| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: answerdotai/ModernBERT-base |
| tags: |
| - generated_from_trainer |
| datasets: |
| - conll2003 |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: ModernBERT-base-finetuned-pos |
| results: |
| - task: |
| name: Token Classification |
| type: token-classification |
| dataset: |
| name: conll2003 |
| type: conll2003 |
| config: conll2003 |
| split: validation |
| args: conll2003 |
| metrics: |
| - name: Precision |
| type: precision |
| value: 0.9028893991580559 |
| - name: Recall |
| type: recall |
| value: 0.91583569886212 |
| - name: F1 |
| type: f1 |
| value: 0.9093164709424872 |
| - name: Accuracy |
| type: accuracy |
| value: 0.9267220257724449 |
| --- |
| |
| <!-- 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. --> |
|
|
| # ModernBERT-base-finetuned-pos |
|
|
| This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the conll2003 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2935 |
| - Precision: 0.9029 |
| - Recall: 0.9158 |
| - F1: 0.9093 |
| - Accuracy: 0.9267 |
|
|
| ## 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: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 3 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | 0.6485 | 1.0 | 878 | 0.3352 | 0.8911 | 0.9007 | 0.8959 | 0.9159 | |
| | 0.1997 | 2.0 | 1756 | 0.2890 | 0.9031 | 0.9110 | 0.9070 | 0.9246 | |
| | 0.1274 | 3.0 | 2634 | 0.2935 | 0.9029 | 0.9158 | 0.9093 | 0.9267 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.48.0.dev0 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.2.0 |
| - Tokenizers 0.21.0 |
|
|
