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---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: robbertfinetuned2408
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. -->
# robbertfinetuned2408
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: 0.3389
- Precision: 0.7133
- Recall: 0.7552
- F1: 0.7337
- Accuracy: 0.8993
## 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: 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: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 236 | 0.4185 | 0.6648 | 0.6218 | 0.6426 | 0.8720 |
| No log | 2.0 | 472 | 0.3389 | 0.7133 | 0.7552 | 0.7337 | 0.8993 |
| 0.4572 | 3.0 | 708 | 0.3503 | 0.7484 | 0.7646 | 0.7564 | 0.9046 |
| 0.4572 | 4.0 | 944 | 0.3875 | 0.7607 | 0.7652 | 0.7629 | 0.9062 |
| 0.1454 | 5.0 | 1180 | 0.4251 | 0.7854 | 0.7786 | 0.7820 | 0.9089 |
| 0.1454 | 6.0 | 1416 | 0.4230 | 0.7878 | 0.7920 | 0.7899 | 0.9152 |
| 0.0544 | 7.0 | 1652 | 0.4555 | 0.7983 | 0.7844 | 0.7913 | 0.9113 |
| 0.0544 | 8.0 | 1888 | 0.4679 | 0.7894 | 0.7821 | 0.7857 | 0.9120 |
### Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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