---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert0410_lrate10b32
  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. -->

# robbert0410_lrate10b32

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: 0.4435
- Precisions: 0.8143
- Recall: 0.8300
- F-measure: 0.8201
- Accuracy: 0.9162

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.6187        | 1.0   | 118  | 0.3807          | 0.8761     | 0.6803 | 0.6943    | 0.8771   |
| 0.3045        | 2.0   | 236  | 0.3297          | 0.7915     | 0.7331 | 0.7475    | 0.8966   |
| 0.1748        | 3.0   | 354  | 0.3503          | 0.7831     | 0.7466 | 0.7553    | 0.9005   |
| 0.1059        | 4.0   | 472  | 0.3670          | 0.8133     | 0.7784 | 0.7893    | 0.9086   |
| 0.0649        | 5.0   | 590  | 0.3926          | 0.7875     | 0.7973 | 0.7908    | 0.9053   |
| 0.0376        | 6.0   | 708  | 0.4213          | 0.7906     | 0.7922 | 0.7906    | 0.9082   |
| 0.0221        | 7.0   | 826  | 0.4435          | 0.8143     | 0.8300 | 0.8201    | 0.9162   |
| 0.014         | 8.0   | 944  | 0.4521          | 0.8170     | 0.8047 | 0.8090    | 0.9142   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0