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---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert1010_lrate10b16
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. -->
# robbert1010_lrate10b16
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: 0.6021
- Precisions: 0.8323
- Recall: 0.7951
- F-measure: 0.8088
- Accuracy: 0.9164
## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.6104 | 1.0 | 236 | 0.4304 | 0.8532 | 0.6700 | 0.6852 | 0.8707 |
| 0.32 | 2.0 | 472 | 0.3520 | 0.7761 | 0.7551 | 0.7413 | 0.8916 |
| 0.1989 | 3.0 | 708 | 0.3686 | 0.7500 | 0.7591 | 0.7465 | 0.9010 |
| 0.1331 | 4.0 | 944 | 0.4045 | 0.8289 | 0.7666 | 0.7835 | 0.9090 |
| 0.0784 | 5.0 | 1180 | 0.4307 | 0.8052 | 0.7759 | 0.7890 | 0.9092 |
| 0.0682 | 6.0 | 1416 | 0.4696 | 0.8101 | 0.7658 | 0.7770 | 0.9059 |
| 0.04 | 7.0 | 1652 | 0.5078 | 0.8450 | 0.7642 | 0.7820 | 0.9096 |
| 0.0256 | 8.0 | 1888 | 0.5718 | 0.8007 | 0.7830 | 0.7906 | 0.9058 |
| 0.0219 | 9.0 | 2124 | 0.5508 | 0.8078 | 0.7987 | 0.8000 | 0.9093 |
| 0.0162 | 10.0 | 2360 | 0.5786 | 0.8256 | 0.7791 | 0.7946 | 0.9141 |
| 0.0117 | 11.0 | 2596 | 0.5979 | 0.8360 | 0.7912 | 0.8046 | 0.9168 |
| 0.011 | 12.0 | 2832 | 0.6021 | 0.8323 | 0.7951 | 0.8088 | 0.9164 |
| 0.0079 | 13.0 | 3068 | 0.6115 | 0.8337 | 0.7956 | 0.8088 | 0.9166 |
| 0.0064 | 14.0 | 3304 | 0.6100 | 0.8305 | 0.7932 | 0.8064 | 0.9164 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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