| --- |
| library_name: transformers |
| license: mit |
| base_model: pdelobelle/robbert-v2-dutch-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| - accuracy |
| model-index: |
| - name: results |
| 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. --> |
|
|
| # results |
|
|
| This model is a fine-tuned version of [pdelobelle/robbert-v2-dutch-base](https://huggingface.co/pdelobelle/robbert-v2-dutch-base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0945 |
| - F1: 0.9841 |
| - Accuracy: 0.9881 |
| - F1 Yes: 0.9760 |
|
|
| ## 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: 1e-05 |
| - train_batch_size: 4 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 16 |
| - 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: cosine |
| - lr_scheduler_warmup_steps: 0.1 |
| - num_epochs: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | F1 Yes | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:------:| |
| | 0.6781 | 1.0 | 1133 | 0.2196 | 0.9637 | 0.9735 | 0.9449 | |
| | 0.1439 | 2.0 | 2266 | 0.1432 | 0.9755 | 0.9819 | 0.9630 | |
| | 0.2089 | 3.0 | 3399 | 0.1242 | 0.9828 | 0.9872 | 0.9742 | |
| | 0.0851 | 4.0 | 4532 | 0.1035 | 0.9851 | 0.9890 | 0.9775 | |
| | 0.1160 | 5.0 | 5665 | 0.1555 | 0.9827 | 0.9872 | 0.9738 | |
| | 0.0628 | 6.0 | 6798 | 0.2245 | 0.9796 | 0.9850 | 0.9691 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.0.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
| |
