---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert0210_lrate5b32
  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. -->

# robbert0210_lrate5b32

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: 0.3497
- Precisions: 0.8168
- Recall: 0.7629
- F-measure: 0.7745
- Accuracy: 0.9044

## 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: 32
- eval_batch_size: 32
- 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 | Precisions | Recall | F-measure | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| No log        | 1.0   | 118  | 0.4100          | 0.8801     | 0.6728 | 0.6931    | 0.8747   |
| No log        | 2.0   | 236  | 0.3638          | 0.7841     | 0.7186 | 0.7176    | 0.8871   |
| No log        | 3.0   | 354  | 0.3533          | 0.8013     | 0.7568 | 0.7535    | 0.8967   |
| No log        | 4.0   | 472  | 0.3497          | 0.8168     | 0.7629 | 0.7745    | 0.9044   |
| 0.3409        | 5.0   | 590  | 0.3781          | 0.7928     | 0.7789 | 0.7814    | 0.9046   |
| 0.3409        | 6.0   | 708  | 0.4072          | 0.8013     | 0.7836 | 0.7884    | 0.9073   |
| 0.3409        | 7.0   | 826  | 0.4193          | 0.8047     | 0.8026 | 0.8012    | 0.9082   |
| 0.3409        | 8.0   | 944  | 0.4197          | 0.8121     | 0.8021 | 0.8049    | 0.9103   |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3