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---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert_testrun
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. -->
# robbert_testrun
This model is a fine-tuned version of [pdelobelle/robbert-v2-dutch-base](https://huggingface.co/pdelobelle/robbert-v2-dutch-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5609
- Precisions: 0.8558
- Recall: 0.8234
- F-measure: 0.8375
- Accuracy: 0.9294
## 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: 7.5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 14
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.4449 | 1.0 | 285 | 0.3985 | 0.8120 | 0.6963 | 0.7240 | 0.8907 |
| 0.19 | 2.0 | 570 | 0.3572 | 0.8522 | 0.7715 | 0.8031 | 0.9118 |
| 0.0946 | 3.0 | 855 | 0.3966 | 0.8331 | 0.7816 | 0.8013 | 0.9168 |
| 0.0492 | 4.0 | 1140 | 0.4321 | 0.8295 | 0.8127 | 0.8189 | 0.9187 |
| 0.034 | 5.0 | 1425 | 0.4523 | 0.8123 | 0.8122 | 0.8097 | 0.9241 |
| 0.0221 | 6.0 | 1710 | 0.5082 | 0.8111 | 0.8109 | 0.8097 | 0.9222 |
| 0.015 | 7.0 | 1995 | 0.5375 | 0.8587 | 0.7934 | 0.8194 | 0.9212 |
| 0.0121 | 8.0 | 2280 | 0.5233 | 0.8542 | 0.8256 | 0.8373 | 0.9292 |
| 0.0077 | 9.0 | 2565 | 0.5259 | 0.8277 | 0.8235 | 0.8246 | 0.9286 |
| 0.0063 | 10.0 | 2850 | 0.5609 | 0.8558 | 0.8234 | 0.8375 | 0.9294 |
| 0.003 | 11.0 | 3135 | 0.5672 | 0.8176 | 0.8197 | 0.8169 | 0.9271 |
| 0.002 | 12.0 | 3420 | 0.5968 | 0.8555 | 0.8184 | 0.8347 | 0.9294 |
| 0.0021 | 13.0 | 3705 | 0.5846 | 0.8315 | 0.8222 | 0.8263 | 0.9269 |
| 0.0016 | 14.0 | 3990 | 0.5905 | 0.8352 | 0.8167 | 0.8251 | 0.9263 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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