| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: bert-base-uncased |
| tags: |
| - generated_from_trainer |
| - ml-intern |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: privacy-filter-sidecar-bert |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # privacy-filter-sidecar-bert |
|
|
| This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0021 |
| - Precision: 0.9795 |
| - Recall: 0.9832 |
| - F1: 0.9814 |
| - Accuracy: 0.9997 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 5e-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 0.1 |
| - num_epochs: 5 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | 0.0028 | 1.0 | 313 | 0.0021 | 0.9790 | 0.9832 | 0.9811 | 0.9996 | |
| | 0.0014 | 2.0 | 626 | 0.0020 | 0.9816 | 0.9837 | 0.9826 | 0.9997 | |
| | 0.0003 | 3.0 | 939 | 0.0020 | 0.9775 | 0.9821 | 0.9798 | 0.9996 | |
| | 0.0003 | 4.0 | 1252 | 0.0021 | 0.9795 | 0.9832 | 0.9814 | 0.9997 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 5.8.0 |
| - Pytorch 2.11.0+cu130 |
| - Datasets 4.8.5 |
| - Tokenizers 0.22.2 |
|
|
| <!-- ml-intern-provenance --> |
| ## Generated by ML Intern |
|
|
| This model repository was generated by [ML Intern](https://github.com/huggingface/ml-intern), an agent for machine learning research and development on the Hugging Face Hub. |
|
|
| - Try ML Intern: https://smolagents-ml-intern.hf.space |
| - Source code: https://github.com/huggingface/ml-intern |
|
|
| ## Usage |
|
|
| ```python |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
| |
| model_id = 'narcolepticchicken/privacy-filter-sidecar-bert' |
| tokenizer = AutoTokenizer.from_pretrained(model_id) |
| model = AutoModelForCausalLM.from_pretrained(model_id) |
| ``` |
|
|
| For non-causal architectures, replace `AutoModelForCausalLM` with the appropriate `AutoModel` class. |
|
|
