| --- |
| license: apache-2.0 |
| base_model: bert-base-cased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: token_classify |
| results: [] |
| datasets: |
| - eriktks/conll2003 |
| pipeline_tag: token-classification |
| library_name: flair |
| --- |
| |
| <!-- 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. --> |
|
|
| # token_classify |
| |
| This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0632 |
| - Precision: 0.9295 |
| - Recall: 0.9497 |
| - F1: 0.9395 |
| - Accuracy: 0.9857 |
| |
| ## 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: 2e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 3 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | 0.077 | 1.0 | 1756 | 0.0641 | 0.9060 | 0.9340 | 0.9198 | 0.9816 | |
| | 0.0346 | 2.0 | 3512 | 0.0695 | 0.9234 | 0.9419 | 0.9326 | 0.9840 | |
| | 0.0211 | 3.0 | 5268 | 0.0632 | 0.9295 | 0.9497 | 0.9395 | 0.9857 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.42.4 |
| - Pytorch 2.3.1+cu121 |
| - Datasets 2.21.0 |
| - Tokenizers 0.19.1 |
