| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: google-bert/bert-base-cased |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - precision |
| | - recall |
| | - f1 |
| | - accuracy |
| | model-index: |
| | - name: bert-base-cased-finetuned-ner5 |
| | 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. --> |
| |
|
| | # bert-base-cased-finetuned-ner5 |
| |
|
| | This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.6873 |
| | - Precision: 0.8196 |
| | - Recall: 0.8344 |
| | - F1: 0.8269 |
| | - Accuracy: 0.9611 |
| |
|
| | ## 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: 3e-05 |
| | - train_batch_size: 32 |
| | - eval_batch_size: 32 |
| | - seed: 42 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: cosine_with_restarts |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 8 |
| | - label_smoothing_factor: 0.1 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | | 0.726 | 1.0 | 1188 | 0.7145 | 0.7742 | 0.7897 | 0.7819 | 0.9525 | |
| | | 0.6889 | 2.0 | 2376 | 0.6936 | 0.8085 | 0.8085 | 0.8085 | 0.9573 | |
| | | 0.6676 | 3.0 | 3564 | 0.6818 | 0.8023 | 0.8239 | 0.8129 | 0.9584 | |
| | | 0.6569 | 4.0 | 4752 | 0.6792 | 0.8154 | 0.8293 | 0.8223 | 0.9610 | |
| | | 0.6452 | 5.0 | 5940 | 0.6883 | 0.8182 | 0.8254 | 0.8218 | 0.9600 | |
| | | 0.6371 | 6.0 | 7128 | 0.6876 | 0.8237 | 0.8336 | 0.8286 | 0.9615 | |
| | | 0.6342 | 7.0 | 8316 | 0.6863 | 0.8194 | 0.8370 | 0.8281 | 0.9615 | |
| | | 0.6298 | 8.0 | 9504 | 0.6873 | 0.8196 | 0.8344 | 0.8269 | 0.9611 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.50.1 |
| | - Pytorch 2.6.0+cu124 |
| | - Datasets 3.4.1 |
| | - Tokenizers 0.21.1 |
| | |
