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---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert_seed33_1311
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_seed33_1311
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: 0.3569
- Precisions: 0.8341
- Recall: 0.8159
- F-measure: 0.8240
- Accuracy: 0.9424
## 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: 33
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.4471 | 1.0 | 236 | 0.2653 | 0.7696 | 0.7076 | 0.7131 | 0.9195 |
| 0.2264 | 2.0 | 472 | 0.2367 | 0.8184 | 0.7497 | 0.7777 | 0.9279 |
| 0.1443 | 3.0 | 708 | 0.2710 | 0.8069 | 0.7735 | 0.7817 | 0.9315 |
| 0.0869 | 4.0 | 944 | 0.2697 | 0.8391 | 0.7998 | 0.8150 | 0.9364 |
| 0.0531 | 5.0 | 1180 | 0.2877 | 0.8622 | 0.7952 | 0.8178 | 0.9393 |
| 0.0373 | 6.0 | 1416 | 0.3171 | 0.8338 | 0.8120 | 0.8204 | 0.9422 |
| 0.0238 | 7.0 | 1652 | 0.3312 | 0.8247 | 0.7921 | 0.8047 | 0.9390 |
| 0.0159 | 8.0 | 1888 | 0.3569 | 0.8341 | 0.8159 | 0.8240 | 0.9424 |
| 0.0122 | 9.0 | 2124 | 0.3832 | 0.8398 | 0.8127 | 0.8238 | 0.9422 |
| 0.0058 | 10.0 | 2360 | 0.4160 | 0.8288 | 0.7975 | 0.8098 | 0.9400 |
| 0.0059 | 11.0 | 2596 | 0.4153 | 0.8321 | 0.8012 | 0.8124 | 0.9405 |
| 0.0045 | 12.0 | 2832 | 0.4399 | 0.8130 | 0.7909 | 0.7994 | 0.9369 |
| 0.0024 | 13.0 | 3068 | 0.4357 | 0.8358 | 0.8026 | 0.8163 | 0.9409 |
| 0.0035 | 14.0 | 3304 | 0.4391 | 0.8374 | 0.8036 | 0.8175 | 0.9414 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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