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---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert0510_lrate9b16
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. -->
# robbert0510_lrate9b16
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: 0.5895
- Precisions: 0.8184
- Recall: 0.7998
- F-measure: 0.8078
- Accuracy: 0.9148
## 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: 8e-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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.5957 | 1.0 | 236 | 0.4045 | 0.8529 | 0.6860 | 0.6940 | 0.8784 |
| 0.3024 | 2.0 | 472 | 0.3456 | 0.7564 | 0.7584 | 0.7471 | 0.8964 |
| 0.1843 | 3.0 | 708 | 0.3792 | 0.8188 | 0.7691 | 0.7741 | 0.9087 |
| 0.1163 | 4.0 | 944 | 0.4231 | 0.8317 | 0.7678 | 0.7878 | 0.9060 |
| 0.0753 | 5.0 | 1180 | 0.4595 | 0.8051 | 0.7846 | 0.7911 | 0.9070 |
| 0.0496 | 6.0 | 1416 | 0.4942 | 0.8188 | 0.7803 | 0.7960 | 0.9087 |
| 0.0321 | 7.0 | 1652 | 0.5121 | 0.7966 | 0.7927 | 0.7900 | 0.9103 |
| 0.0246 | 8.0 | 1888 | 0.5057 | 0.8155 | 0.7959 | 0.8030 | 0.9148 |
| 0.0156 | 9.0 | 2124 | 0.5445 | 0.8039 | 0.7924 | 0.7967 | 0.9109 |
| 0.0118 | 10.0 | 2360 | 0.5646 | 0.8151 | 0.7948 | 0.8032 | 0.9140 |
| 0.0083 | 11.0 | 2596 | 0.5911 | 0.8387 | 0.7872 | 0.8075 | 0.9138 |
| 0.0052 | 12.0 | 2832 | 0.5895 | 0.8184 | 0.7998 | 0.8078 | 0.9148 |
| 0.0038 | 13.0 | 3068 | 0.5839 | 0.8193 | 0.7987 | 0.8078 | 0.9149 |
| 0.0026 | 14.0 | 3304 | 0.5911 | 0.8195 | 0.7926 | 0.8041 | 0.9135 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0
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