---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert_seed36_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_seed36_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: 0.3538
- Precisions: 0.8351
- Recall: 0.8079
- F-measure: 0.8173
- Accuracy: 0.9422

## 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: 36
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.4364        | 1.0   | 236  | 0.2547          | 0.8525     | 0.7285 | 0.7372    | 0.9231   |
| 0.2196        | 2.0   | 472  | 0.2772          | 0.8456     | 0.7521 | 0.7718    | 0.9291   |
| 0.1273        | 3.0   | 708  | 0.2681          | 0.8056     | 0.7798 | 0.7897    | 0.9315   |
| 0.0799        | 4.0   | 944  | 0.2971          | 0.8835     | 0.7898 | 0.8158    | 0.9393   |
| 0.0541        | 5.0   | 1180 | 0.3302          | 0.8515     | 0.7815 | 0.8016    | 0.9373   |
| 0.0358        | 6.0   | 1416 | 0.3291          | 0.8140     | 0.7901 | 0.7994    | 0.9385   |
| 0.0217        | 7.0   | 1652 | 0.3538          | 0.8351     | 0.8079 | 0.8173    | 0.9422   |
| 0.0145        | 8.0   | 1888 | 0.3622          | 0.8331     | 0.8000 | 0.8113    | 0.9431   |
| 0.0092        | 9.0   | 2124 | 0.3782          | 0.8190     | 0.8098 | 0.8116    | 0.9402   |
| 0.0091        | 10.0  | 2360 | 0.4023          | 0.8499     | 0.7967 | 0.8149    | 0.9422   |
| 0.0068        | 11.0  | 2596 | 0.3932          | 0.8293     | 0.8062 | 0.8154    | 0.9409   |
| 0.0053        | 12.0  | 2832 | 0.3894          | 0.8415     | 0.7942 | 0.8108    | 0.9412   |
| 0.0023        | 13.0  | 3068 | 0.3910          | 0.8379     | 0.7987 | 0.8127    | 0.9426   |
| 0.0035        | 14.0  | 3304 | 0.3919          | 0.8349     | 0.7990 | 0.8110    | 0.9422   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1