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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: 0.5873
- Precisions: 0.8240
- Recall: 0.8030
- F-measure: 0.8121
- Accuracy: 0.9175
## 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: 9e-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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.6115 | 1.0 | 236 | 0.3939 | 0.8592 | 0.6769 | 0.6912 | 0.8757 |
| 0.3166 | 2.0 | 472 | 0.3750 | 0.7447 | 0.7640 | 0.7458 | 0.8897 |
| 0.194 | 3.0 | 708 | 0.3445 | 0.7683 | 0.7462 | 0.7525 | 0.9025 |
| 0.1292 | 4.0 | 944 | 0.3776 | 0.8345 | 0.7570 | 0.7754 | 0.9072 |
| 0.0755 | 5.0 | 1180 | 0.4667 | 0.7897 | 0.8244 | 0.7995 | 0.9079 |
| 0.0556 | 6.0 | 1416 | 0.4879 | 0.8233 | 0.7809 | 0.7973 | 0.9086 |
| 0.0413 | 7.0 | 1652 | 0.4901 | 0.7770 | 0.8020 | 0.7846 | 0.9049 |
| 0.0245 | 8.0 | 1888 | 0.5467 | 0.8159 | 0.7679 | 0.7836 | 0.9086 |
| 0.015 | 9.0 | 2124 | 0.5914 | 0.8156 | 0.7858 | 0.7957 | 0.9109 |
| 0.0129 | 10.0 | 2360 | 0.5640 | 0.8041 | 0.8160 | 0.8079 | 0.9133 |
| 0.0055 | 11.0 | 2596 | 0.5848 | 0.8084 | 0.8044 | 0.8055 | 0.9142 |
| 0.0068 | 12.0 | 2832 | 0.5752 | 0.8097 | 0.7957 | 0.8017 | 0.9140 |
| 0.0036 | 13.0 | 3068 | 0.5873 | 0.8240 | 0.8030 | 0.8121 | 0.9175 |
| 0.0025 | 14.0 | 3304 | 0.5992 | 0.8217 | 0.7913 | 0.8037 | 0.9155 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0
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