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---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robdataaugmentation1511
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. -->
# robdataaugmentation1511
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: 0.4187
- Precisions: 0.8503
- Recall: 0.8197
- F-measure: 0.8320
- Accuracy: 0.9446
## 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: 34
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.4276 | 1.0 | 284 | 0.2688 | 0.8001 | 0.7195 | 0.7402 | 0.9200 |
| 0.1871 | 2.0 | 568 | 0.2595 | 0.8183 | 0.7803 | 0.7948 | 0.9308 |
| 0.0942 | 3.0 | 852 | 0.2800 | 0.8083 | 0.8047 | 0.8042 | 0.9366 |
| 0.0542 | 4.0 | 1136 | 0.2841 | 0.8228 | 0.8232 | 0.8212 | 0.9402 |
| 0.0365 | 5.0 | 1420 | 0.3355 | 0.8472 | 0.8056 | 0.8224 | 0.9393 |
| 0.0228 | 6.0 | 1704 | 0.3860 | 0.8501 | 0.8009 | 0.8211 | 0.9405 |
| 0.0141 | 7.0 | 1988 | 0.3997 | 0.8320 | 0.8175 | 0.8233 | 0.9409 |
| 0.0132 | 8.0 | 2272 | 0.4225 | 0.8478 | 0.8025 | 0.8164 | 0.9397 |
| 0.0077 | 9.0 | 2556 | 0.3890 | 0.8258 | 0.8410 | 0.8312 | 0.9429 |
| 0.006 | 10.0 | 2840 | 0.3954 | 0.8354 | 0.8150 | 0.8235 | 0.9402 |
| 0.0045 | 11.0 | 3124 | 0.4266 | 0.8441 | 0.8136 | 0.8246 | 0.9424 |
| 0.0037 | 12.0 | 3408 | 0.4171 | 0.8364 | 0.8174 | 0.8245 | 0.9426 |
| 0.0021 | 13.0 | 3692 | 0.4221 | 0.8461 | 0.8192 | 0.8294 | 0.9434 |
| 0.0018 | 14.0 | 3976 | 0.4187 | 0.8503 | 0.8197 | 0.8320 | 0.9446 |
### Framework versions
- Transformers 4.35.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1
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