| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google-bert/bert-base-uncased |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: bert-BBc-classifier |
| results: [] |
| --- |
| # BERT News Category Classifier |
|
|
| This model is a fine-tuned version of `bert-base-uncased` optimized to classify articles into 5 categories (Business, Tech, Politics, Sports, Entertainment). |
|
|
| ## Model Description |
| * **Architecture:** BERT-base-uncased with frozen base layers for training efficiency. |
| * **Task:** Multi-class Text Classification (NLP Pipeline). |
| * **Performance:** Achieved a 0.96 Macro-F1 score on evaluation. |
|
|
| ## Training and Evaluation Data |
| * **Dataset:** BBC News Dataset. |
| * **Preprocessing:** Cleaned text fields tokenized using the standard BERT WordPiece tokenizer. |
|
|
| ## Intended Uses & Limitations |
| This model is intended for production-ready news classification pipelines. It is lightweight due to layer-freezing optimization during training. |
| # bert-BBc-classifier |
|
|
| This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0873 |
|
|
| ## 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: 0.0002 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - 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 |
| - num_epochs: 5 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 0.0635 | 1.0 | 213 | 0.1708 | |
| | 0.0695 | 2.0 | 426 | 0.1116 | |
| | 0.0677 | 3.0 | 639 | 0.0842 | |
| | 0.0525 | 4.0 | 852 | 0.0882 | |
| | 0.0511 | 5.0 | 1065 | 0.0873 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.57.3 |
| - Pytorch 2.9.0+cu126 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.1 |
| |
