 0.0895 | 0.9729 | 0.9726 | 0.9726 | |
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| 0.0343 | 6.0 | 900 | 0.0952 | 0.9727 | 0.9719 | 0.9721 | |
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| 0.023 | 7.0 | 1050 | 0.0991 | 0.9745 | 0.9740 | 0.9741 | |
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| 0.0179 | 8.0 | 1200 | 0.1020 | 0.9748 | 0.9744 | 0.9745 | |
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### Framework versions |
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- Transformers 4.50.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.5.0 |
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- Tokenizers 0.21.1 |
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